%0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e67318 %T Bridging Data Gaps in Emergency Care: The NIGHTINGALE Project and the Future of AI in Mass Casualty Management %A , %A Caviglia,Marta %+ Center for Research and Training in Disaster Medicine, Humanitarian Aid and Global Health (CRIMEDIM), Università del Piemonte Orientale, Via Lanino 1, Novara, 28100, Italy, 39 0321 660 620, marta.caviglia@med.uniupo.it %K AI %K technology %K mass casualty incident %K incident management %K artificial intelligence %K emergency care %K MCI %K data gaps %K tool %D 2025 %7 10.4.2025 %9 Viewpoint %J J Med Internet Res %G English %X In the context of mass casualty incident (MCI) management, artificial intelligence (AI) represents a promising future, offering potential improvements in processes such as triage, decision support, and resource optimization. However, the effectiveness of AI is heavily reliant on the availability of quality data. Currently, MCI data are scarce and difficult to obtain, as critical information regarding patient demographics, vital signs, and treatment responses is often missing or incomplete, particularly in the prehospital setting. Although the NIGHTINGALE (Novel Integrated Toolkit for Enhanced Pre-Hospital Life Support and Triage in Challenging and Large Emergencies) project is actively addressing these challenges by developing a comprehensive toolkit designed to support first responders and enhance data collection during MCIs, significant work remains to ensure the tools are fully operational and can effectively integrate continuous monitoring and data management. To further advance these efforts, we provide a series of recommendation, advocating for increased European Union funding to facilitate the generation of diverse and high-quality datasets essential for training AI models, including the application of transfer learning and the development of tools supporting data collection during MCIs, while fostering continuous collaboration between end users and technical developers. By securing these resources, we can enhance the efficiency and adaptability of AI applications in emergency care, bridging the current data gaps and ultimately improving outcomes during critical situations. %M 40209223 %R 10.2196/67318 %U https://www.jmir.org/2025/1/e67318 %U https://doi.org/10.2196/67318 %U http://www.ncbi.nlm.nih.gov/pubmed/40209223 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e66959 %T Factors Influencing Information Distortion in Electronic Nursing Records: Qualitative Study %A Wang,Jianan %A Xu,Yihong %A Yang,Zhichao %A Zhang,Jie %A Zhang,Xiaoxiao %A Li,Wen %A Sun,Yushu %A Pan,Hongying %+ Department of Nursing, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, 3 Qingchun East Road, Hangzhou, 310016, China, 86 13857188922, 3191016@zju.edu.cn %K information distortion %K electronic health record %K qualitative research %K ethics %K nursing %D 2025 %7 9.4.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: Information distortion in nursing records poses significant risks to patient safety and impedes the enhancement of care quality. The introduction of information technologies, such as decision support systems and predictive models, expands the possibilities for using health data but also complicates the landscape of information distortion. Only by identifying influencing factors about information distortion can care quality and patient safety be ensured. Objective: This study aims to explore the factors influencing information distortion in electronic nursing records (ENRs) within the context of China’s health care system and provide appropriate recommendations to address these distortions. Methods: This qualitative study used semistructured interviews conducted with 14 nurses from a Class-A tertiary hospital. Participants were primarily asked about their experiences with and observations of information distortion in clinical practice, as well as potential influencing factors and corresponding countermeasures. Data were analyzed using inductive content analysis, which involved initial preparation, line-by-line coding, the creation of categories, and abstraction. Results: The analysis identified 4 categories and 10 subcategories: (1) nurse-related factors—skills, awareness, and work habits; (2) patient-related factors—willingness and ability; (3) operational factors—work characteristics and system deficiencies; and (4) organizational factors—management system, organizational climate, and team collaboration. Conclusions: Although some factors influencing information distortion in ENRs are similar to those observed in paper-based records, others are unique to the digital age. As health care continues to embrace digitalization, it is crucial to develop and implement strategies to mitigate information distortion. Regular training and education programs, robust systems and mechanisms, and optimized human resources and organizational practices are strongly recommended. %M 40202777 %R 10.2196/66959 %U https://www.jmir.org/2025/1/e66959 %U https://doi.org/10.2196/66959 %U http://www.ncbi.nlm.nih.gov/pubmed/40202777 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 13 %N %P e66451 %T Construction and Application of an Information Closed-Loop Management System for Maternal and Neonatal Access and Exit Rooms: Non Randomized Controlled Trial %A Jia,Shafeng %A Zhu,Naifeng %A Liu,Jia %A Cheng,Niankai %A Jiang,Ling %A Yang,Jing %K mother-infant same-room management %K information-based identity verification %K closed-loop management system %K newborn safety management %D 2025 %7 7.4.2025 %9 %J JMIR Med Inform %G English %X Background: Traditional management methods can no longer meet the demand for efficient and accurate neonatal care. There is a need for an information-based and intelligent management system. Objective: This study aimed to construct an information closed-loop management system to improve the accuracy of identification in mother-infant rooming-in care units and enhance the efficiency of infant admission and discharge management. Methods: Mothers who delivered between January 2023 and June 2023 were assigned to the control group (n=200), while those who delivered between July 2023 and May 2024 were assigned to the research group (n=200). The control group adopted traditional management methods, whereas the research group implemented closed-loop management. Barcode technology, a wireless network, mobile terminals, and other information technology equipments were used to complete the closed loop of newborn exit and entry management. Data on the satisfaction of mothers and their families, the monthly average qualification rate of infant identity verification, and the qualification rate of infant consultation time were collected and statistically analyzed before and after the closed-loop process was implemented. Results: After the closed-loop process was implemented, the monthly average qualification rate of infant identity verification increased to 99.45 (SD 1.34), significantly higher than the control group before implementation 83.58 (SD 1.92) (P=.02). The satisfaction of mothers and their families was 96.45 (SD 3.32), higher than that of the control group before the closed-loop process was implemented 92.82 (SD 4.73) (P=.01). Additionally, the separation time between infants and mothers was restricted to under 1 hour. Conclusion: The construction and application of the information closed-loop management system significantly improved the accuracy and efficiency of maternal and infant identity verification, enhancing the safety of newborns. %R 10.2196/66451 %U https://medinform.jmir.org/2025/1/e66451 %U https://doi.org/10.2196/66451 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 13 %N %P e66466 %T Identifying Patient-Reported Outcome Measure Documentation in Veterans Health Administration Chiropractic Clinic Notes: Natural Language Processing Analysis %A Coleman,Brian C %A Corcoran,Kelsey L %A Brandt,Cynthia A %A Goulet,Joseph L %A Luther,Stephen L %A Lisi,Anthony J %K Veterans Health Administration %K natural language processing %K quality of health care %K chiropractic %K patient reported outcome measures %K NLP %K AI %K artificial intelligence %K veteran %K chiropractor %K integrated health cohort %K musculoskeletal diagnosis %K musculoskeletal %K quality of care %K care %K PROM %K neural network %K chiropractic care %D 2025 %7 2.4.2025 %9 %J JMIR Med Inform %G English %X Background: The use of patient-reported outcome measures (PROMs) is an expected component of high-quality, measurement-based chiropractic care. The largest health care system offering integrated chiropractic care is the Veterans Health Administration (VHA). Challenges limit monitoring PROM use as a care quality metric at a national scale in the VHA. Structured data are unavailable, with PROMs often embedded within clinic text notes as unstructured data requiring time-intensive, peer-conducted chart review for evaluation. Natural language processing (NLP) of clinic text notes is one promising solution to extracting care quality data from unstructured text. Objective: This study aims to test NLP approaches to identify PROMs documented in VHA chiropractic text notes. Methods: VHA chiropractic notes from October 1, 2017, to September 30, 2020, were obtained from the VHA Musculoskeletal Diagnosis/Complementary and Integrative Health Cohort. A rule-based NLP model built using medspaCy and spaCy was evaluated on text matching and note categorization tasks. SpaCy was used to build bag-of-words, convoluted neural networks, and ensemble models for note categorization. Performance metrics for each model and task included precision, recall, and F-measure. Cross-validation was used to validate performance metric estimates for the statistical and machine-learning models. Results: Our sample included 377,213 visit notes from 56,628 patients. The rule-based model performance was good for soft-boundary text-matching (precision=81.1%, recall=96.7%, and F-measure=88.2%) and excellent for note categorization (precision=90.3%, recall=99.5%, and F-measure=94.7%). Cross-validation performance of the statistical and machine learning models for the note categorization task was very good overall, but lower than rule-based model performance. The overall prevalence of PROM documentation was low (17.0%). Conclusions: We evaluated multiple NLP methods across a series of tasks, with optimal performance achieved using a rule-based method. By leveraging NLP approaches, we can overcome the challenges posed by unstructured clinical text notes to track documented PROM use. Overall documented use of PROMs in chiropractic notes was low and highlights a potential for quality improvement. This work represents a methodological advancement in the identification and monitoring of documented use of PROMs to ensure consistent, high-quality chiropractic care for veterans. %R 10.2196/66466 %U https://medinform.jmir.org/2025/1/e66466 %U https://doi.org/10.2196/66466 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 14 %N %P e54651 %T Policy Spotlight Effects on Critical Time-Sensitive Diseases: Nationwide Retrospective Cohort Study on Taiwan’s Hospital Emergency Capability Categorization Policy %A Lin,Chih-Yuan %A Liu,Chih-Ching %A Huang,Yu-Tung %A Lee,Yue-Chune %+ Institute of Health and Welfare, College of Medicine, Yangming Campus, National Yang Ming Chiao Tung University, Taipei, Taiwan, No.155, Sec.2, Linong Street, Taipei City, 112, Taiwan, 886 225916681 ext 1526, DAS73@tpech.gov.tw %K categorization of hospital emergency capability %K quality %K time-sensitive diseases %K emergency care %K difference-in-differences %D 2025 %7 25.3.2025 %9 Original Paper %J Interact J Med Res %G English %X Background: Taiwan’s categorization of hospital emergency capability (CHEC) policy is designed to regionalize and dispatch critical patients. The policy was designed in 2009 to improve the quality of emergency care for critical time-sensitive diseases (CTSDs). The CHEC policy primarily uses time-based quality surveillance indicators. Objective: We aimed to investigate the impact of Taiwan’s CHEC policy on CTSDs. Methods: Using Taiwan’s 2005 Longitudinal Health Insurance Database, this nationwide retrospective cohort study examined the CHEC policy’s impact from 2005 to 2011. Propensity score matching and difference-in-differences analysis within a generalized estimating equation framework were used to compare pre- and postimplementation periods. The study focused on acute ischemic stroke (AIS), ST-segment elevation myocardial infarction (STEMI), septic shock, and major trauma. AIS and STEMI cases, monitored with time-based indicators, were evaluated for adherence to diagnostic and treatment guidelines as process quality measures. Mortality and medical use served as outcome indicators. Major trauma, with evolving guidelines and no time-based monitoring, acted as a control to test for policy spotlight effects. Results: In our cohort of 9923 patients, refined through 1:1 propensity score matching, 5566 (56.09%) were male and were mostly older adults. Our analysis revealed that the CHEC policy effectively improved system efficiency and patient outcomes, resulting in significant reductions in medical orders (–7.29 items, 95% CI –10.09 to –4.48; P<.001), short-term mortality rates (–0.09%, 95% CI –0.17% to –0.02%; P=.01) and long-term mortality rates (–0.09%, 95% CI –0.15% to –0.04%; P=.001), and total medical expenses (–5328.35 points per case, 95% CI –10,387.10 to –269.60; P=.04), despite a modest increase in diagnostic fees (376.37 points, 95% CI 92.42-660.33; P=.01). The CHEC policy led to notable increases in diagnostic fees, major treatments, and medical orders for AIS and STEMI cases. For AIS cases, significant increases were observed in major treatments (β=0.77; 95% CI 0.21-1.33; P=.007) and medical orders (β=15.20; 95% CI 5.28-25.11; P=.003) compared to major trauma. In STEMI cases, diagnostic fees significantly increased (β=1983.75; 95% CI 84.28-3883.21; P=.04), while upward transfer rates significantly decreased (β=–0.59; 95% CI –1.18 to –0.001; P=.049). There were also trends toward increased major treatments (β=0.30; 95% CI –0.03 to 0.62, P=.07), medical orders (β=11.92; 95% CI –0.90 to 24.73; P=.07), and medical expenses (β=24,275.54; 95% CI –640.71 to 4,991,991.78; P=.06), although these were not statistically significant. In contrast, no significant changes were identified in process or outcome quality indicators for septic shock. These findings suggest policy spotlight effects, reflecting a greater emphasis on diseases directly prioritized under the CHEC policy. Conclusions: The CHEC policy demonstrated the dual benefits of reducing costs and improving patient outcomes. We observed unintended consequences of policy spotlight effects, which led to a disproportionate improvement in guideline adherence and process quality for CTSDs with time-based surveillance indicators. %M 40132185 %R 10.2196/54651 %U https://www.i-jmr.org/2025/1/e54651 %U https://doi.org/10.2196/54651 %U http://www.ncbi.nlm.nih.gov/pubmed/40132185 %0 Journal Article %@ 2369-1999 %I JMIR Publications %V 11 %N %P e64809 %T Monthly Variations in Colorectal Cancer Screening Tests Among Federally Qualified Health Center Patients in Missouri: Quality Improvement Project %A McElroy,Jane A %A Smith,Jamie B %A Everett,Kevin D %K colorectal cancer screening %K federally qualified health center %K FQHC %K fecal immunochemical test %K FIT %K FIT-DNA %K colorectal cancer %K CRC %K cancer %K cancer screening %K colonoscopy %K United States %K health center %K quality improvement %D 2025 %7 19.3.2025 %9 %J JMIR Cancer %G English %X Background: Cancer is the second leading cause of death in the United States. Compelling evidence shows screening detects colorectal cancer (CRC) at earlier stages and prevents the development of CRC through the removal of precancerous polyps. The Healthy People 2030 goal for CRC screening is 68.3%, but only 36.5% of Missouri federally qualified health center patients aged 50‐75 years are up-to-date on CRC screening. For average risk patients, there are three commonly used screening tests in the United States—two types of stool tests collected at home (fecal immunochemical test [FIT]–immunochemical fecal occult blood test [FOBT] and FIT-DNA, such as Cologuard) and colonoscopies completed at procedural centers. Objective: This study aims to examine variation by month for the three types of CRC testing to evaluate consistent patient care by clinical staff. Methods: Data from 31 federally qualified health center clinics in Missouri from 2011 to 2023 were analyzed. A sample of 34,124 unique eligible “average risk” patients defined as persons not having a personal history of CRC or certain types of polyps, family history of CRC, personal history of inflammatory bowel disease, and personal history of receiving radiation to the abdomen or pelvic to treat a previous cancer or confirmed or suspected hereditary CRC syndrome. Another eligibility criterion is that patients need to be seen at least once at the clinic to be included in the denominator for the screening rate calculation. Descriptive statistics characterize the sample, while bivariate analyses assess differences in screening types by month. Results: Completion of CRC screening yielded statistically significant differences for patients completing the different types of CRC screening by month. October-January had the highest proportions of patients (644-680 per month, 8.5%‐10.2%) receiving a colonoscopy, while February-April had the lowest (509-578 per month, 6.9%‐7.8%), with 614 being the average monthly number of colonoscopies. For FIT-FOBT, June-August had the higher proportions of patients receiving this test (563-613 per month, 8.9%‐9.6%), whereas December-February had the lowest (453-495 per month, 7.1%‐8%), with 541 being the average monthly number of FIT-FOBT kits used. For FIT-DNA, March was the most popular month with 11.3% (n=261 per month) of patients using the Cologuard test, followed by April, May, and November (207-220 per month, 8.7%‐9.4%), and January and June (168-171 per month, 7.2%-7.3%) had the lowest proportion of patients using Cologuard, with 193 being the average monthly number of FIT-DNA kits used. Combining all tests, February had the fewest CRC tests completed (1153/16,173, 7.1%). Conclusions: Home-based tests are becoming popular, replacing the gold standard colonoscopy, but need to be repeated more frequently. Monthly variation of screening over the course of a year suggests that CRC screening efforts and patient care may be less than ideal. Months with lower rates of screening for each type of CRC test represent opportunities for improving CRC screening. %R 10.2196/64809 %U https://cancer.jmir.org/2025/1/e64809 %U https://doi.org/10.2196/64809 %0 Journal Article %@ 2561-9128 %I JMIR Publications %V 8 %N %P e58998 %T Enhancing Quadruple Health Outcomes After Thoracic Surgery: Feasibility Pilot Randomized Controlled Trial Using Digital Home Monitoring %A Nagappa,Mahesh %A Subramani,Yamini %A Yang,Homer %A Wood,Natasha %A Querney,Jill %A Fochesato,Lee-Anne %A Nguyen,Derek %A Fatima,Nida %A Martin,Janet %A John-Baptiste,Ava %A Nayak,Rahul %A Qiabi,Mehdi %A Inculet,Richard %A Fortin,Dalilah %A Malthaner,Richard %+ Department of Anesthesia and Perioperative Medicine, London Health Sciences Centre and St. Joseph Health Care, Lawson Health Research Institute, Schulich School of Medicine and Dentistry, Western University, 339 Windermere Road, London, ON, N6A 5A5, Canada, 1 5196858500 ext 34436, Mahesh.Nagappa@lhsc.on.ca %K remote monitor %K digital home monitoring %K continuity of care %K quadruple health outcomes %K patient satisfaction %K caregivers satisfaction %K healthcare provider satisfaction %K feasibility %K RCT %K thoracic surgery %K postoperative monitoring %K surgical recovery %K perioperative medicine %K patient care %K questionnaire %D 2025 %7 12.2.2025 %9 Original Paper %J JMIR Perioper Med %G English %X Background: Surgical recovery after hospital discharge often presents challenges for patients and caregivers. Postoperative complications and poorly managed pain at home can lead to unexpected visits to the emergency department (ED) and readmission to the hospital. Digital home monitoring (DHM) may improve postoperative care compared to standard methods. Objective: We conducted a feasibility study for a randomized controlled trial (RCT) to assess DHM's effectiveness following thoracic surgical procedures compared to standard care. Methods: We conducted a 2-arm parallel-group pilot RCT at a single tertiary care center. Adult patients undergoing thoracic surgical procedures were randomized 1:1 into 2 groups: the DHM group and the standard of care (control group). We adhered to the intention-to-treat analysis principle. The primary outcome was predetermined RCT feasibility criteria. The trial would be feasible if more than 75% of trial recruitment, protocol adherence, and data collection were achieved. Secondary outcomes included 30-day ED visit rates, 30-day readmission rates, postoperative complications, length of stay, postdischarge 30-day opioid consumption, 30-day quality of recovery, patient-program satisfaction, caregiver satisfaction, health care provider satisfaction, and cost per case. Results: All RCT feasibility criteria were met. The trial recruitment rate was 87.9% (95% CI 79.4%-93.8%). Protocol adherence and outcome data collection rates were 96.3% (95% CI 89.4%-99.2%) and 98.7% (95% CI 92.9%-99.9%), respectively. In total, 80 patients were randomized, with 40 (50%) in the DHM group and 40 (50%) in the control group. Baseline patient and clinical characteristics were comparable between the 2 groups. The DHM group had fewer unplanned ED visits (2.7% vs 20.5%; P=.02), fewer unplanned admission rates (0% vs 7.6%; P=.24), lower rates of postoperative complications (20% vs 47.5%, P=.01) shorter hospital stays (4.0 vs 6.9 days; P=.05), but more opioid consumption (111.6, SD 110.9) vs 74.3, SD 71.9 mg morphine equivalents; P=.08) compared to the control group. DHM also resulted in shorter ED visit times (130, SD 0 vs 1048, SD 1093 minutes; P=.48) and lower cost per case (CAD $12,145 [US $ 8436.34], SD CAD $8779 [US $ 6098.20] vs CAD $17,247 [US $11,980.37], SD CAD $15,313 [US $10,636.95]; P=.07). The quality of recovery scores was clinically significantly better than the controls (185.4, SD 2.6 vs 178.3, SD 3.3; P<.001). All 37 patients who completed the intervention answered the program satisfaction survey questionnaires (100%; 95% CI 90.5%-100%). Only 36 out of 80 caregivers responded to the caregiver satisfaction questionnaires at the end of the fourth week post hospital discharge (47.7%; 95% CI 35.7%-59.1%). Health care providers reported a 100% satisfaction rate. Conclusions: This pilot RCT demonstrates the feasibility of conducting a full-scale trial to assess DHM's efficacy in improving postoperative care following thoracic surgery. DHM shows promise for enhancing continuity of care and warrants further investigation. Trial Registration: ClinicalTrials.gov NCT04340960; https://clinicaltrials.gov/study/NCT04340960 %M 39938882 %R 10.2196/58998 %U https://periop.jmir.org/2025/1/e58998 %U https://doi.org/10.2196/58998 %U http://www.ncbi.nlm.nih.gov/pubmed/39938882 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e62670 %T Electronic Health Record Data Collection Practices to Advance Standardization and Interoperability of Patient Preferences for Interpretation Services: Qualitative Study %A Heaney-Huls,Krysta %A Shams,Rida %A Nwefo,Ruth %A Kane,Rachel %A Gordon,Janna %A Laffan,Alison M %A Stare,Scott %A Dullabh,Prashila %+ , NORC at the University of Chicago, 55 E Monroe St 30th Floor, Chicago, IL, 60603, United States, 1 7734017110, heaney-huls-krysta@norc.org %K health information exchange %K interoperability %K electronic health records %K interpreter %K limited English proficiency %K communication barriers %D 2025 %7 31.1.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: Poor health outcomes are well documented among patients with a non-English language preference (NELP). The use of interpreters can improve the quality of care for patients with NELP. Despite a growing and unmet need for interpretation services in the US health care system, rates of interpreter use in the care setting are consistently low. Standardized collection and exchange of patient interpretation needs can improve access to appropriate language assistance services. Objective: This study aims to examine current practices for collecting, documenting, and exchanging information on a patient’s self-reported preference for an interpreter in the electronic health record (EHR) and the implementation maturity and adoption level of available data standards. The paper identifies standards implementation; data collection workflows; use cases for collecting, documenting, and exchanging information on a patient’s self-reported preference for an interpreter; challenges to data collection and use; and opportunities to advance standardization of the interpreter needed data element to facilitate patient-centered care. Methods: We conducted a narrative review to describe the availability of terminology standards to facilitate health care organization documentation of a patient’s self-reported preference for an interpreter in the EHR. Key informant discussions with EHR developers, health systems, clinicians, a practice-based research organization, a national standards collaborative, a professional health care association, and Federal agency representatives filled in gaps from the narrative review. Results: The findings indicate that health care organizations value standardized collection and exchange of patient language assistance service needs and preferences. Informants identified three use cases for collecting, documenting, and exchanging information on a patient’s self-reported preference for an interpreter, which are (1) person-centered care, (2) transitions of care, and (3) health care administration. The discussions revealed that EHR developers provide a data field for documenting interpreter needed data, which are routinely collected across health care organizations through commonly used data collection workflows. However, this data element is not mapped to standard terminologies, such as Logical Observation Identifiers Names and Codes (LOINC) or Systematized Medical Nomenclature for Medicine–Clinical Terminology (SNOMED-CT), consequently limiting the opportunities to electronically share these data between health systems and community-based organizations. The narrative review and key informant discussions identified three potential challenges to using information on a patient’s self-reported preference for an interpreter for person-centered care and quality improvement, which are (1) lack of adoption of available data standards, (2) limited electronic exchange, and (3) patient mistrust. Conclusions: Collecting and documenting patient’s self-reported interpreter preferences can improve the quality of services provided, patient care experiences, and equitable health care delivery without invoking a significant burden on the health care system. Although there is routine collection and documentation of patient interpretation needs, the lack of standardization limits the exchange of this information among health care and community-based organizations. %M 39888652 %R 10.2196/62670 %U https://www.jmir.org/2025/1/e62670 %U https://doi.org/10.2196/62670 %U http://www.ncbi.nlm.nih.gov/pubmed/39888652 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 12 %N %P e60825 %T The Research Agenda for Perinatal Innovation and Digital Health Project: Human-Centered Approach to Multipartner Research Agenda Codevelopment %A Amhaz,Haneen %A Chen,Sally Xuanping %A Elchehimi,Amanee %A Han,Kylin Jialin %A Gil,Jade Morales %A Yao,Lu %A Vidler,Marianne %A Berry-Einarson,Kathryn %A Dewar,Kathryn %A Tuason,May %A Prestley,Nicole %A Doan,Quynh %A van Rooij,Tibor %A Costa,Tina %A Ogilvie,Gina %A Payne,Beth A %+ Women's Health Research Institute, H214-4500 Oak Street, Box 42, Vancouver, BC, V6H3N1, Canada, 1 604 875 3459, bpayne@cw.bc.ca %K digital health %K co-design %K digital strategy %K human-centered design %K eHealth %K cocreation %K codevelopment %K perinatal intervention %K quality of care %K digital tools %K pregnancy %K patient autonomy %K patient support %K mobile phone %D 2025 %7 30.1.2025 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Digital health innovations provide an opportunity to improve access to care, information, and quality of care during the perinatal period, a critical period of health for mothers and infants. However, research to develop perinatal digital health solutions needs to be informed by actual patient and health system needs in order to optimize implementation, adoption, and sustainability. Objective: Our aim was to co-design a research agenda with defined research priorities that reflected health system realities and patient needs. Methods: Co-design of the research agenda involved a series of activities: (1) review of the provincial Digital Health Strategy and Maternity Services Strategy to identify relevant health system priorities, (2) anonymous survey targeting perinatal care providers to ascertain their current use and perceived need for digital tools, (3) engagement meetings using human-centered design methods with multilingual patients who are currently or recently pregnant to understand their health experiences and needs, and (4) a workshop that brought together patients and other project partners to prioritize identified challenges and opportunities for perinatal digital health in a set of research questions. These questions were grouped into themes using a deductive analysis approach starting with current BC Digital Health Strategy guiding principles. Results: Between September 15, 2022, and August 31, 2023, we engaged with more than 150 perinatal health care providers, researchers, and health system stakeholders and a patient advisory group of women who were recently pregnant to understand the perceived needs and priorities for digital innovation in perinatal care in British Columbia, Canada. As a combined group, partners were able to define 12 priority research questions in 3 themes. The themes prioritized are digital innovation for (1) patient autonomy and support, (2) standardized educational resources for patients and providers, and (3) improved access to health information. Conclusions: Our research agenda highlights the needs for perinatal digital health research to support improvements in the quality of care in British Columbia. By using a human-centered design approach, we were able to co-design research priorities that are meaningful to patients and health system stakeholders. The identified priority research questions are merely a stepping stone in the research process and now need to be actioned by research teams and health systems partners. %M 39883935 %R 10.2196/60825 %U https://humanfactors.jmir.org/2025/1/e60825 %U https://doi.org/10.2196/60825 %U http://www.ncbi.nlm.nih.gov/pubmed/39883935 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e46257 %T The Role of the Organization in Promoting Information Security–Related Behavior Among Resident Physicians in Hospitals in Germany: Cross-Sectional Questionnaire Study %A Kraushaar,Judith %A Bohnet-Joschko,Sabine %+ Chair of Healthcare Management and Innovation, Faculty of Management, Economics and Society, Witten/Herdecke University, Alfred-Herrhausen-Straße 50, Witten, 58455, Germany, 49 2302 926 47, judith.kraushaar@uni-wh.de %K information security %K compliance %K work engagement %K awareness %K leadership %K communication %K education and training %K security %K privacy %K structural equation modeling %K resident %K fellow %K medical education %K continuing education %K professional development %D 2025 %7 7.1.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: Nowadays, optimal patient care should be based on data-driven decisions. In the course of digitization, hospitals, in particular, are becoming complex organizations with an enormously high density of digital information. Ensuring information security is, therefore, essential and has become a major challenge. Researchers have shown that—in addition to technological and regulatory measures—it is also necessary for all employees to follow security policies and consciously use information technology (compliance), because noncompliance can lead to security breaches with far-reaching consequences for the organization. There is little empirical research on information security–related behavior in hospitals and its organizational antecedents. Objective: This study aimed to explore the impact of specific job demands and resources on resident physicians’ information security–related compliance in hospitals through the mediating role of work engagement and information security–related awareness. Methods: We used a cross-sectional, survey-based study design to collect relevant data from our target population, namely resident physicians in hospitals. For data analysis, we applied structural equation modeling. Our research model consisted of a total of 7 job demands and resources as exogenous variables, 2 mediators, and information security–related compliance as the endogenous variable. Results: Overall, data from 281 participating physicians were included in the analyses. Both mediators—work engagement and awareness—had a significant positive effect on information security–related compliance (β=.208, P=.001 vs β=.552, P<.001). Quality of leadership was found to be the only resource with a significant indirect effect on physicians’ compliance, mediated by work engagement (β=.086, P=.03). Furthermore, awareness mediated the relationships between information security–related communication and information security–related compliance (β=.192, P<.001), as well as between further education and training and the endogenous variable (β=.096, P=.02). Contrary to our hypothesis, IT resources had a negative effect on compliance, mediated by awareness (β=–.114, P=.02). Conclusions: This study provides new insights into how a high standard of information security compliance among resident physicians could be achieved through strengthening physicians’ security work engagement and awareness. Hospital management is required to establish an information security culture that is informative and motivating and that raises awareness. Particular attention should be paid to the quality of leadership, further education and training, as well as clear communication. %M 39773548 %R 10.2196/46257 %U https://www.jmir.org/2025/1/e46257 %U https://doi.org/10.2196/46257 %U http://www.ncbi.nlm.nih.gov/pubmed/39773548 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 9 %N %P e64936 %T Real-Time Analytics and AI for Managing No-Show Appointments in Primary Health Care in the United Arab Emirates: Before-and-After Study %A AlSerkal,Yousif Mohamed %A Ibrahim,Naseem Mohamed %A Alsereidi,Aisha Suhail %A Ibrahim,Mubaraka %A Kurakula,Sudheer %A Naqvi,Sadaf Ahsan %A Khan,Yasir %A Oottumadathil,Neema Preman %K electronic health record %K EHR %K artificial intelligence %K AI %K no-show appointments %K real-time data %K primary health care %K risk prediction %K clinic waiting time %K operational efficiency %D 2025 %7 6.1.2025 %9 %J JMIR Form Res %G English %X Background: Primary health care (PHC) services face operational challenges due to high patient volumes, leading to complex management needs. Patients access services through booked appointments and walk-in visits, with walk-in visits often facing longer waiting times. No-show appointments are significant contributors to inefficiency in PHC operations, which can lead to an estimated 3%-14% revenue loss, disrupt resource allocation, and negatively impact health care quality. Emirates Health Services (EHS) PHC centers handle over 140,000 visits monthly. Baseline data indicate a 21% no-show rate and an average patient wait time exceeding 16 minutes, necessitating an advanced scheduling and resource management system to enhance patient experiences and operational efficiency. Objective: The objective of this study was to evaluate the impact of an artificial intelligence (AI)-driven solution that was integrated with an interactive real-time data dashboard on reducing no-show appointments and improving patient waiting times at the EHS PHCs. Methods: This study introduced an innovative AI-based data application to enhance PHC efficiency. Leveraging our electronic health record system, we deployed an AI model with an 86% accuracy rate to predict no-shows by analyzing historical data and categorizing appointments based on no-show risk. The model was integrated with a real-time dashboard to monitor patient journeys and wait times. Clinic coordinators used the dashboard to proactively manage high-risk appointments and optimize resource allocation. The intervention was assessed through a before-and-after comparison of PHC appointment dynamics and wait times, analyzing data from 135,393 appointments (67,429 before implementation and 67,964 after implementation). Results: Implementation of the AI-powered no-show prediction model resulted in a significant 50.7% reduction in no-show rates (P<.001). The odds ratio for no-shows after implementation was 0.43 (95% CI 0.42-0.45; P<.001), indicating a 57% reduction in the likelihood of no-shows. Additionally, patient wait times decreased by an average of 5.7 minutes overall (P<.001), with some PHCs achieving up to a 50% reduction in wait times. Conclusions: This project demonstrates that integrating AI with a data analytics platform and an electronic health record systems can significantly improve operational efficiency and patient satisfaction in PHC settings. The AI model enabled daily assessments of wait times and allowed for real-time adjustments, such as reallocating patients to different clinicians, thus reducing wait times and optimizing resource use. These findings illustrate the transformative potential of AI and real-time data analytics in health care delivery. %R 10.2196/64936 %U https://formative.jmir.org/2025/1/e64936 %U https://doi.org/10.2196/64936 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e49844 %T The Virtual Client Experience Survey for Mental Health and Addictions: Revalidation of a Survey to Measure Client and Family Experiences of Virtual Care %A Crawford,Allison %A Kirvan,Anne %A Sanches,Marcos %A Gambin,Amanda %A Canso,Denise %A Serhal,Eva %+ Centre for Addiction and Mental Health, 60 White Squirrel Way, Office 223, Toronto, ON, M6J1H4, Canada, 1 416 535 8501, allison.crawford@utoronto.ca %K virtual care %K digital health %K mental health %K client satisfaction %K health care quality %K Virtual Client Experience Survey %K telehealth %K telemedicine %K eHealth %D 2025 %7 3.1.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: The onset of the COVID-19 pandemic precipitated a rapid shift to virtual care in health care settings, inclusive of mental health care. Understanding clients’ perspectives on virtual mental health care quality will be critical to informing future policies and practices. Objective: This study aimed to outline the process of redesigning and validating the Virtual Client Experience Survey (VCES), which can be used to evaluate client and family experiences of virtual care, specifically virtual mental health and addiction care. Methods: The VCES was adapted from a previously validated telepsychiatry survey. All items were reviewed and updated, with particular attention to the need to ensure relevance across mental health care sectors and settings. The survey was then revalidated using the 6 domains of health care quality of the Institute of Medicine (IOM) as a guiding framework. These 6 domains include being safe, effective, patient-centered, efficient, timely, and equitable. The VCES was piloted with a convenience sample of clients and family members accessing outpatient care at the Centre for Addiction and Mental Health (CAMH) in Toronto, Ontario, through video or telephone. A confirmatory factor analysis (CFA) was conducted in MPlus and used to test the factorial structures of the VCES, with minor respecification of the model based on modification indices, factor loadings, reliability, and item-total correlation. The respecifications were checked for alignment with the construct definitions and item interpretation. The reliability of the constructs was estimated by the Cronbach α coefficient. Results: The survey was completed 181 times. The construct reliability was generally high. Timely was the only subscale with an α lower than 0.7; all others were above 0.8. In all cases, the corrected item-total correlation was higher than 0.3. For the CFA, the model was adjusted after multiple imputations with 20 datasets. The mean chi-square value was 437.5, with df=199 (P<.001). The mean root mean square error of approximation (RMSEA) was 0.08 (SD 0.002), the mean confirmatory fit index (CFI) was 0.987 (SD 0.001), the mean Tucker-Lewis Index (TLI) was 0.985 (SD 0.001), and the mean standardized root mean square residual (SRMR) was 0.04 (SD 0.001). Conclusions: This study describes the validation of the VCES to evaluate client and family experiences of virtual mental health and addictions care. Given the widespread uptake of virtual care, this survey has broad applicability across settings that provide mental health and addiction care. The VCES can be used to guide targeted quality improvement initiatives across health care quality domains. By effectively addressing challenges as they emerge, it is anticipated that we will continue to move toward hybrid modalities of practice that leverage the strengths and benefits of telephone, video, and in-person care to effectively respond to unique client and family needs and circumstances. %M 39752192 %R 10.2196/49844 %U https://www.jmir.org/2025/1/e49844 %U https://doi.org/10.2196/49844 %U http://www.ncbi.nlm.nih.gov/pubmed/39752192 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e60017 %T Visualizing Patient Pathways and Identifying Data Repositories in a UK Neurosciences Center: Exploratory Study %A Knight,Jo %A Chandrabalan,Vishnu Vardhan %A Emsley,Hedley C A %K health data %K business process monitoring notation %K neurology %K process monitoring %K patient pathway %K clinical pathway %K patient care %K EHR %K electronic health record %K dataset %K questionnaire %K patient data %K NHS %K National Health Service %D 2024 %7 24.12.2024 %9 %J JMIR Med Inform %G English %X Background: Health and clinical activity data are a vital resource for research, improving patient care and service efficiency. Health care data are inherently complex, and their acquisition, storage, retrieval, and subsequent analysis require a thorough understanding of the clinical pathways underpinning such data. Better use of health care data could lead to improvements in patient care and service delivery. However, this depends on the identification of relevant datasets. Objective: We aimed to demonstrate the application of business process modeling notation (BPMN) to represent clinical pathways at a UK neurosciences center and map the clinical activity to corresponding data flows into electronic health records and other nonstandard data repositories. Methods: We used BPMN to map and visualize a patient journey and the subsequent movement and storage of patient data. After identifying several datasets that were being held outside of the standard applications, we collected information about these datasets using a questionnaire. Results: We identified 13 standard applications where neurology clinical activity was captured as part of the patient’s electronic health record including applications and databases for managing referrals, outpatient activity, laboratory data, imaging data, and clinic letters. We also identified 22 distinct datasets not within standard applications that were created and managed within the neurosciences department, either by individuals or teams. These were being used to deliver direct patient care and included datasets for tracking patient blood results, recording home visits, and tracking triage status. Conclusions: Mapping patient data flows and repositories allowed us to identify areas wherein the current electronic health record does not fulfill the needs of day-to-day patient care. Data that are being stored outside of standard applications represent a potential duplication in the effort and risks being overlooked. Future work should identify unmet data needs to inform correct data capture and centralization within appropriate data architectures. %R 10.2196/60017 %U https://medinform.jmir.org/2024/1/e60017 %U https://doi.org/10.2196/60017 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e63685 %T Improving Blood Pressure Control and Tobacco Use Cessation Intervention In Primary Care: Protocol for the Alabama Cardiovascular Cooperative Heart Health Improvement Project %A Foti,Kathryn %A Hubbard,Demetria %A Smith,Kimberly A %A Hearld,Larry %A Richman,Joshua %A Horton,Trudi %A Parker,Sharon %A Roughton,Dodey %A Craft,Macie %A Clarkson,Stephen A %A Jackson,Elizabeth A %A Cherrington,Andrea L %+ Department of Epidemiology, University of Alabama at Birmingham, 1655 University Blvd, 230-L, Birmingham, AL, 35294, United States, 1 2059347911, kfoti@uab.edu %K hypertension %K primary care %K quality improvement %K tobacco use %K smoking cessation %K healthcare quality %K quality of care %K risk modification %K cardiovascular disease prevention %D 2024 %7 20.12.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: Alabama has the second highest rate of cardiovascular disease (CVD) mortality of any US state and a high prevalence of CVD risk factors such as hypertension, diabetes, obesity, and smoking. Within the state, there are disparities in CVD outcomes and risk factors by race or ethnicity and geography. Many primary care practices do not have the capacity for full-scale quality improvement (QI) initiatives. The Alabama Cardiovascular Cooperative (ALCC), which includes academic and community stakeholders, was formed to support primary care practices to implement QI initiatives to improve cardiovascular health. The ALCC is implementing a Heart Health Improvement Project (HHIP) in primary care practices with suboptimal rates of blood pressure (BP) control and tobacco use screening. Objective: The study aimed to support primary care practices to increase BP control among adults with hypertension and increase rates of tobacco use screening and cessation intervention. Methods: We are using a type 1 hybrid design to test the effects of the HHIP on BP control among adults with hypertension and tobacco use screening and cessation intervention, while collecting information on implementation. Primary care practices were recruited through existing practice networks and additional electronic and in-person outreach. To ensure participation from a broad range of clinics, we required at least 50% of practices to be Federally Qualified Health Centers or look-alikes and to include representation from practices in rural areas. At baseline, we collected information about practice characteristics and preintervention rates of BP control and tobacco use screening and cessation intervention. The QI intervention includes quarterly activities conducted over a 12-month period. The HHIP uses a multipronged approach to QI, including practice facilitation and technical assistance, on-site and e-learning, and improvement through data transparency. We will conduct a pre-post analysis to estimate the effects of the HHIP and whether there is an enduring change in outcomes after the 12 months of HHIP activities beyond what would be expected due to secular trends. Results: Practice recruitment took place between April 2021 and October 2022. After contacting 417 primary care practices, 51 were enrolled, including 28 Federally Qualified Health Centers or look-alikes; 47 practices implemented the HHIP. Among 45 practices that completed the baseline survey, 11 (24%) were solo practices, while 28 (62%) had 1-5 clinicians, and 6 (13%) had 6 or more clinicians. The median number of patient visits per year was 5819 (IQR 3707.3-8630.5). Practices had been in operation for a mean of 19.2 (SD 13.0) years. At baseline, the mean BP control rate was 49.6% and the rate of tobacco use screening and cessation intervention was 67.4%. Conclusions: If successful, the ALCC and HHIP may improve the implementation of evidence-based guidelines in primary care and, subsequently, cardiovascular health and health equity in the state of Alabama. International Registered Report Identifier (IRRID): DERR1-10.2196/63685 %M 39706585 %R 10.2196/63685 %U https://www.researchprotocols.org/2024/1/e63685 %U https://doi.org/10.2196/63685 %U http://www.ncbi.nlm.nih.gov/pubmed/39706585 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e60244 %T Building a Foundation for High-Quality Health Data: Multihospital Case Study in Belgium %A Declerck,Jens %A Vandenberk,Bert %A Deschepper,Mieke %A Colpaert,Kirsten %A Cool,Lieselot %A Goemaere,Jens %A Bové,Mona %A Staelens,Frank %A De Meester,Koen %A Verbeke,Eva %A Smits,Elke %A De Decker,Cami %A Van Der Vekens,Nicky %A Pauwels,Elin %A Vander Stichele,Robert %A Kalra,Dipak %A Coorevits,Pascal %K EHR %K electronic health records %K health data %K data quality dimensions %K data quality assessment %K secondary use %K data quality framework %K fit for purpose %K Belgium %K data quality %K framework %K case study %K hospital %K variability %D 2024 %7 20.12.2024 %9 %J JMIR Med Inform %G English %X Background: Data quality is fundamental to maintaining the trust and reliability of health data for both primary and secondary purposes. However, before the secondary use of health data, it is essential to assess the quality at the source and to develop systematic methods for the assessment of important data quality dimensions. Objective: This case study aims to offer a dual aim—to assess the data quality of height and weight measurements across 7 Belgian hospitals, focusing on the dimensions of completeness and consistency, and to outline the obstacles these hospitals face in sharing and improving data quality standards. Methods: Focusing on data quality dimensions completeness and consistency, this study examined height and weight data collected from 2021 to 2022 within 3 distinct departments—surgical, geriatrics, and pediatrics—in each of the 7 hospitals. Results: Variability was observed in the completeness scores for height across hospitals and departments, especially within surgical and geriatric wards. In contrast, weight data uniformly achieved high completeness scores. Notably, the consistency of height and weight data recording was uniformly high across all departments. Conclusions: A collective collaboration among Belgian hospitals, transcending network affiliations, was formed to conduct this data quality assessment. This study demonstrates the potential for improving data quality across health care organizations by sharing knowledge and good practices, establishing a foundation for future, similar research. %R 10.2196/60244 %U https://medinform.jmir.org/2024/1/e60244 %U https://doi.org/10.2196/60244 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e51219 %T Information Source Characteristics of Personal Data Leakage During the COVID-19 Pandemic in China: Observational Study %A Wang,Zhong %A Hu,Fangru %A Su,Jie %A Lin,Yuyao %K public health emergency %K privacy leakage %K characteristics of information sources %K COVID-19 %K China %K information source %K data privacy %K public health %K leakage %D 2024 %7 10.12.2024 %9 %J JMIR Med Inform %G English %X Background: During the COVID-19 pandemic, in the period of preventing and controlling the spread of the virus, a large amount of personal data was collected in China, and privacy leakage incidents occurred. Objective: We aimed to examine the information source characteristics of personal data leakage during the COVID-19 pandemic in China. Methods: We extracted information source characteristics of 40 personal data leakage cases using open coding and analyzed the data with 1D and 2D matrices. Results: In terms of organizational characteristics, data leakage cases mainly occurred in government agencies below the prefecture level, while few occurred in the medical system or in high-level government organizations. The majority of leakers were regular employees or junior staff members rather than temporary workers or senior managers. Family WeChat groups were the primary route for disclosure; the forwarding of documents was the main method of divulgence, while taking screenshots and pictures made up a comparatively smaller portion. Conclusions: We propose the following suggestions: restricting the authority of nonmedical institutions and low-level government agencies to collect data, strengthening training for low-level employees on privacy protection, and restricting the flow of data on social media through technical measures. %R 10.2196/51219 %U https://medinform.jmir.org/2024/1/e51219 %U https://doi.org/10.2196/51219 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e59828 %T Development, Implementation, and Evaluation Methods for Dashboards in Health Care: Scoping Review %A Helminski,Danielle %A Sussman,Jeremy B %A Pfeiffer,Paul N %A Kokaly,Alex N %A Ranusch,Allison %A Renji,Anjana Deep %A Damschroder,Laura J %A Landis-Lewis,Zach %A Kurlander,Jacob E %K dashboard %K medical informatics %K quality improvement %K electronic health record %K scoping review %K monitoring %K health care system %K patient care %K clinical research %K emergency department %K inpatient %K clinical management %D 2024 %7 10.12.2024 %9 %J JMIR Med Inform %G English %X Background: Dashboards have become ubiquitous in health care settings, but to achieve their goals, they must be developed, implemented, and evaluated using methods that help ensure they meet the needs of end users and are suited to the barriers and facilitators of the local context. Objective: This scoping review aimed to explore published literature on health care dashboards to characterize the methods used to identify factors affecting uptake, strategies used to increase dashboard uptake, and evaluation methods, as well as dashboard characteristics and context. Methods: MEDLINE, Embase, Web of Science, and the Cochrane Library were searched from inception through July 2020. Studies were included if they described the development or evaluation of a health care dashboard with publication from 2018‐2020. Clinical setting, purpose (categorized as clinical, administrative, or both), end user, design characteristics, methods used to identify factors affecting uptake, strategies to increase uptake, and evaluation methods were extracted. Results: From 116 publications, we extracted data for 118 dashboards. Inpatient (45/118, 38.1%) and outpatient (42/118, 35.6%) settings were most common. Most dashboards had ≥2 stated purposes (84/118, 71.2%); of these, 54 of 118 (45.8%) were administrative, 43 of 118 (36.4%) were clinical, and 20 of 118 (16.9%) had both purposes. Most dashboards included frontline clinical staff as end users (97/118, 82.2%). To identify factors affecting dashboard uptake, half involved end users in the design process (59/118, 50%); fewer described formative usability testing (26/118, 22%) or use of any theory or framework to guide development, implementation, or evaluation (24/118, 20.3%). The most common strategies used to increase uptake included education (60/118, 50.8%); audit and feedback (59/118, 50%); and advisory boards (54/118, 45.8%). Evaluations of dashboards (84/118, 71.2%) were mostly quantitative (60/118, 50.8%), with fewer using only qualitative methods (6/118, 5.1%) or a combination of quantitative and qualitative methods (18/118, 15.2%). Conclusions: Most dashboards forego steps during development to ensure they suit the needs of end users and the clinical context; qualitative evaluation—which can provide insight into ways to improve dashboard effectiveness—is uncommon. Education and audit and feedback are frequently used to increase uptake. These findings illustrate the need for promulgation of best practices in dashboard development and will be useful to dashboard planners. International Registered Report Identifier (IRRID): RR2-10.2196/34894 %R 10.2196/59828 %U https://medinform.jmir.org/2024/1/e59828 %U https://doi.org/10.2196/59828 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e63834 %T Advancing Progressive Web Applications to Leverage Medical Imaging for Visualization of Digital Imaging and Communications in Medicine and Multiplanar Reconstruction: Software Development and Validation Study %A AboArab,Mohammed A. %A Potsika,Vassiliki T. %A Theodorou,Alexis %A Vagena,Sylvia %A Gravanis,Miltiadis %A Sigala,Fragiska %A Fotiadis,Dimitrios I. %+ Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, GR-45110, Ioannina, 45110, Greece, 30 2651005580, fotiadis@uoi.gr %K medical image visualization %K peripheral artery computed tomography imaging %K multiplanar reconstruction %K progressive web applications %D 2024 %7 9.12.2024 %9 Original Paper %J JMIR Med Inform %G English %X Background: In medical imaging, 3D visualization is vital for displaying volumetric organs, enhancing diagnosis and analysis. Multiplanar reconstruction (MPR) improves visual and diagnostic capabilities by transforming 2D images from computed tomography (CT) and magnetic resonance imaging into 3D representations. Web-based Digital Imaging and Communications in Medicine (DICOM) viewers integrated into picture archiving and communication systems facilitate access to pictures and interaction with remote data. However, the adoption of progressive web applications (PWAs) for web-based DICOM and MPR visualization remains limited. This paper addresses this gap by leveraging PWAs for their offline access and enhanced performance. Objective: This study aims to evaluate the integration of DICOM and MPR visualization into the web using PWAs, addressing challenges related to cross-platform compatibility, integration capabilities, and high-resolution image reconstruction for medical image visualization. Methods: Our paper introduces a PWA that uses a modular design for enhancing DICOM and MPR visualization in web-based medical imaging. By integrating React.js and Cornerstone.js, the application offers seamless DICOM image processing, ensures cross-browser compatibility, and delivers a responsive user experience across multiple devices. It uses advanced interpolation techniques to make volume reconstructions more accurate. This makes MPR analysis and visualization better in a web environment, thus promising a substantial advance in medical imaging analysis. Results: In our approach, the performance of DICOM- and MPR-based PWAs for medical image visualization and reconstruction was evaluated through comprehensive experiments. The application excelled in terms of loading time and volume reconstruction, particularly in Google Chrome, whereas Firefox showed superior performance in viewing slices. This study uses a dataset comprising 22 CT scans of peripheral artery patients to demonstrate the application’s robust performance, with Google Chrome outperforming other browsers in both the local area network and wide area network settings. In addition, the application’s accuracy in MPR reconstructions was validated with an error margin of <0.05 mm and outperformed the state-of-the-art methods by 84% to 98% in loading and volume rendering time. Conclusions: This paper highlights advancements in DICOM and MPR visualization using PWAs, addressing the gaps in web-based medical imaging. By exploiting PWA features such as offline access and improved performance, we have significantly advanced medical imaging technology, focusing on cross-platform compatibility, integration efficiency, and speed. Our application outperforms existing platforms for handling complex MPR analyses and accurate analysis of medical imaging as validated through peripheral artery CT imaging. %M 39652391 %R 10.2196/63834 %U https://medinform.jmir.org/2024/1/e63834 %U https://doi.org/10.2196/63834 %U http://www.ncbi.nlm.nih.gov/pubmed/39652391 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e57705 %T Design and Implementation of a Dashboard for Drug Interactions Mediated by Cytochromes Using a Health Care Data Warehouse in a University Hospital Center: Development Study %A Gosselin,Laura %A Maes,Alexandre %A Eyer,Kevin %A Dahamna,Badisse %A Disson,Flavien %A Darmoni,Stefan %A Wils,Julien %A Grosjean,Julien %K drug-drug interaction %K adverse %K interaction %K information system %K warehouse %K warehousing %K cytochrome %K personalized medicine %K dashboard %K drugs %K pharmacy %K pharmacology %K pharmacotherapy %K pharmaceutic %K pharmaceutical %K medication %K visualization %K develop %K development %K design %D 2024 %7 28.11.2024 %9 %J JMIR Med Inform %G English %X Background: The enzymatic system of cytochrome P450 (CYP450) is a group of enzymes involved in the metabolism of drugs present in the liver. Literature records instances of underdosing of drugs due to the concurrent administration of another drug that strongly induces the same cytochrome for which the first drug is a substrate and overdosing due to strong inhibition. IT solutions have been proposed to raise awareness among prescribers to mitigate these interactions. Objective: This study aimed to develop a drug interaction dashboard for Cytochrome-mediated drug interactions (DIDC) using a health care data warehouse to display results that are easily readable and interpretable by clinical experts. Methods: The initial step involved defining requirements with expert pharmacologists. An existing model of interactions involving the (CYP450) was used. A program for the automatic detection of cytochrome-mediated drug interactions (DI) was developed. Finally, the development and visualization of the DIDC were carried out by an IT engineer. An evaluation of the tool was carried out. Results: The development of the DIDC was successfully completed. It automatically compiled cytochrome-mediated DIs in a comprehensive table and provided a dedicated dashboard for each potential DI. The most frequent interaction involved paracetamol and carbamazepine with CYP450 3A4 (n=50 patients). The prescription of tacrolimus with CYP3A5 genotyping pertained to 675 patients. Two experts qualitatively evaluated the tool, resulting in overall satisfaction scores of 6 and 5 out of 7, respectively. Conclusions: At our hospital, measurements of molecules that could have altered concentrations due to cytochrome-mediated DIs are not systematic. These DIs can lead to serious clinical consequences. The purpose of this DIDC is to provide an overall view and raise awareness among prescribers about the importance of measuring concentrations of specific drugs and metabolites. Ultimately, the tool could lead to an individualized approach and become a prescription support tool if integrated into prescription assistance software. %R 10.2196/57705 %U https://medinform.jmir.org/2024/1/e57705 %U https://doi.org/10.2196/57705 %0 Journal Article %@ 2562-7600 %I JMIR Publications %V 7 %N %P e59619 %T Calculating Optimal Patient to Nursing Capacity: Comparative Analysis of Traditional and New Methods %A Ware,Anna %A Blumke,Terri %A Hoover,Peter %A Arreola,David %K nurse scheduling %K nurse %K patient ratio %K nursing hours per patient day %K NHPPD %K nursing administration %K workload %K comparative analysis %K nursing %K staffing %K nurse staffing %K registered nurses %K nurse assistants %K staff allocation %K patient capacity %D 2024 %7 22.11.2024 %9 %J JMIR Nursing %G English %X Background: Optimal nurse staffing levels have been shown to impact patients’ prognoses and safety, as well as staff burnout. The predominant method for calculating staffing levels has been patient-to-nurse (P/N) ratios and nursing hours per patient day. However, both methods fall short of addressing the dynamic nature of staffing needs that often fluctuate throughout the day as patients’ clinical status changes and new patients are admitted or discharged from the unit. Objective: In this evaluation, the Veterans Affairs Palo Alto Health Care System (VAPAHCS) piloted a new dynamic bed count calculation in an effort to target optimal staffing levels every hour to provide greater temporal resolution on nurse staffing levels within the Veterans Health Administration. Methods: The dynamic bed count uses elements from both the nursing hours per patient day and P/N ratio to calculate current and target staffing levels, every hour, while balancing across nurse types (registered nurses to nurse assistants) to provide improved temporal insight into staff allocation. The dynamic bed count was compared with traditional P/N ratio methods of calculating patient capacity at the VAPAHCS, to assess optimal patient capacity within their acute care ward from January 1, 2023, through May 25, 2023. Descriptive statistics summarized patient capacity variables across the intensive care unit (ICU), medical-surgical ICU, and 3 acute care units. Student t tests (2-tailed) were used to analyze differences between patient capacity measures. Results: Hourly analysis of patient capacity information displayed how the dynamic bed count provided improved temporal resolution on patient capacity. Comparing the dynamic bed count to the P/N ratio, we found the patient capacity, as determined by the P/N ratio, was, on average, higher than that of the dynamic bed count across VAPAHCS acute care units and the medical-surgical ICU (P<.001). For example, in acute care unit 3C, the average dynamic bed count was 21.6 (SD 4.2) compared with a P/N ratio of 28.6 (SD 3.2). This suggests that calculating patient capacity using P/N ratios alone could lead to units taking on more patients than what the dynamic bed count suggests the unit can optimally handle. Conclusions: As a new patient capacity calculation, the dynamic bed count provided additional details and timely information about clinical staffing levels, patient acuity, and patient turnover. Implementing this calculation into the management process has the potential to empower departments to further optimize staffing and patient care. %R 10.2196/59619 %U https://nursing.jmir.org/2024/1/e59619 %U https://doi.org/10.2196/59619 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e52675 %T Unintended Consequences of Data Sharing Under the Meaningful Use Program %A Willcockson,Irmgard Ursula %A Valdes,Ignacio Herman %K electronic health records %K EHR %K medical record %K interoperability %K health information interoperability %K clinical burden %K Medicare %K Medicaid %K reimbursement %K data science %K data governance %K data breach %K cybersecurity %K privacy %D 2024 %7 14.11.2024 %9 %J JMIR Med Inform %G English %X Interoperability has been designed to improve the quality and efficiency of health care. It allows the Centers for Medicare and Medicaid Services to collect data on quality measures as a part of the Meaningful Use program. Covered providers who fail to provide data have lower rates of reimbursement. Unintended consequences also arise at each step of the data collection process: (1) providers are not reimbursed for the extra time required to generate data; (2) patients do not have control over when and how their data are provided to or used by the government; and (3) large datasets increase the chances of an accidental data breach or intentional hacker attack. After detailing the issues, we describe several solutions, including an appropriate data use review board, which is designed to oversee certain aspects of the process and ensure accountability and transparency. %R 10.2196/52675 %U https://medinform.jmir.org/2024/1/e52675 %U https://doi.org/10.2196/52675 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 11 %N %P e55667 %T Clinical Acceptability of a Quality Improvement Program for Reducing Cardiovascular Disease Risk in People With Chronic Kidney Disease in Australian General Practice: Qualitative Study %A McBride,Caroline %A Hunter,Barbara %A Lumsden,Natalie %A Somasundaram,Kaleswari %A McMorrow,Rita %A Boyle,Douglas %A Emery,Jon %A Nelson,Craig %A Manski-Nankervis,Jo-Anne %K clinical decision support %K general practice %K GP %K primary care %K family medicine %K general medicine %K family physician %K implementation science %K chronic kidney disease %K CKD %K nephrology %K nephrologist %K chronic disease %K cardiovascular risk %K cardiology %K quality improvement %K EHR %K electronic health record %K clinical software %D 2024 %7 13.11.2024 %9 %J JMIR Hum Factors %G English %X Background: Future Health Today (FHT) is a technology program that integrates with general practice clinical software to provide point of care (PoC) clinical decision support and a quality improvement dashboard. This qualitative study looks at the use of FHT in the context of cardiovascular disease risk in chronic kidney disease (CKD). Objective: This study aims to explore factors influencing clinical implementation of the FHT module focusing on cardiovascular risk in CKD, from the perspectives of participating general practitioner staff. Methods: Practices in Victoria were recruited to participate in a pragmatic cluster randomized controlled trial using FHT, of which 19 practices were randomly assigned to use FHT’s cardiovascular risk in CKD program. A total of 13 semistructured interviews were undertaken with a nominated general practitioner (n=7) or practice nurse (n=6) from 10 participating practices. Interview questions focused on the clinical usefulness of the tool and its place in clinical workflows. Qualitative data were coded by 2 researchers and analyzed using framework analysis and Clinical Performance Feedback Intervention Theory. Results: All 13 interviewees had used the FHT PoC tool, and feedback was largely positive. Overall, clinicians described engaging with the tool as a “prompt” or “reminder” system. Themes reflected that the tool’s goals and clinical content were aligned with clinician’s existing priorities and knowledge, and the tool’s design facilitated easy integration into existing workflows. The main barrier to implementation identified by 2 clinicians was notification fatigue. A total of 7 interviewees had used the FHT dashboard tool. The main barriers to use were its limited integration into clinical workflows, such that some participants did not know of its existence; clinicians’ competing clinical priorities; and limited time to learn and use the tool. Conclusions: This study identified many facilitators for the successful use of the FHT PoC program, in the context of cardiovascular risk in CKD, and barriers to the use of the dashboard program. This work will be used to inform the wider implementation of FHT, as well as the development of future modules of FHT for other risk or disease states. Trial Registration: Australian New Zealand Clinical Trial Registry ACTRN12620000993998; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380119&is %R 10.2196/55667 %U https://humanfactors.jmir.org/2024/1/e55667 %U https://doi.org/10.2196/55667 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e51412 %T Influence of Blood Sampling Service Process Reengineering on Medical Services Supply: Quasi-Experimental Study %A Liao,Wenmin %A He,Rong %A He,Zhonglian %A Shi,Nan %A Li,Dan %A Zhuang,Aihua %A Gan,Feng %A Sun,Ying %A Li,Chaofeng %+ State Key Laboratory of Oncology, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Dongfengdong road 651#, Guangzhou, 510060, China, 86 87343292, lichaofeng@sysucc.org.cn %K process reengineering %K blood sampling %K hospital administration %K medical informatics %K digital health %K patient experience %D 2024 %7 12.11.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Tertiary hospitals in China are confronted with significant challenges due to limited spatial capacity and workforce constraints, leading to saturated allocation of medical resources and restricted growth in medical service provision. The incorporation of digital health into medical service process reengineering (MSPR) marks a pivotal transformation and restructuring of conventional health service delivery models. Specifically, the application of MSPR to blood sampling services processes reengineering (BSSPR) holds promise for substantially enhancing the efficiency and quality of medical services through streamlining and optimizing these procedures. However, the comprehensive impact of BSSPR has been infrequently quantified in existing research. Objective: This study aims to investigate the influence of BSSPR on the efficiency and quality of medical services and to elucidate the key informative technological support points underpinning BSSPR. Methods: Data were collected from both the new and old laboratory information systems from August 1, 2019, to December 31, 2021. A combination of statistical description, chi-square test, and t test was used to compare check-in time and waiting time of outpatients before and after the implementation of BSSPR. An interrupted time-series design was used to analyze the impact of BSSPR on medical service efficiency and quality, enabling the control of confounding variables, including changes in medical human resources and both long- and short-term temporal trends. Results: BSSPR had an impact on the efficiency and quality of medical services. Notably, there was a significant increase in the number of patients receiving blood sampling services, with a daily service volume increase of ~150 individuals (P=.04). The average waiting time for patients decreased substantially from 29 (SD 36) to 11 (SD 11) minutes, indicating a marked improvement in patient experience. During the peak period, the number of patients receiving blood sampling services per working hour statistically increased from 9.56 to 16.77 (P<.001). The interrupted time-series model results demonstrated a reduction in patients’ waiting time by an average of 26.1 (SD 3.8; 95% CI –33.64 to –18.57) minutes. Although there was an initial decline in the number of outpatients admitted following BSSPR implementation, an upward trend was observed over time (β=1.13, 95% CI 0.91-1.36). Conclusions: BSSPR implementation for outpatients not only reduced waiting time and improved patients’ experience but also augmented the hospital’s capacity to provide medical services. This study’s findings offer valuable insights into the potential advantages of BSSPR and underscore the significance of harnessing digital technologies to optimize medical service processes. This research serves as a foundational basis and provides scientific support for the promotion and application of BSSPR in other health care contexts. By continuing to explore and refine the integration of digital technologies in health care, we can further enhance patient outcomes and elevate the overall quality of medical services. %M 39531265 %R 10.2196/51412 %U https://www.jmir.org/2024/1/e51412 %U https://doi.org/10.2196/51412 %U http://www.ncbi.nlm.nih.gov/pubmed/39531265 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e54415 %T Enhancing Clinical History Taking Through the Implementation of a Streamlined Electronic Questionnaire System at a Pediatric Headache Clinic: Development and Evaluation Study %A Cho,Jaeso %A Han,Ji Yeon %A Cho,Anna %A Yoo,Sooyoung %A Lee,Ho-Young %A Kim,Hunmin %K electronic questionnaire system %K electronic questionnaire %K history taking %K medical history %K headache %K migraine %K neuralgia %K pediatric %K paediatric %K infant %K neonatal %K toddler %K child %K youth %K adolescent %D 2024 %7 8.11.2024 %9 %J JMIR Med Inform %G English %X Background: Accurate history taking is essential for diagnosis, treatment, and patient care, yet miscommunications and time constraints often lead to incomplete information. Consequently, there has been a pressing need to establish a system whereby the questionnaire is duly completed before the medical appointment, entered into the electronic health record (EHR), and stored in a structured format within a database. Objective: This study aimed to develop and evaluate a streamlined electronic questionnaire system, BEST-Survey (Bundang Hospital Electronic System for Total Care-Survey), integrated with the EHR, to enhance history taking and data management for patients with pediatric headaches. Methods: An electronic questionnaire system was developed at Seoul National University Bundang Hospital, allowing patients to complete previsit questionnaires on a tablet PC. The information is automatically integrated into the EHR and stored in a structured database for further analysis. A retrospective analysis compared clinical information acquired from patients aged <18 years visiting the pediatric neurology outpatient clinic for headaches, before and after implementing the BEST-Survey system. The study included 365 patients before and 452 patients after system implementation. Answer rates and positive rates of key headache characteristics were compared between the 2 groups to evaluate the system’s clinical utility. Results: Implementation of the BEST-Survey system significantly increased the mean data acquisition rate from 54.6% to 99.3% (P<.001). Essential clinical features such as onset, location, duration, severity, nature, and frequency were obtained in over 98.7% (>446/452) of patients after implementation, compared to from 53.7% (196/365) to 85.2% (311/365) before. The electronic system facilitated comprehensive data collection, enabling detailed analysis of headache characteristics in the patient population. Most patients (280/452, 61.9%) reported headache onset less than 1 year prior, with the temporal region being the most common pain location (261/703, 37.1%). Over half (232/452, 51.3%) experienced headaches lasting less than 2 hours, with nausea and vomiting as the most commonly associated symptoms (231/1036, 22.3%). Conclusions: The BEST-Survey system markedly improved the completeness and accuracy of essential history items for patients with pediatric headaches. The system also streamlined data extraction and analysis for clinical and research purposes. While the electronic questionnaire cannot replace physician-led history taking, it serves as a valuable adjunctive tool to enhance patient care. %R 10.2196/54415 %U https://medinform.jmir.org/2024/1/e54415 %U https://doi.org/10.2196/54415 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e55140 %T Service Quality and Patient Satisfaction of Internet Hospitals in China: Cross-Sectional Evaluation With the Service Quality Questionnaire %A Han,Tao %A Wei,Qinpeng %A Wang,Ruike %A Cai,Yijin %A Zhu,Hongyi %A Chen,Jiani %A Zhang,Zhiruo %A Li,Sisi %+ School of Public Health, Shanghai Jiao Tong University School of Medicine, 227 Chongqing South Road, Shanghai, 200025, China, 86 02163846590 ext 776145, lisi8318@gmail.com %K service quality %K SERVQUAL %K Service Quality Questionnaire %K internet hospital %K e-hospital %K digital medical care %K health care professionals %K Chinese digital health care %D 2024 %7 8.11.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Internet hospitals, which refer to service platforms that integrate consultation, prescription, payment, and drug delivery based on hospital entities, have been developing at a rapid pace in China since 2014. However, assessments regarding their service quality and patient satisfaction have not been well developed. There is an urgent need to comprehensively evaluate and improve the service quality of internet hospitals. Objective: This study aims to investigate the current status of patients’ use of internet hospitals, as well as familiarity and willingness to use internet hospitals, to evaluate patients’ expected and perceived service qualities of internet hospitals using the Chinese version of the Service Quality Questionnaire (SERVQUAL-C) with a national representative sample, and to explore the association between service quality of internet hospitals and patients’ overall satisfaction toward associated medical platforms. Methods: This cross-sectional survey was conducted through face-to-face or digital interviews from June to September 2022. A total of 1481 outpatient participants (635 men and 846 women; mean age 33.22, SD 13.22). Participants reported their use of internet hospitals, and then rated their expectations and perceptions of service quality toward internet hospitals via the SERVQUAL-C, along with their demographic information. Results: Among the surveyed participants, 51.2% (n=758) of participants had used internet hospital service or services. Use varied across age, education level, and annual income. Although the majority of them (n=826, 55.8%) did not know internet hospital services well, 68.1% (n=1009) of participants expressed the willingness to adopt this service. Service quality evaluation revealed that the perceived service quality did not match with the expectation, especially the responsiveness dimension. Important-performance analysis results further alerted that reliable diagnosis, prompt response, clear feedback pathway, and active feedback handling were typically the services awaiting substantial improvement. More importantly, multiple linear regressions revealed that familiarity and willingness to use internet hospital services were significant predictors of satisfaction, above and over tangibles, reliability, and empathy service perspectives, and demographic characteristics such as gender, age, education level, and annual income. Conclusions: In the future, internet hospitals should focus more on how to narrow the gaps between the expected and perceived service quality. Promotion of internet hospitals should also be facilitated to increase patients’ familiarity with and willingness to use these services. %M 39514849 %R 10.2196/55140 %U https://www.jmir.org/2024/1/e55140 %U https://doi.org/10.2196/55140 %U http://www.ncbi.nlm.nih.gov/pubmed/39514849 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e55502 %T A Combined Telemedicine and Ambulatory Wound Care Team Intervention for Improving Cross-Sector Outpatient Chronic Wound Management: Protocol for the Mixed Methods TELE-AMBUS Research Project %A Høyland,Sindre Aske %A Holte,Kari Anne %A Øygarden,Olaug %A Islam,Kamrul %A Kjerstad,Egil %A Gjerstad-Sørensen,Ragnhild %A Høyland,Synnøve Aske %A Wærnes,Hanne Rusten %A Carayon,Pascale %A Fallon,Maureen %A Bradbury,Sarah %A Gürgen,Marcus %A Husebø,Sissel Eikeland %A Rødseth,Eirin %+ Division for Health and Social Sciences, Norwegian Research Centre, Box 8046, Stavanger, N- 4068, Norway, 47 92230965, siho@norceresearch.no %K chronic wound management %K specialist health care sector %K primary health care sector %K ambulatory wound care team %K telemedicine %K process evaluation %K economic evaluation %K observations %K interviews %K whole system framework %D 2024 %7 4.11.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: There is a growing prevalence of nonhealing wounds and chronic diseases in society, and there is an associated need for wound management solutions that include the use of telemedicine. A broad spectrum of factors influences the planning and execution of interventions within telemedicine in chronic wound management, spanning organizations, technologies, and individuals, including professionals and patients. The Telemedicine and Ambulatory Wound Care Team (TELE-AMBUS) project applies a whole-system research approach to account for this spectrum of factors. Objective: The primary objective of this study was to explore and analyze the implementation and consequences of an outpatient wound management model, comprising 2 interconnected quality improvement interventions (ie, telemedicine and ambulatory wound care team) aimed at older and vulnerable patients with chronic wounds, across the specialist and primary health care sectors. Embedded in this objective is the aim to improve the competence levels of health care providers and, consequently, the service quality of outpatient wound management across specialist and primary health care services. Methods: This project examines the implementation and consequences of an outpatient wound management model through a combined process and economic evaluation research strategy. A sociotechnical system theory approach and multiple work package design support the examination. The project uses observations, conversations, interviews, and economic assessments to gather rich, in-depth insights and understanding on why and how the new wound management model contributes to a change or not compared with the traditional treatment model. Results: The project has been funded from 2021 to 2025. Baseline interviews have been conducted since April 2022 and concluded in January 2024. Fieldwork, including nonparticipant observations, semistructured interviews, and informal conversations, has been conducted since November 2022 and is expected to conclude in March 2025. In parallel and as part of the cost-effectiveness analyses, time usage data on the outpatient and regular clinical models are being gathered during the fieldwork. Conclusions: We applied a whole-system approach in multiple ways, that is, to design or inform our fieldwork and to explore, evaluate, and translate project findings into practice across services. To our knowledge, this approach has not been undertaken in telemedicine in chronic wound management literature and associated human factors and ergonomics research. Thus, our approach can produce both original and novel research and theoretical results internationally. International Registered Report Identifier (IRRID): DERR1-10.2196/55502 %M 39496308 %R 10.2196/55502 %U https://www.researchprotocols.org/2024/1/e55502 %U https://doi.org/10.2196/55502 %U http://www.ncbi.nlm.nih.gov/pubmed/39496308 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e58066 %T Electronic Health Interventions and Cervical Cancer Screening: Systematic Review and Meta-Analysis %A Liu,Xiaoxia %A Ning,Lianzhen %A Fan,Wenqi %A Jia,Chanyi %A Ge,Lina %+ Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Nanhu Campus, No36 Sanhao Street, Heping District, Shenyang, 110004, China, 86 18940251669, geln@sj-hospital.org %K cervical cancer %K electronic health record %K cancer screening %K HPV %K women's health %K electronic health interventions %D 2024 %7 31.10.2024 %9 Review %J J Med Internet Res %G English %X Background: Cervical cancer is a significant cause of mortality in women. Although screening has reduced cervical cancer mortality, screening rates remain suboptimal. Electronic health interventions emerge as promising strategies to effectively tackle this issue. Objective: This systematic review and meta-analysis aimed to determine the effectiveness of electronic health interventions in cervical cancer screening. Methods: On December 29, 2023, we performed an extensive search for randomized controlled trials evaluating electronic health interventions to promote cervical cancer screening in adults. The search covered multiple databases, including MEDLINE, the Cochrane Central Registry of Controlled Trials, Embase, PsycINFO, PubMed, Scopus, Web of Science, and the Cumulative Index to Nursing and Allied Health Literature. These studies examined the effectiveness of electronic health interventions on cervical cancer screening. Studies published between 2013 and 2022 were included. Two independent reviewers evaluated the titles, abstracts, and full-text publications, also assessing the risk of bias using the Cochrane Risk of Bias 2 tool. Subgroup analysis was conducted based on subjects, intervention type, and economic level. The Mantel-Haenszel method was used within a random-effects model to pool the relative risk of participation in cervical cancer screening. Results: A screening of 713 records identified 14 articles (15 studies) with 23,102 participants, which were included in the final analysis. The intervention strategies used in these studies included short messaging services (4/14), multimode interventions (4/14), phone calls (2/14), web videos (3/14), and internet-based booking (1/14). The results indicated that electronic health interventions were more effective than control interventions for improving cervical cancer screening rates (relative risk [RR] 1.464, 95% CI 1.285-1.667; P<.001; I2=84%), cervical cancer screening (intention-to-treat) (RR 1.382, 95% CI 1.214-1.574; P<.001; I2=82%), and cervical cancer screening (per-protocol; RR 1.565, 95% CI 1.381-1.772; P<.001; I2=74%). Subgroup analysis revealed that phone calls (RR 1.82, 95% CI 1.40-2.38), multimode (RR 1.62, 95% CI 1.26-2.08), SMS (RR 1.41, 95% CI 1.14-1.73), and video- and internet-based booking (RR 1.25, 95% CI 1.03-1.51) interventions were superior to usual care. In addition, electronic health interventions did not show a statistically significant improvement in cervical cancer screening rates among women with HPV (RR 1.17, 95% CI 0.95-1.45). Electronic health interventions had a greater impact on improving cervical cancer screening rates among women in low- and middle-income areas (RR 1.51, 95% CI 1.27-1.79). There were no indications of small study effects or publication bias. Conclusions: Electronic health interventions are recommended in cervical cancer screening programs due to their potential to increase participation rates. However, significant heterogeneity remained in this meta-analysis. Researchers should conduct large-scale studies focusing on the cost-effectiveness of these interventions. Trial Registration: CRD42024502884; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=502884 %M 39481096 %R 10.2196/58066 %U https://www.jmir.org/2024/1/e58066 %U https://doi.org/10.2196/58066 %U http://www.ncbi.nlm.nih.gov/pubmed/39481096 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e55148 %T Establishing Medical Intelligence—Leveraging Fast Healthcare Interoperability Resources to Improve Clinical Management: Retrospective Cohort and Clinical Implementation Study %A Brehmer,Alexander %A Sauer,Christopher Martin %A Salazar Rodríguez,Jayson %A Herrmann,Kelsey %A Kim,Moon %A Keyl,Julius %A Bahnsen,Fin Hendrik %A Frank,Benedikt %A Köhrmann,Martin %A Rassaf,Tienush %A Mahabadi,Amir-Abbas %A Hadaschik,Boris %A Darr,Christopher %A Herrmann,Ken %A Tan,Susanne %A Buer,Jan %A Brenner,Thorsten %A Reinhardt,Hans Christian %A Nensa,Felix %A Gertz,Michael %A Egger,Jan %A Kleesiek,Jens %+ Institute for Artificial Intelligence in Medicine, University Hospital Essen, Hufelandstr. 55, Essen, 45147, Germany, 49 0201723 ext 77801, jens.kleesiek@uk-essen.de %K clinical informatics %K FHIR %K real-world evidence %K medical intelligence %K interoperability %K data exchange %K clinical management %K clinical decision-making %K electronic health records %K quality of care %K quality improvement %D 2024 %7 31.10.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: FHIR (Fast Healthcare Interoperability Resources) has been proposed to enable health data interoperability. So far, its applicability has been demonstrated for selected research projects with limited data. Objective: This study aimed to design and implement a conceptual medical intelligence framework to leverage real-world care data for clinical decision-making. Methods: A Python package for the use of multimodal FHIR data (FHIRPACK [FHIR Python Analysis Conversion Kit]) was developed and pioneered in 5 real-world clinical use cases, that is, myocardial infarction, stroke, diabetes, sepsis, and prostate cancer. Patients were identified based on the ICD-10 (International Classification of Diseases, Tenth Revision) codes, and outcomes were derived from laboratory tests, prescriptions, procedures, and diagnostic reports. Results were provided as browser-based dashboards. Results: For 2022, a total of 1,302,988 patient encounters were analyzed. (1) Myocardial infarction: in 72.7% (261/359) of cases, medication regimens fulfilled guideline recommendations. (2) Stroke: out of 1277 patients, 165 received thrombolysis and 108 thrombectomy. (3) Diabetes: in 443,866 serum glucose and 16,180 glycated hemoglobin A1c measurements from 35,494 unique patients, the prevalence of dysglycemic findings was 39% (13,887/35,494). Among those with dysglycemia, diagnosis was coded in 44.2% (6138/13,887) of the patients. (4) Sepsis: In 1803 patients, Staphylococcus epidermidis was the primarily isolated pathogen (773/2672, 28.9%) and piperacillin and tazobactam was the primarily prescribed antibiotic (593/1593, 37.2%). (5) PC: out of 54, three patients who received radical prostatectomy were identified as cases with prostate-specific antigen persistence or biochemical recurrence. Conclusions: Leveraging FHIR data through large-scale analytics can enhance health care quality and improve patient outcomes across 5 clinical specialties. We identified (1) patients with sepsis requiring less broad antibiotic therapy, (2) patients with myocardial infarction who could benefit from statin and antiplatelet therapy, (3) patients who had a stroke with longer than recommended times to intervention, (4) patients with hyperglycemia who could benefit from specialist referral, and (5) patients with PC with early increases in cancer markers. %M 39240144 %R 10.2196/55148 %U https://www.jmir.org/2024/1/e55148 %U https://doi.org/10.2196/55148 %U http://www.ncbi.nlm.nih.gov/pubmed/39240144 %0 Journal Article %@ 2291-9279 %I JMIR Publications %V 12 %N %P e53825 %T Effects of Virtual Reality Therapy for Patients With Breast Cancer During Chemotherapy: Randomized Controlled Trial %A Li,Mengdan %A Yu,Zhifu %A Li,Hui %A Cao,Li %A Yu,Huihui %A Deng,Ning %A Liu,Yunyong %K virtual reality %K breast neoplasms %K quality of life %K psychological distress %K longitudinal studies %D 2024 %7 17.10.2024 %9 %J JMIR Serious Games %G English %X Background: Patients with breast cancer endure high levels of psychological and physical pain. Virtual reality (VR) may be an acceptable, safe intervention to alleviate the negative emotions and pain of patients with cancer. Objective: We aimed to test the long-term effects of VR on psychological distress and quality of life (QOL) with traditional care in Chinese patients with breast cancer. We also explored the intervention mechanism and the acceptability of VR. Methods: A total of 327 eligible participants were randomly assigned to a VR intervention group or a control group. The Distress Thermometer, QLQ-C30 (Quality of Life Questionnaire version 3.0), and Virtual Reality Symptom Questionnaire were assessed at baseline, postintervention (3 mo), and follow-up (6 mo). Analysis followed the intention-to-treat (ITT) principle. The generalized estimating equations model was used to analyze the longitudinal data, and the PROCESS macro was used to analyze the mediating effect. Results: Compared with the control group, patients with breast cancer in the VR group had lower distress scores (P=.007), and higher health-related QOL scores (physical, role, emotional, cognitive, and social functioning) after 6 months (P<.05). Psychological distress had mediating effects on the longitudinal association between VR and the health-related QOL (indirect effect=4.572‐6.672, all P<.05). Conclusions: VR intervention technology may help reduce distress and improve QOL for patients with breast cancer over time. By incorporating a mediating analysis, we showed that the QOL benefits of VR intervention was manifested through positive effects on psychological distress risk factors. Trial Registration: Chinese Clinical Trial Registry ChiCTR2000035049; https://www.chictr.org.cn/showproj.html?proj=53648 %R 10.2196/53825 %U https://games.jmir.org/2024/1/e53825 %U https://doi.org/10.2196/53825 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e54572 %T The Effects of Electronic Health Records on Medical Error Reduction: Extension of the DeLone and McLean Information System Success Model %A Chimbo,Bester %A Motsi,Lovemore %+ Department of Information Systems, University of South Africa, Cnr of Christiaan de Wet Road & Pioneer Avenue Florida, Johannesburg, 1709, South Africa, 27 82 333 8815, chimbb@unisa.ac.za %K medication error %K patient safety %K information system %K information systems %K electronic health record %K service quality %D 2024 %7 16.10.2024 %9 Original Paper %J JMIR Med Inform %G English %X Background: Medical errors are becoming a major problem for health care providers and those who design health policies. These errors cause patients’ illnesses to worsen over time and can make recovery impossible. For the benefit of patients and the welfare of health care providers, a decrease in these errors is required to maintain safe, high-quality patient care. Objective: This study aimed to improve the ability of health care professionals to diagnose diseases and reduce medical errors. Methods: Data collection was performed at Dr George Mukhari Academic Hospital using convenience sampling. In total, 300 health care professionals were given a self-administered questionnaire, including doctors, dentists, pharmacists, physiologists, and nurses. To test the study hypotheses, multiple linear regression was used to evaluate empirical data. Results: In the sample of 300 health care professionals, no significant correlation was found between medical error reduction (MER) and knowledge quality (KQ) (β=.043, P=.48). A nonsignificant negative relationship existed between MER and information quality (IQ) (β=–.080, P=.19). However, a significant positive relationship was observed between MER and electronic health records (EHR; β=.125, 95% CI 0.005-0.245, P=.042). Conclusions: Increasing patient access to medical records for health care professionals may significantly improve patient health and well-being. The effectiveness of health care organizations’ operations can also be increased through better health information systems. To lower medical errors and enhance patient outcomes, policy makers should provide financing and support for EHR adoption as a top priority. Health care administrators should also concentrate on providing staff with the training they need to operate these systems efficiently. Empirical surveys in other public and private hospitals can be used to further test the validated survey instrument. %M 39412857 %R 10.2196/54572 %U https://medinform.jmir.org/2024/1/e54572 %U https://doi.org/10.2196/54572 %U http://www.ncbi.nlm.nih.gov/pubmed/39412857 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e52722 %T Application of Information Link Control in Surgical Specimen Near-Miss Events in a South China Hospital: Nonrandomized Controlled Study %A Chen,Tingting %A Tang,Xiaofen %A Xu,Min %A Jiang,Yue %A Zheng,Fengyan %K near misses %K technical barriers %K process barriers %K surgical specimens %K information %D 2024 %7 14.10.2024 %9 %J JMIR Med Inform %G English %X Background: Information control is a promising approach for managing surgical specimens. However, there is limited research evidence on surgical near misses. This is particularly true in the closed loop of information control for each link. Objective: A new model of surgical specimen process management is further constructed, and a safe operating room nursing practice environment is created by intercepting specimen near-miss events through information safety barriers. Methods: In a large hospital in China, 84,289 surgical specimens collected in the conventional information specimen management mode from January to December 2021 were selected as the control group, and 99,998 surgical specimens collected in the information safety barrier control surgical specimen management mode from January to December 2022 were selected as the improvement group. The incidence of near misses, the qualified rate of pathological specimen fixation, and the average time required for specimen fixation were compared under the 2 management modes. The causes of 2 groups of near misses were analyzed and the near misses of information safety barrier control surgical specimens were studied. Results: Under the information-based safety barrier control surgical specimen management model, the incidence of adverse events in surgical specimens was reduced, the reporting of near-miss events in surgical specimens was improved by 100%, the quality control quality management of surgical specimens was effectively improved, the pass rate of surgical pathology specimen fixation was improved, and the meantime for surgical specimen fixation was shortened, with differences considered statistically significant at P<.05. Conclusions: Our research has developed a new mode of managing the surgical specimen process. This mode can prevent errors in approaching specimens by implementing information security barriers, thereby enhancing the quality of specimen management, ensuring the safety of medical procedures, and improving the quality of hospital services. %R 10.2196/52722 %U https://medinform.jmir.org/2024/1/e52722 %U https://doi.org/10.2196/52722 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e53828 %T Economic Burden of Community-Acquired Antibiotic-Resistant Urinary Tract Infections: Systematic Review and Meta-Analysis %A Zhu,Nina Jiayue %A Weldegiorgis,Misghina %A Carter,Emma %A Brown,Colin %A Holmes,Alison %A Aylin,Paul %K cost-effectiveness %K urinary tract infection %K antibiotic resistance %K mortality %K hospital length of stay %D 2024 %7 9.10.2024 %9 %J JMIR Public Health Surveill %G English %X Background: Antibiotic resistance (ABR) poses a major burden to global health and economic systems. ABR in community-acquired urinary tract infections (CA-UTIs) has become increasingly prevalent. Accurate estimates of ABR’s clinical and economic burden are needed to support medical resource prioritization and cost-effectiveness evaluations of urinary tract infection (UTI) interventions. Objective: This study aims to systematically synthesize the evidence on the economic costs associated with ABR in CA-UTIs, using published studies comparing the costs of antibiotic-susceptible and antibiotic-resistant cases. Methods: We searched the PubMed, Ovid MEDLINE and Embase, Cochrane Review Library, and Scopus databases. Studies published in English from January 1, 2008, to January 31, 2023, reporting the economic costs of ABR in CA-UTI of any microbe were included. Independent screening of titles/abstracts and full texts was performed based on prespecified criteria. A quality assessment was performed using the Integrated Quality Criteria for Review of Multiple Study Designs (ICROMS) tool. Data in UTI diagnosis criteria, patient characteristics, perspectives, resource costs, and patient and health economic outcomes, including mortality, hospital length of stay (LOS), and costs, were extracted and analyzed. Monetary costs were converted into 2023 US dollars. Results: This review included 15 studies with a total of 57,251 CA-UTI cases. All studies were from high- or upper-middle-income countries. A total of 14 (93%) studies took a health system perspective, 13 (87%) focused on hospitalized patients, and 14 (93%) reported UTI pathogens. Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa are the most prevalent organisms. A total of 12 (80%) studies reported mortality, of which, 7 reported increased mortality in the ABR group. Random effects meta-analyses estimated an odds ratio of 1.50 (95% CI 1.29-1.74) in the ABR CA-UTI cases. All 13 hospital-based studies reported LOS, of which, 11 reported significantly higher LOS in the ABR group. The meta-analysis of the reported median LOS estimated a pooled excess LOS ranging from 1.50 days (95% CI 0.71-4.00) to 2.00 days (95% CI 0.85-3.15). The meta-analysis of the reported mean LOS estimated a pooled excess LOS of 2.45 days (95% CI 0.51‐4.39). A total of 8 (53%) studies reported costs in monetary terms—none discounted the costs. All 8 studies reported higher medical costs spent treating patients with ABR CA-UTI in hospitals. The highest excess cost was observed in UTIs caused by carbapenem-resistant Enterobacterales. No meta-analysis was performed for monetary costs due to heterogeneity. Conclusions: ABR was attributed to increased mortality, hospital LOS, and economic costs among patients with CA-UTI. The findings of this review highlighted the scarcity of research in this area, particularly in patient morbidity and chronic sequelae and costs incurred in community health care. Future research calls for a cost-of-illness analysis of infections, standardizing therapy-pathogen combination comparators, medical resources, productivity loss, intangible costs to be captured, and data from community sectors and low-resource settings and countries. %R 10.2196/53828 %U https://publichealth.jmir.org/2024/1/e53828 %U https://doi.org/10.2196/53828 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e56263 %T Health Care Worker Usage of Large-Scale Health Information Exchanges in Japan: User-Level Audit Log Analysis Study %A Suzumoto,Jun %A Mori,Yukiko %A Kuroda,Tomohiro %K health information exchange %K audit log %K Japan %K HIE %K audit %K logs %K usage %K medical informatics %K rate %K hospitals %K electronic health record %D 2024 %7 9.10.2024 %9 %J JMIR Med Inform %G English %X Background: Over 200 health information exchanges (HIEs) are currently operational in Japan. The most common feature of HIEs is remote on-demand viewing or searching of aggregated patient health data from multiple institutions. However, the usage of this feature by individual users and institutions remains unknown. Objective: This study aims to understand usage of the on-demand patient data viewing feature of large-scale HIEs by individual health care workers and institutions in Japan. Methods: We conducted audit log analyses of large-scale HIEs. The research subjects were HIEs connected to over 100 institutions and with over 10,000 patients. Each health care worker’s profile and audit log data for HIEs were collected. We conducted four types of analyses on the extracted audit log. First, we calculated the ratio of the number of days of active HIE use for each hospital-affiliated doctor account. Second, we calculated cumulative monthly usage days of HIEs by each institution in financial year (FY) 2021/22. Third, we calculated each facility type’s monthly active institution ratio in FY2021/22. Fourth, we compared the monthly active institution ratio by medical institution for each HIE and the proportion of cumulative usage days by user type for each HIE. Results: We identified 24 HIEs as candidates for data collection and we analyzed data from 7 HIEs. Among hospital doctors, 93.5% (7326/7833) had never used HIEs during the available period in FY2021/22, while 19 doctors used them at least 30% of days. The median (IQR) monthly active institution ratios were 0.482 (0.470‐0.487) for hospitals, 0.243 (0.230‐0.247) for medical clinics, and 0.030 (0.024‐0.048) for dental clinics. In 51.9% (1781/3434) of hospitals, the cumulative monthly usage days of HIEs was 0, while in 26.8% (921/3434) of hospitals, it was between 1 and 10, and in 3% (103/3434) of hospitals, it was 100 or more. The median (IQR) monthly active institution ratio in medical institutions was 0.511 (0.487‐0.529) for the most used HIE and 0.109 (0.0927‐0.117) for the least used. The proportion of cumulative usage days of HIE by user type was complex for each HIE, and no consistent trends could be discerned. Conclusions: In the large-scale HIEs surveyed in this study, the overall usage of the on-demand patient data viewing feature was low, consistent with past official reports. User-level analyses of audit logs revealed large disparities in the number of days of HIE use among health care workers and institutions. There were also large disparities in HIE use by facility type or HIE; the percentage of cumulative HIE usage days by user type also differed by HIE. This study indicates the need for further research into why there are large disparities in demand for HIEs in Japan as well as the need to design comprehensive audit logs that can be matched with other official datasets. %R 10.2196/56263 %U https://medinform.jmir.org/2024/1/e56263 %U https://doi.org/10.2196/56263 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e55267 %T A Collection of Components to Design Clinical Dashboards Incorporating Patient-Reported Outcome Measures: Qualitative Study %A Bischof,Anja Yvonne %A Kuklinski,David %A Salvi,Irene %A Walker,Carla %A Vogel,Justus %A Geissler,Alexander %+ Chair of Health Economics, Policy and Management, School of Medicine, University of St. Gallen, St. Jakob-Strasse 21, St. Gallen, 9000, Switzerland, 41 712243220, anja.bischof@unisg.ch %K clinical dashboards %K design components %K patient-reported outcome measures (PROMs) %K patient-reported outcomes (PROs) %D 2024 %7 2.10.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: A clinical dashboard is a data-driven clinical decision support tool visualizing multiple key performance indicators in a single report while minimizing time and effort for data gathering. Studies have shown that including patient-reported outcome measures (PROMs) in clinical dashboards supports the clinician’s understanding of how treatments impact patients’ health status, helps identify changes in health-related quality of life at an early stage, and strengthens patient-physician communication. Objective: This study aims to determine design components for clinical dashboards incorporating PROMs to inform software producers and users (ie, physicians). Methods: We conducted interviews with software producers and users to test preselected design components. Furthermore, the interviews allowed us to derive additional components that are not outlined in existing literature. Finally, we used inductive and deductive coding to derive a guide on which design components need to be considered when building a clinical dashboard incorporating PROMs. Results: A total of 25 design components were identified, of which 16 were already surfaced during the literature search. Furthermore, 9 additional components were derived inductively during our interviews. The design components are clustered in a generic dashboard, PROM-related, adjacent information, and requirements for adoption components. Both software producers and users agreed on the primary purpose of a clinical dashboard incorporating PROMs to enhance patient communication in outpatient settings. Dashboard benefits include enhanced data visualization and improved workflow efficiency, while interoperability and data collection were named as adoption challenges. Consistency in dashboard design components is preferred across different episodes of care, with adaptations only for disease-specific PROMs. Conclusions: Clinical dashboards have the potential to facilitate informed treatment decisions if certain design components are followed. This study establishes a comprehensive framework of design components to guide the development of effective clinical dashboards incorporating PROMs in health care practice. %M 39357042 %R 10.2196/55267 %U https://www.jmir.org/2024/1/e55267 %U https://doi.org/10.2196/55267 %U http://www.ncbi.nlm.nih.gov/pubmed/39357042 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 11 %N %P e49691 %T Inefficient Processes and Associated Factors in Primary Care Nursing: System Configuration Analysis %A Tarver,Willi L %A Savoy,April %A Patel,Himalaya %A Weiner,Michael %A Holden,Richard J %+ School of Industrial Engineering, Purdue University, 799 W. Michigan St. ET 201, Indianapolis, IN, 46202, United States, 1 3172782194, asavoy@purdue.edu %K health information technology %K mobile devices %K nursing and nursing systems %K outpatient care %K SEIPS 2.0 %K work-system analysis %D 2024 %7 30.9.2024 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Industrywide, primary care nurses’ work is increasing in complexity and team orientation. Mobile health information technologies (HITs) designed to aid nurses with indirect care tasks, including charting, have had mixed success. Failed introductions of HIT may be explained by insufficient integration into nurses’ work processes, owing to an incomplete or incorrect understanding of the underlying work systems. Despite this need for context, published evidence has focused more on inpatient settings than on primary care. Objective: This study aims to characterize nurses’ and health technicians’ perceptions of process inefficiencies in the primary care setting and identify related work system factors. Methods: Guided by the Systems Engineering Initiative for Patient Safety (SEIPS) 2.0 model, we conducted an exploratory work system analysis with a convenience sample of primary care nurses and health technicians. Semistructured contextual interviews were conducted in 2 sets of primary care clinics in the Midwestern United States, one in an urban tertiary care center and the other in a rural community-based outpatient facility. Using directed qualitative content analysis of transcripts, we identified tasks participants perceived as frequent, redundant, or difficult, related processes, and recommendations for improvement. In addition, we conducted configuration analyses to identify associations between process inefficiencies and work system factors. Results: We interviewed a convenience sample of 20 primary care nurses and 2 health technicians, averaging approximately 12 years of experience in their current role. Across sites, participants perceived 2 processes, managing patient calls and clinic walk-in visits, as inefficient. Among work system factors, participants described organizational and technological factors associated with inefficiencies. For example, new organization policies to decrease patient waiting invoked frequent, repetitive, and difficult tasks, including chart review and check-in using tablet computers. Participants reported that issues with policy implementation and technology usability contributed to process inefficiencies. Organizational and technological factors were also perceived among participants as the most adaptable. Suggested technology changes included new tools for walk-in triage and patient self-reporting of symptoms. Conclusions: In response to changes to organizational policy and technology, without compensative changes elsewhere in their primary care work system, participants reported process adaptations. These adaptations indicate inefficient work processes. Understanding how the implementation of organizational policies affects other factors in the primary care work system may improve the quality of such implementations and, in turn, increase the effectiveness and efficiency of primary care nurse processes. Furthermore, the design and implementation of HIT interventions should consider influential work system factors and their effects on work processes. %M 39348682 %R 10.2196/49691 %U https://humanfactors.jmir.org/2024/1/e49691 %U https://doi.org/10.2196/49691 %U http://www.ncbi.nlm.nih.gov/pubmed/39348682 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e60293 %T Toward Better Semantic Interoperability of Data Element Repositories in Medicine: Analysis Study %A Hu,Zhengyong %A Wang,Anran %A Duan,Yifan %A Zhou,Jiayin %A Hu,Wanfei %A Wu,Sizhu %+ Institute of Medical Information/Medical Library, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 3 Yabao Road, Chaoyang District, Beijing, 100020, China, 86 52328760, Wu.sizhu@imicams.ac.cn %K data element repository %K FAIR %K ISO/IEC 11179 %K metadata %K semantic interoperability %D 2024 %7 30.9.2024 %9 Original Paper %J JMIR Med Inform %G English %X Background: Data element repositories facilitate high-quality medical data sharing by standardizing data and enhancing semantic interoperability. However, the application of repositories is confined to specific projects and institutions. Objective: This study aims to explore potential issues and promote broader application of data element repositories within the medical field by evaluating and analyzing typical repositories. Methods: Following the inclusion of 5 data element repositories through a literature review, a novel analysis framework consisting of 7 dimensions and 36 secondary indicators was constructed and used for evaluation and analysis. Results: The study’s results delineate the unique characteristics of different repositories and uncover specific issues in their construction. These issues include the absence of data reuse protocols and insufficient information regarding the application scenarios and efficacy of data elements. The repositories fully comply with only 45% (9/20) of the subprinciples for Findable and Reusable in the FAIR principle, while achieving a 90% (19/20 subprinciples) compliance rate for Accessible and 67% (10/15 subprinciples) for Interoperable. Conclusions: The recommendations proposed in this study address the issues to improve the construction and application of repositories, offering valuable insights to data managers, computer experts, and other pertinent stakeholders. %M 39348178 %R 10.2196/60293 %U https://medinform.jmir.org/2024/1/e60293 %U https://doi.org/10.2196/60293 %U http://www.ncbi.nlm.nih.gov/pubmed/39348178 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e55546 %T Evaluating the National Rollout of a Type 2 Diabetes Self-Management Intervention: Qualitative Interview Study With Local National Health Service Leads Responsible for Implementation %A Brunton,Lisa %A Cotterill,Sarah %A Wilson,Paul %+ Division of Population Health, Health Services Research & Primary Care, School of Health Sciences, University of Manchester, Suite 3, 6th Floor Williamson Building, Oxford Road, Manchester, M13 9PL, United Kingdom, 44 161 275 7603, lisa.brunton@manchester.ac.uk %K type 2 diabetes %K structured education %K self-management %K digital interventions %K implementation %K qualitative methods %K evaluation %D 2024 %7 25.9.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Approximately 4.5 million people live with type 2 diabetes mellitus (T2DM) in the United Kingdom. Evidence shows that structured education programs can improve glycemic control and reduce the risk of complications from T2DM, but they have low attendance rates. To widen access to T2DM structured education, National Health Service England commissioned a national rollout of Healthy Living, a digital self-management program. Objective: The objectives were to understand the barriers and enablers to adopting, implementing, and integrating Healthy Living into existing T2DM care pathways across England. Methods: We undertook a cross-sectional, qualitative telephone semistructured interview study to address the objectives. In total, 17 local National Health Service leads responsible for implementing Healthy Living across their locality were recruited. We conducted 16 one-time interviews across 16 case sites (1 of the interviews was conducted with 2 local leads from the same case site). Interview data were analyzed using thematic analysis. Results: Three overarching themes were generated: (1) implementation activities, (2) where Healthy Living fits within existing pathways, and (3) contextual factors affecting implementation. Of the 16 sites, 14 (88%) were implementing Healthy Living; the barrier to not implementing it in 2 case sites was not wanting Healthy Living to compete with their current education provision for T2DM. We identified 6 categories of implementation activities across sites: communication strategies to raise awareness of Healthy Living, developing bespoke local resources to support general practices with referrals, providing financial reimbursement or incentives to general practices, promoting Healthy Living via public events, monitoring implementation across their footprint, and widening access across high-need groups. However, outside early engagement sites, most implementation activities were “light touch,” consisting mainly of one-way communications to raise awareness. Local leads were generally positive about Healthy Living as an additional part of their T2DM structured education programs, but some felt it was more suited to specific patient groups. Barriers to undertaking more prolonged, targeted implementation campaigns included implementation not being mandated, sites not receiving data on uptake across their footprint, and confusion in understanding where Healthy Living fit within existing care pathways. Conclusions: A passive process of disseminating information about Healthy Living to general practices rather than an active process of implementation occurred across most sites sampled. This study identified that there is a need for clearer communications regarding the type of patients that may benefit from the Healthy Living program, including when it should be offered and whether it should be offered instead of or in addition to other education programs. No sites other than early engagement sites received data to monitor uptake across their footprint. Understanding variability in uptake across practices may have enabled sites to plan targeted referral campaigns in practices that were not using the service. %M 39321457 %R 10.2196/55546 %U https://www.jmir.org/2024/1/e55546 %U https://doi.org/10.2196/55546 %U http://www.ncbi.nlm.nih.gov/pubmed/39321457 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e58977 %T Automated System to Capture Patient Symptoms From Multitype Japanese Clinical Texts: Retrospective Study %A Nishiyama,Tomohiro %A Yamaguchi,Ayane %A Han,Peitao %A Pereira,Lis Weiji Kanashiro %A Otsuki,Yuka %A Andrade,Gabriel Herman Bernardim %A Kudo,Noriko %A Yada,Shuntaro %A Wakamiya,Shoko %A Aramaki,Eiji %A Takada,Masahiro %A Toi,Masakazu %+ Department of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, 630-0192, Japan, 81 743 72 5250, aramaki@is.naist.jp %K natural language processing %K named entity recognition %K adverse drug reaction %K adverse event %K peripheral neuropathy %K NLP %K symptoms %K symptom %K machine learning %K ML %K drug %K drugs %K pharmacology %K pharmacotherapy %K pharmaceutic %K pharmaceutics %K pharmaceuticals %K pharmaceutical %K medication %K medications %K adverse %K neuropathy %K cancer %K oncology %K text %K texts %K textual %K note %K notes %K report %K reports %K EHR %K EHRs %K record %K records %K detect %K detection %K detecting %D 2024 %7 24.9.2024 %9 Original Paper %J JMIR Med Inform %G English %X Background: Natural language processing (NLP) techniques can be used to analyze large amounts of electronic health record texts, which encompasses various types of patient information such as quality of life, effectiveness of treatments, and adverse drug event (ADE) signals. As different aspects of a patient’s status are stored in different types of documents, we propose an NLP system capable of processing 6 types of documents: physician progress notes, discharge summaries, radiology reports, radioisotope reports, nursing records, and pharmacist progress notes. Objective: This study aimed to investigate the system’s performance in detecting ADEs by evaluating the results from multitype texts. The main objective is to detect adverse events accurately using an NLP system. Methods: We used data written in Japanese from 2289 patients with breast cancer, including medication data, physician progress notes, discharge summaries, radiology reports, radioisotope reports, nursing records, and pharmacist progress notes. Our system performs 3 processes: named entity recognition, normalization of symptoms, and aggregation of multiple types of documents from multiple patients. Among all patients with breast cancer, 103 and 112 with peripheral neuropathy (PN) received paclitaxel or docetaxel, respectively. We evaluate the utility of using multiple types of documents by correlation coefficient and regression analysis to compare their performance with each single type of document. All evaluations of detection rates with our system are performed 30 days after drug administration. Results: Our system underestimates by 13.3 percentage points (74.0%−60.7%), as the incidence of paclitaxel-induced PN was 60.7%, compared with 74.0% in the previous research based on manual extraction. The Pearson correlation coefficient between the manual extraction and system results was 0.87 Although the pharmacist progress notes had the highest detection rate among each type of document, the rate did not match the performance using all documents. The estimated median duration of PN with paclitaxel was 92 days, whereas the previously reported median duration of PN with paclitaxel was 727 days. The number of events detected in each document was highest in the physician’s progress notes, followed by the pharmacist’s and nursing records. Conclusions: Considering the inherent cost that requires constant monitoring of the patient’s condition, such as the treatment of PN, our system has a significant advantage in that it can immediately estimate the treatment duration without fine-tuning a new NLP model. Leveraging multitype documents is better than using single-type documents to improve detection performance. Although the onset time estimation was relatively accurate, the duration might have been influenced by the length of the data follow-up period. The results suggest that our method using various types of data can detect more ADEs from clinical documents. %M 39316418 %R 10.2196/58977 %U https://medinform.jmir.org/2024/1/e58977 %U https://doi.org/10.2196/58977 %U http://www.ncbi.nlm.nih.gov/pubmed/39316418 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e53314 %T Creation of an Automated and Comprehensive Resident Progress System for Residents and to Save Hours of Faculty Time: Mixed Methods Study %A Perotte,Rimma %A Berns,Alyssa %A Shaker,Lana %A Ophaswongse,Chayapol %A Underwood,Joseph %A Hajicharalambous,Christina %+ Hackensack University Medical Center, 30 Prospect Ave, Hackensack, NJ, 07601, United States, 1 5519962470, rimma.perotte@hmhn.org %K progress dashboard %K informatics in medical education %K residency learning management system %K residency progress system %K residency education system %K summarization %K administrative burden %K medical education %K resident %K residency %K resident data %K longitudinal %K pilot study %K competency %K dashboards %K dashboard %K faculty %K residents %D 2024 %7 23.9.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: It is vital for residents to have a longitudinal view of their educational progression, and it is crucial for the medical education team to have a clear way to track resident progress over time. Current tools for aggregating resident data are difficult to use and do not provide a comprehensive way to evaluate and display resident educational advancement. Objective: This study aims to describe the creation and assessment of a system designed to improve the longitudinal presentation, quality, and synthesis of educational progress for trainees. We created a new system for residency progress management with 3 goals in mind, that are (1) a long-term and centralized location for residency education data, (2) a clear and intuitive interface that is easy to access for both the residents and faculty involved in medical education, and (3) automated data input, transformation, and analysis. We present evaluations regarding whether residents find the system useful, and whether faculty like the system and perceive that it helps them save time with administrative duties. Methods: The system was created using a suite of Google Workspace tools including Forms, Sheets, Gmail, and a collection of Apps Scripts triggered at various times and events. To assess whether the system had an effect on the residents, we surveyed and asked them to self-report on how often they accessed the system and interviewed them as to whether they found it useful. To understand what the faculty thought of the system, we conducted a 14-person focus group and asked the faculty to self-report their time spent preparing for residency progress meetings before and after the system debut. Results: The system went live in February 2022 as a quality improvement project, evolving through multiple iterations of feedback. The authors found that the system was accessed differently by different postgraduate years (PGY), with the most usage reported in the PGY1 class (weekly), and the least amount of usage in the PGY3 class (once or twice). However, all of the residents reported finding the system useful, specifically for aggregating all of their evaluations in the same place. Faculty members felt that the system enabled a more high-quality biannual clinical competency committee meeting and they reported a combined time savings of 8 hours in preparation for each clinical competency committee as a result of reviewing resident data through the system. Conclusions: Our study reports on the creation of an automated, instantaneous, and comprehensive resident progress management system. The system has been shown to be well-liked by both residents and faculty. Younger PGY classes reported more frequent system usage than older PGY classes. Faculty reported that it helped facilitate more meaningful discussion of training progression and reduced the administrative burden by 8 hours per biannual session. %M 39312292 %R 10.2196/53314 %U https://formative.jmir.org/2024/1/e53314 %U https://doi.org/10.2196/53314 %U http://www.ncbi.nlm.nih.gov/pubmed/39312292 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e57406 %T How Patient-Generated Data Enhance Patient-Provider Communication in Chronic Care: Field Study in Design Science Research %A Staehelin,Dario %A Dolata,Mateusz %A Stöckli,Livia %A Schwabe,Gerhard %+ Department of Informatics, University of Zurich, Binzmühlestrasse 14, Zurich, 8050, Switzerland, 41 763103137, dario.staehelin@ost.ch %K patient-provider communication %K patient-generated data %K field study %K chronic care %K design science research %K patient-centered care %K integrated care %K patient-provider collaboration %K mobile phone %D 2024 %7 10.9.2024 %9 Original Paper %J JMIR Med Inform %G English %X Background: Modern approaches such as patient-centered care ask health care providers (eg, nurses, physicians, and dietitians) to activate and include patients to participate in their health care. Mobile health (mHealth) is integral in this endeavor to be more patient centric. However, structural and regulatory barriers have hindered its adoption. Existing mHealth apps often fail to activate and engage patients sufficiently. Moreover, such systems seldom integrate well with health care providers’ workflow. Objective: This study investigated how patient-provider communication behaviors change when introducing patient-generated data into patient-provider communication. Methods: We adopted the design science approach to design PatientHub, an integrated digital health system that engages patients and providers in patient-centered care for weight management. PatientHub was developed in 4 iterations and was evaluated in a 3-week field study with 27 patients and 6 physicians. We analyzed 54 video recordings of PatientHub-supported consultations and interviews with patients and physicians. Results: PatientHub introduces patient-generated data into patient-provider communication. We observed 3 emerging behaviors when introducing patient-generated data into consultations. We named these behaviors emotion labeling, expectation decelerating, and decision ping-pong. Our findings show how these behaviors enhance patient-provider communication and facilitate patient-centered care. Introducing patient-generated data leads to behaviors that make consultations more personal, actionable, trustworthy, and equal. Conclusions: The results of this study indicate that patient-generated data facilitate patient-centered care by activating and engaging patients and providers. We propose 3 design principles for patient-centered communication. Patient-centered communication informs the design of future mHealth systems and offers insights into the inner workings of mHealth-supported patient-provider communication in chronic care. %M 39255481 %R 10.2196/57406 %U https://medinform.jmir.org/2024/1/e57406 %U https://doi.org/10.2196/57406 %U http://www.ncbi.nlm.nih.gov/pubmed/39255481 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e60860 %T Quality Indicators for Transition from Pediatric to Adult Care for Youth With Chronic Conditions: Proposal for an Online Modified Delphi Study %A Toulany,Alene %A Khodyakov,Dmitry %A Mooney,Sarah %A Stromquist,Lisa %A Bailey,Katherine %A Barber,Claire EH %A Batthish,Michelle %A Cleverley,Kristin %A Dimitropoulos,Gina %A Gorter,Jan Willem %A Grahovac,Danijela %A Grimes,Ruth %A Guttman,Beverly %A Hébert,Michèle L %A John,Tomisin %A Lo,Lisha %A Luong,Dorothy %A MacGregor,Laura %A Mukerji,Geetha %A Pidduck,Jacklynn %A Senthilnathan,Vjura %A Shulman,Rayzel %A Trbovich,Patricia %A Munce,Sarah EP %+ Department of Adolescent Medicine, The Hospital for Sick Children, 170 Elizabeth St, Toronto, ON, M5G 1E8, Canada, 1 416 813 7654 ext 428939, alene.toulany@sickkids.ca %K transition to adult care %K adolescent health %K chronic conditions %K quality indicators %K consensus %K caregivers %K adolescent %K stakeholder engagement %K patient engagement %K Delphi %D 2024 %7 10.9.2024 %9 Proposal %J JMIR Res Protoc %G English %X Background: The transition from pediatric to adult care poses a significant health system–level challenge impeding the delivery of quality health services for youth with chronic health conditions. In Canada and globally, the transition to adult care is regarded as a top priority in adolescent health in need of readily applicable, adaptable, and relevant national metrics to evaluate and benchmark transition success across disease populations and clinical care settings. Unfortunately, existing literature fails to account for the lack of engagement from youth and caregivers in developing indicators, and its applicability across chronic conditions, primary care involvement, and health equity considerations. Objective: Our proposed study aims to establish a consensus-driven set of quality indicators for the transition to adult care that are universally applicable across physical, developmental, and mental health conditions, clinical care settings, and health jurisdictions. Methods: Using an integrated knowledge translation (iKT) approach, a panel comprising youth, caregivers, interdisciplinary health care providers, and health system leaders will be established to collaborate with our research team to ensure that the study methodology, materials, and knowledge dissemination are suitable and reflect the perspectives of youth and their families. We will then conduct an iterative 3-round Online Modified Delphi (OMD) study (n=160) to (1) compare and contrast the perspectives of youth, caregivers, health care providers, and health system leaders on quality indicators for transition; and (2) prioritize a key set of quality indicators for transition applicable across disease populations that are the most important, useful, and feasible in the Canadian context. Using the RAND/UCLA Appropriateness Method (RAM) multistage analytic approach, data from each panel and stakeholder group will be examined separately and compared to establish a key set of indicators endorsed by both panels. Results: The study is funded by the Canadian Institutes of Health Research and Physicians Services Incorporated. Conclusions: This study will produce quality indicators to evaluate and inform action equitably to improve transition from pediatric to adult care for youth and their families in Canada. International Registered Report Identifier (IRRID): PRR1-10.2196/60860 %M 38889353 %R 10.2196/60860 %U https://www.researchprotocols.org/2024/1/e60860 %U https://doi.org/10.2196/60860 %U http://www.ncbi.nlm.nih.gov/pubmed/38889353 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e58347 %T Alarm Management in Provisional COVID-19 Intensive Care Units: Retrospective Analysis and Recommendations for Future Pandemics %A Wunderlich,Maximilian Markus %A Frey,Nicolas %A Amende-Wolf,Sandro %A Hinrichs,Carl %A Balzer,Felix %A Poncette,Akira-Sebastian %+ Institute of Medical Informatics, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Invalidenstraße 90, Berlin, 10115 Berlin, Germany, 49 030 450 581 018, akira-sebastian.poncette@charite.de %K patient monitoring %K intensive care unit %K ICU %K alarm fatigue %K alarm management %K patient safety %K alarm system %K alarm system quality %K medical devices %K clinical alarms %K COVID-19 %D 2024 %7 9.9.2024 %9 Original Paper %J JMIR Med Inform %G English %X Background: In response to the high patient admission rates during the COVID-19 pandemic, provisional intensive care units (ICUs) were set up, equipped with temporary monitoring and alarm systems. We sought to find out whether the provisional ICU setting led to a higher alarm burden and more staff with alarm fatigue. Objective: We aimed to compare alarm situations between provisional COVID-19 ICUs and non–COVID-19 ICUs during the second COVID-19 wave in Berlin, Germany. The study focused on measuring alarms per bed per day, identifying medical devices with higher alarm frequencies in COVID-19 settings, evaluating the median duration of alarms in both types of ICUs, and assessing the level of alarm fatigue experienced by health care staff. Methods: Our approach involved a comparative analysis of alarm data from 2 provisional COVID-19 ICUs and 2 standard non–COVID-19 ICUs. Through interviews with medical experts, we formulated hypotheses about potential differences in alarm load, alarm duration, alarm types, and staff alarm fatigue between the 2 ICU types. We analyzed alarm log data from the patient monitoring systems of all 4 ICUs to inferentially assess the differences. In addition, we assessed staff alarm fatigue with a questionnaire, aiming to comprehensively understand the impact of the alarm situation on health care personnel. Results: COVID-19 ICUs had significantly more alarms per bed per day than non–COVID-19 ICUs (P<.001), and the majority of the staff lacked experience with the alarm system. The overall median alarm duration was similar in both ICU types. We found no COVID-19–specific alarm patterns. The alarm fatigue questionnaire results suggest that staff in both types of ICUs experienced alarm fatigue. However, physicians and nurses who were working in COVID-19 ICUs reported a significantly higher level of alarm fatigue (P=.04). Conclusions: Staff in COVID-19 ICUs were exposed to a higher alarm load, and the majority lacked experience with alarm management and the alarm system. We recommend training and educating ICU staff in alarm management, emphasizing the importance of alarm management training as part of the preparations for future pandemics. However, the limitations of our study design and the specific pandemic conditions warrant further studies to confirm these findings and to explore effective alarm management strategies in different ICU settings. %M 39250783 %R 10.2196/58347 %U https://medinform.jmir.org/2024/1/e58347 %U https://doi.org/10.2196/58347 %U http://www.ncbi.nlm.nih.gov/pubmed/39250783 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e58456 %T Impact of an Electronic Health Record–Based Interruptive Alert Among Patients With Headaches Seen in Primary Care: Cluster Randomized Controlled Trial %A Pradhan,Apoorva %A Wright,Eric A %A Hayduk,Vanessa A %A Berhane,Juliana %A Sponenberg,Mallory %A Webster,Leeann %A Anderson,Hannah %A Park,Siyeon %A Graham,Jove %A Friedenberg,Scott %K headache management %K migraine management %K electronic health record–based alerts %K primary care %K clinician decision support tools %K electronic health record %K EHR %D 2024 %7 29.8.2024 %9 %J JMIR Med Inform %G English %X Background: Headaches, including migraines, are one of the most common causes of disability and account for nearly 20%‐30% of referrals from primary care to neurology. In primary care, electronic health record–based alerts offer a mechanism to influence health care provider behaviors, manage neurology referrals, and optimize headache care. Objective: This project aimed to evaluate the impact of an electronic alert implemented in primary care on patients’ overall headache management. Methods: We conducted a stratified cluster-randomized study across 38 primary care clinic sites between December 2021 to December 2022 at a large integrated health care delivery system in the United States. Clinics were stratified into 6 blocks based on region and patient-to–health care provider ratios and then 1:1 randomized within each block into either the control or intervention. Health care providers practicing at intervention clinics received an interruptive alert in the electronic health record. The primary end point was a change in headache burden, measured using the Headache Impact Test 6 scale, from baseline to 6 months. Secondary outcomes included changes in headache frequency and intensity, access to care, and resource use. We analyzed the difference-in-differences between the arms at follow-up at the individual patient level. Results: We enrolled 203 adult patients with a confirmed headache diagnosis. At baseline, the average Headache Impact Test 6 scores in each arm were not significantly different (intervention: mean 63, SD 6.9; control: mean 61.8, SD 6.6; P=.21). We observed a significant reduction in the headache burden only in the intervention arm at follow-up (3.5 points; P=.009). The reduction in the headache burden was not statistically different between groups (difference-in-differences estimate –1.89, 95% CI –5 to 1.31; P=.25). Similarly, secondary outcomes were not significantly different between groups. Only 11.32% (303/2677) of alerts were acted upon. Conclusions: The use of an interruptive electronic alert did not significantly improve headache outcomes. Low use of alerts by health care providers prompts future alterations of the alert and exploration of alternative approaches. Trial Registration: ClinicalTrials.gov NCT05067725; https://clinicaltrials.gov/study/NCT05067725 %R 10.2196/58456 %U https://medinform.jmir.org/2024/1/e58456 %U https://doi.org/10.2196/58456 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e55717 %T Impacts of Clinical Decision Support Systems on the Relationship, Communication, and Shared Decision-Making Between Health Care Professionals and Patients: Multistakeholder Interview Study %A Funer,Florian %A Schneider,Diana %A Heyen,Nils B %A Aichinger,Heike %A Klausen,Andrea Diana %A Tinnemeyer,Sara %A Liedtke,Wenke %A Salloch,Sabine %A Bratan,Tanja %+ Competence Center Emerging Technologies, Fraunhofer Institute for Systems and Innovation Research ISI, Breslauer Straße 48, Karlsruhe, 76139, Germany, 49 0721 6809 58, diana.schneider@isi.fraunhofer.de %K clinical decision support system %K CDSS %K health care professionals %K patients %K relationships %K communication %K shared decision-making %K Germany %D 2024 %7 23.8.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Clinical decision support systems (CDSSs) are increasingly being introduced into various domains of health care. Little is known so far about the impact of such systems on the health care professional–patient relationship, and there is a lack of agreement about whether and how patients should be informed about the use of CDSSs. Objective: This study aims to explore, in an empirically informed manner, the potential implications for the health care professional–patient relationship and to underline the importance of this relationship when using CDSSs for both patients and future professionals. Methods: Using a methodological triangulation, 15 medical students and 12 trainee nurses were interviewed in semistructured interviews and 18 patients were involved in focus groups between April 2021 and April 2022. All participants came from Germany. Three examples of CDSSs covering different areas of health care (ie, surgery, nephrology, and intensive home care) were used as stimuli in the study to identify similarities and differences regarding the use of CDSSs in different fields of application. The interview and focus group transcripts were analyzed using a structured qualitative content analysis. Results: From the interviews and focus groups analyzed, three topics were identified that interdependently address the interactions between patients and health care professionals: (1) CDSSs and their impact on the roles of and requirements for health care professionals, (2) CDSSs and their impact on the relationship between health care professionals and patients (including communication requirements for shared decision-making), and (3) stakeholders’ expectations for patient education and information about CDSSs and their use. Conclusions: The results indicate that using CDSSs could restructure established power and decision-making relationships between (future) health care professionals and patients. In addition, respondents expected that the use of CDSSs would involve more communication, so they anticipated an increased time commitment. The results shed new light on the existing discourse by demonstrating that the anticipated impact of CDSSs on the health care professional–patient relationship appears to stem less from the function of a CDSS and more from its integration in the relationship. Therefore, the anticipated effects on the relationship between health care professionals and patients could be specifically addressed in patient information about the use of CDSSs. %M 39178023 %R 10.2196/55717 %U https://www.jmir.org/2024/1/e55717 %U https://doi.org/10.2196/55717 %U http://www.ncbi.nlm.nih.gov/pubmed/39178023 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e57615 %T Data Quality–Driven Improvement in Health Care: Systematic Literature Review %A Lighterness,Anthony %A Adcock,Michael %A Scanlon,Lauren Abigail %A Price,Gareth %+ Clinical Outcomes and Data Unit, The Christie NHS Foundation Trust, 550 Wilmslow Road, Manchester, M20 4BX, United Kingdom, 44 7305054646, anthony.lighterness@nhs.net %K real-world data %K data quality %K quality improvement %K systematic literature review %K PRISMA %D 2024 %7 22.8.2024 %9 Review %J J Med Internet Res %G English %X Background: The promise of real-world evidence and the learning health care system primarily depends on access to high-quality data. Despite widespread awareness of the prevalence and potential impacts of poor data quality (DQ), best practices for its assessment and improvement are unknown. Objective: This review aims to investigate how existing research studies define, assess, and improve the quality of structured real-world health care data. Methods: A systematic literature search of studies in the English language was implemented in the Embase and PubMed databases to select studies that specifically aimed to measure and improve the quality of structured real-world data within any clinical setting. The time frame for the analysis was from January 1945 to June 2023. We standardized DQ concepts according to the Data Management Association (DAMA) DQ framework to enable comparison between studies. After screening and filtering by 2 independent authors, we identified 39 relevant articles reporting DQ improvement initiatives. Results: The studies were characterized by considerable heterogeneity in settings and approaches to DQ assessment and improvement. Affiliated institutions were from 18 different countries and 18 different health domains. DQ assessment methods were largely manual and targeted completeness and 1 other DQ dimension. Use of DQ frameworks was limited to the Weiskopf and Weng (3/6, 50%) or Kahn harmonized model (3/6, 50%). Use of standardized methodologies to design and implement quality improvement was lacking, but mainly included plan-do-study-act (PDSA) or define-measure-analyze-improve-control (DMAIC) cycles. Most studies reported DQ improvements using multiple interventions, which included either DQ reporting and personalized feedback (24/39, 61%), IT-related solutions (21/39, 54%), training (17/39, 44%), improvements in workflows (5/39, 13%), or data cleaning (3/39, 8%). Most studies reported improvements in DQ through a combination of these interventions. Statistical methods were used to determine significance of treatment effect (22/39, 56% times), but only 1 study implemented a randomized controlled study design. Variability in study designs, approaches to delivering interventions, and reporting DQ changes hindered a robust meta-analysis of treatment effects. Conclusions: There is an urgent need for standardized guidelines in DQ improvement research to enable comparison and effective synthesis of lessons learned. Frameworks such as PDSA learning cycles and the DAMA DQ framework can facilitate this unmet need. In addition, DQ improvement studies can also benefit from prioritizing root cause analysis of DQ issues to ensure the most appropriate intervention is implemented, thereby ensuring long-term, sustainable improvement. Despite the rise in DQ improvement studies in the last decade, significant heterogeneity in methodologies and reporting remains a challenge. Adopting standardized frameworks for DQ assessment, analysis, and improvement can enhance the effectiveness, comparability, and generalizability of DQ improvement initiatives. %M 39173155 %R 10.2196/57615 %U https://www.jmir.org/2024/1/e57615 %U https://doi.org/10.2196/57615 %U http://www.ncbi.nlm.nih.gov/pubmed/39173155 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e50307 %T Characteristics of Existing Online Patient Navigation Interventions: Scoping Review %A Marsh,Meghan %A Shah,Syeda Rafia %A Munce,Sarah E P %A Perrier,Laure %A Lee,Tin-Suet Joan %A Colella,Tracey J F %A Kokorelias,Kristina Marie %+ Section of Geriatrics, Sinai Health and University Health Network, 600 University Avenue, Geriatrics Department, Toronto, ON, M5G1X5, Canada, 1 4165864800 ext 4573, kristina.kokorelias@sinaihealth.ca %K online %K patient navigation %K peer navigation %K patient navigation interventions %K online patient navigation interventions %K scoping review %K patient portals %K social care services %K online medical tools %K eHealth %K telehealth %K personal support %K social care %K patient navigation intervention %D 2024 %7 19.8.2024 %9 Review %J JMIR Med Inform %G English %X Background: Patient navigation interventions (PNIs) can provide personalized support and promote appropriate coordination or continuation of health and social care services. Online PNIs have demonstrated excellent potential for improving patient knowledge, transition readiness, self-efficacy, and use of services. However, the characteristics (ie, intervention type, mode of delivery, duration, frequency, outcomes and outcome measures, underlying theories or mechanisms of change of the intervention, and impact) of existing online PNIs to support the health and social needs of individuals with illness remain unclear. Objective: This scoping review of the existing literature aims to identify the characteristics of existing online PNIs reported in the literature. Methods: A scoping review based on the guidelines outlined in the Joanna Briggs Institute framework was conducted. A search for peer-reviewed literature published between 1989 and 2022 on online PNIs was conducted using MEDLINE, CINAHL, Embase, PsycInfo, and Cochrane Library databases. Two independent reviewers conducted 2 levels of screening. Data abstraction was conducted to outline key study characteristics (eg, study design, population, and intervention characteristics). The data were analyzed using descriptive statistics and qualitative content analysis. Results: A total of 100 studies met the inclusion criteria. Our findings indicate that a variety of study designs are used to describe and evaluate online PNIs, with literature being published between 2003 and 2022 in Western countries. Of these studies, 39 (39%) studies were randomized controlled trials. In addition, we noticed an increase in reported online PNIs since 2019. The majority of studies involved White females with a diagnosis of cancer and a lack of participants aged 70 years or older was observed. Most online PNIs provide support through navigation, self-management and lifestyle changes, counseling, coaching, education, or a combination of support. Variation was noted in terms of mode of delivery, duration, and frequency. Only a small number of studies described theoretical frameworks or change mechanisms to guide intervention. Conclusions: To our knowledge, this is the first review to comprehensively synthesize the existing literature on online PNIs, by focusing on the characteristics of interventions and studies in this area. Inconsistency in reporting the country of publication, population characteristics, duration and frequency of interventions, and a lack of the use of underlying theories and working mechanisms to inform intervention development, provide guidance for the reporting of future online PNIs. %M 39159443 %R 10.2196/50307 %U https://medinform.jmir.org/2024/1/e50307 %U https://doi.org/10.2196/50307 %U http://www.ncbi.nlm.nih.gov/pubmed/39159443 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e57153 %T Evaluating and Enhancing the Fitness-for-Purpose of Electronic Health Record Data: Qualitative Study on Current Practices and Pathway to an Automated Approach Within the Medical Informatics for Research and Care in University Medicine Consortium %A Kamdje Wabo,Gaetan %A Moorthy,Preetha %A Siegel,Fabian %A Seuchter,Susanne A %A Ganslandt,Thomas %+ Center for Preventive Medicine and Digital Health Baden-Wuerttemberg, Department of Biomedical Informatics, Medical Faculty of Mannheim, University of Heidelberg, Building 3, Level 4, Theodor-Kutzer-Ufer 1-3, Mannheim, 68167, Germany, 49 621 383 8088, gaetankamdje.wabo@medma.uni-heidelberg.de %K data quality %K fitness-for-purpose %K secondary use %K thematic analysis %K EHR data %K electronic health record %K data integration center %K Medical Informatics Initiative %K MIRACUM consortium %K Medical Informatics for Research and Care in University Medicine %K data science %K integration %K data use %K visualization %K visualizations %K record %K records %K EHR %K EHRs %K survey %K surveys %K medical informatics %D 2024 %7 19.8.2024 %9 Original Paper %J JMIR Med Inform %G English %X Background: Leveraging electronic health record (EHR) data for clinical or research purposes heavily depends on data fitness. However, there is a lack of standardized frameworks to evaluate EHR data suitability, leading to inconsistent quality in data use projects (DUPs). This research focuses on the Medical Informatics for Research and Care in University Medicine (MIRACUM) Data Integration Centers (DICs) and examines empirical practices on assessing and automating the fitness-for-purpose of clinical data in German DIC settings. Objective: The study aims (1) to capture and discuss how MIRACUM DICs evaluate and enhance the fitness-for-purpose of observational health care data and examine the alignment with existing recommendations and (2) to identify the requirements for designing and implementing a computer-assisted solution to evaluate EHR data fitness within MIRACUM DICs. Methods: A qualitative approach was followed using an open-ended survey across DICs of 10 German university hospitals affiliated with MIRACUM. Data were analyzed using thematic analysis following an inductive qualitative method. Results: All 10 MIRACUM DICs participated, with 17 participants revealing various approaches to assessing data fitness, including the 4-eyes principle and data consistency checks such as cross-system data value comparison. Common practices included a DUP-related feedback loop on data fitness and using self-designed dashboards for monitoring. Most experts had a computer science background and a master’s degree, suggesting strong technological proficiency but potentially lacking clinical or statistical expertise. Nine key requirements for a computer-assisted solution were identified, including flexibility, understandability, extendibility, and practicability. Participants used heterogeneous data repositories for evaluating data quality criteria and practical strategies to communicate with research and clinical teams. Conclusions: The study identifies gaps between current practices in MIRACUM DICs and existing recommendations, offering insights into the complexities of assessing and reporting clinical data fitness. Additionally, a tripartite modular framework for fitness-for-purpose assessment was introduced to streamline the forthcoming implementation. It provides valuable input for developing and integrating an automated solution across multiple locations. This may include statistical comparisons to advanced machine learning algorithms for operationalizing frameworks such as the 3×3 data quality assessment framework. These findings provide foundational evidence for future design and implementation studies to enhance data quality assessments for specific DUPs in observational health care settings. %M 39158950 %R 10.2196/57153 %U https://medinform.jmir.org/2024/1/e57153 %U https://doi.org/10.2196/57153 %U http://www.ncbi.nlm.nih.gov/pubmed/39158950 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e52019 %T Summary Measure of Health-Related Quality of Life and Its Related Factors Based on the Chinese Version of the Core Healthy Days Measures: Cross-Sectional Study %A Shi,Yulin %A Wang,Baohua %A Zhao,Jian %A Wang,Chunping %A Li,Ning %A Chen,Min %A Wan,Xia %K health-related quality of life %K Healthy Days %K summary measure %K health status indicators %K exploratory factor analyses %K confirmatory factor analyses %D 2024 %7 31.7.2024 %9 %J JMIR Public Health Surveill %G English %X Background: The core Healthy Days measures were used to track the population-level health status in the China Chronic Disease and Risk Factor Surveillance; however, they were not easily combined to create a summary of the overall health-related quality of life (HRQOL), limiting this indicator’s use. Objective: This study aims to develop a summary score based on the Chinese version of the core Healthy Days measures (HRQOL-5) and apply it to estimate HRQOL and its determinants in a Chinese population. Methods: From November 2018 to May 2019, a multistage stratified cluster survey was conducted to examine population health status and behavioral risk factors among the resident population older than 15 years in Weifang City, Shandong Province, China. Both exploratory factor analyses and confirmatory factor analyses were performed to reveal the underlying latent construct of HRQOL-5 and then to quantify the overall HRQOL by calculating its summary score. Tobit regression models were finally carried out to identify the influencing factors of the summary score. Results: A total of 26,269 participants (male: n=13,571, 51.7%; mean age 55.9, SD 14.9 years) were included in this study. A total of 71% (n=18,663) of respondents reported that they had excellent or very good general health. One summary factor was extracted to capture overall HRQOL using exploratory factor analysis. The confirmatory factor analysis further confirmed this one-factor model (Tucker-Lewis index, comparative fit index, and goodness-of-fit index >0.90; root mean square error of approximation 0.02). Multivariate Tobit regression analysis showed that age (β=–0.06), educational attainments (primary school: β=0.72; junior middle school: β=1.46; senior middle school or more: β=2.58), average income (≥¥30,000 [US $4200]: β=0.69), physical activity (β=0.75), alcohol use (β=0.46), self-reported disease (β=−6.36), and self-reported injury (β=–5.00) were the major influencing factors on the summary score of the HRQOL-5. Conclusions: This study constructs a summary score from the HRQOL-5, providing a comprehensive representation of population-level HRQOL. Differences in summary scores of different subpopulations may help set priorities for health planning in China to improve population HRQOL. %R 10.2196/52019 %U https://publichealth.jmir.org/2024/1/e52019 %U https://doi.org/10.2196/52019 %0 Journal Article %@ 2561-9128 %I JMIR Publications %V 7 %N %P e57541 %T Preoperative Anesthesia Virtual Video Consultations in a Preadmission Clinic: Quality Improvement Study %A Subramani,Yamini %A Querney,Jill %A Singh,Priyanka %A Zhang,Yifan %A Fochesato,Lee-Anne %A Fatima,Nida %A Wood,Natasha %A Nagappa,Mahesh %+ Department of Anesthesia and Perioperative Medicine, London Health Sciences Centre, St. Joseph Health Care, Schulich School of Medicine and Dentistry, Western University, 339 Windermere Road, London, ON, N6A 5A5, Canada, 1 5196858500 ext 34436, Mahesh.Nagappa@lhsc.on.ca %K preoperative evaluation %K preadmission clinic %K telemedicine %K remote %K virtual care %K remote consultation %K video consultation %K telehealth %K online health %K digital health %K perioperative medicine %K preoperative %K eMedicine %K surgery %K consultation %K safety %K assessment %K virtual care %K workflow %K implementation %K integration %K hospital %D 2024 %7 25.7.2024 %9 Original Paper %J JMIR Perioper Med %G English %X Background: The preadmission clinic (PAC) is crucial in perioperative care, offering evaluations, education, and patient optimization before surgical procedures. During the COVID-19 pandemic, the PAC adapted by implementing telephone visits due to a lack of infrastructure for video consultations. While the pandemic significantly increased the use of virtual care, including video appointments as an alternative to in-person consultations, our PAC had not used video consultations for preoperative assessments. Objective: This study aimed to develop, implement, and integrate preoperative video consultations into the PAC workflow. Methods: A prospective quality improvement project was undertaken using the Plan-Do-Study-Act (PDSA) methodology. The project focused on developing, implementing, and integrating virtual video consultations at London Health Sciences Centre and St. Joseph Health Care (London, Ontario, Canada) in the PAC. Data were systematically collected to monitor the number of patients undergoing video consultations, address patient flow concerns, and increase the percentage of video consultations. Communication between the PAC, surgeon offices, and patients was analyzed for continuous improvement. Technological challenges were addressed, and procedures were streamlined to facilitate video calls on appointment days. Results: The PAC team, which includes professionals from medicine, anesthesia, nursing, pharmacy, occupational therapy, and physiotherapy, offers preoperative evaluation and education to surgical patients, conducting approximately 8000 consultations annually across 3 hospital locations. Following the initial PDSA cycles, the interventions consistently improved the video consultation utilization rate to 17%, indicating positive progress. With the onset of PDSA cycle 3, there was a notable surge to a 29% utilization rate in the early phase. This upward trend continued, culminating in a 38% utilization rate of virtual video consultations in the later stages of the cycle. This heightened level was consistently maintained throughout 2023, highlighting the sustained success of our interventions. Conclusions: The quality improvement process significantly enhanced the institution’s preoperative video consultation workflow. By understanding the complexities within the PAC, strategic interventions were made to integrate video consultations without compromising efficiency, morale, or safety. This project highlights the potential for transformative improvements in health care delivery through the thoughtful integration of virtual care technologies. %M 39052992 %R 10.2196/57541 %U https://periop.jmir.org/2024/1/e57541 %U https://doi.org/10.2196/57541 %U http://www.ncbi.nlm.nih.gov/pubmed/39052992 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e57717 %T Telehealth Uptake Among Hispanic People During COVID-19: Retrospective Observational Study %A Shang,Di %A Williams,Cynthia %A Culiqi,Hera %K telehealth %K telemedicine %K ICT %K eHealth %K e-health %K Hispanic %K health equity %K health access %K Hispanics %K digital divide %K usage %K utilization %K equity %K inequity %K inequities %K access %K accessibility %K Spanish %K observational %K demographic %K demographics %K socioeconomic %K socioeconomics %K information and communication technology %D 2024 %7 24.7.2024 %9 %J JMIR Med Inform %G English %X Background: The Hispanic community represents a sizeable community that experiences inequities in the US health care system. As the system has moved toward digital health platforms, evaluating the potential impact on Hispanic communities is critical. Objective: The study aimed to investigate demographic, socioeconomic, and behavioral factors contributing to low telehealth use in Hispanic communities. Methods: We used a retrospective observation study design to examine the study objectives. The COVID-19 Research Database Consortium provided the Analytics IQ PeopleCore consumer data and Office Alley claims data. The study period was from March 2020 to April 2021. Multiple logistic regression was used to determine the odds of using telehealth services. Results: We examined 3,478,287 unique Hispanic patients, 16.6% (577,396) of whom used telehealth. Results suggested that patients aged between 18 and 44 years were more likely to use telehealth (odds ratio [OR] 1.07, 95% CI 1.05-1.1; P<.001) than patients aged older than 65 years. Across all age groups, patients with high incomes were at least 20% more likely to use telehealth than patients with lower incomes (P<.001); patients who had a primary care physician (P=.01), exhibited high medical usage (P<.001), or were interested in exercise (P=.03) were more likely to use telehealth; patients who had unhealthy behaviors such as smoking and alcohol consumption were less likely to use telehealth (P<.001). Male patients were less likely than female patients to use telehealth among patients aged 65 years and older (OR 0.94, 95% CI 0.93-0.95; P<.001), while male patients aged between 18 and 44 years were more likely to use telehealth (OR 1.05, 95% CI 1.03-1.07; P<.001). Among patients younger than 65 years, full-time employment was positively associated with telehealth use (P<.001). Patients aged between 18 and 44 years with high school or less education were 2% less likely to use telehealth (OR 0.98, 95% CI 0.97-0.99; P=.005). Results also revealed a positive association with using WebMD (WebMD LLC) among patients aged older than 44 years (P<.001), while there was a negative association with electronic prescriptions among those who were aged between 18 and 44 years (P=.009) and aged between 45 and 64 years (P=.004). Conclusions: This study demonstrates that telehealth use among Hispanic communities is dependent upon factors such as age, gender, education, socioeconomic status, current health care engagement, and health behaviors. To address these challenges, we advocate for interdisciplinary approaches that involve medical professionals, insurance providers, and community-based services actively engaging with Hispanic communities and promoting telehealth use. We propose the following recommendations: enhance access to health insurance, improve access to primary care providers, and allocate fiscal and educational resources to support telehealth use. As telehealth increasingly shapes health care delivery, it is vital for professionals to facilitate the use of all available avenues for accessing care. %R 10.2196/57717 %U https://medinform.jmir.org/2024/1/e57717 %U https://doi.org/10.2196/57717 %0 Journal Article %@ 2368-7959 %I %V 11 %N %P e56886 %T Impacts of Telehealth Adoption on the Quality of Care for Individuals With Serious Mental Illness: Retrospective Observational Analysis of Veterans Affairs Administrative Data %A Cummings,Camilla %A Raja,Pushpa %A Gabrielian,Sonya %A Doran,Neal %K telemedicine %K quality of care %K serious mental illness %K telehealth %K adoption %K mental illness %K patients %K patient %K veterans %K veteran %K psychotherapy %K psychosocial %K mental healthcare %K suicide %K rehabilitation %K mental health care %D 2024 %7 9.7.2024 %9 %J JMIR Ment Health %G English %X Background: Telehealth implementation can be challenging for persons with serious mental illness (SMI), which may impact their quality of care and health outcomes. The literature on telehealth’s impacts on SMI care outcomes is mixed, necessitating further investigation. Objective: We examined the impacts of facility-level telehealth adoption on quality of care metrics over time among patients with SMI. Methods: We analyzed Veterans Affairs (VA) administrative data across 138 facilities from January 2021 to December 2022. We performed longitudinal mixed-effects regressions to identify the relationships between the proportion of facility-level telehealth visits and SMI specialty care quality metrics: engagement with primary care; access and continuity of care across a range of mental health services including psychotherapy or psychosocial rehabilitation, SMI-specific intensive outpatient programs, and intensive case management; and continuity of mental health care after a high-risk event (eg, suicide attempt). Results: Facilities with a higher proportion of telehealth visits had reduced access and continuity of physical and mental health care for patients with SMI (P<.05). Higher telehealth adoption was associated with reduced primary care engagement (z=−4.04; P<.001), reduced access to and continuity in SMI-specific intensive case management (z=−4.49; P<.001; z=−3.15; P<.002), reductions in the continuity of care within psychotherapy and psychosocial rehabilitation (z=−3.74; P<.001), and continuity of care after a high-risk event (z=−2.46; P<.01). Telehealth uptake initially increased access to intensive outpatient but did not improve its continuity over time (z=−4.47; P<.001). Except for continuity within SMI-specific intensive case management (z=2.62; P<.009), continuity did not improve over time as telehealth became routinized. Conclusions: Although telehealth helped preserve health care access during the pandemic, telehealth may have tradeoffs with regard to quality of care for some individuals with SMI. These data suggest that engagement strategies used by SMI-specific intensive case management may have preserved quality and could benefit other settings. Strategies that enhance telehealth implementation—selected through a health equity lens—may improve quality of care among patients with SMI. %R 10.2196/56886 %U https://mental.jmir.org/2024/1/e56886 %U https://doi.org/10.2196/56886 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e50437 %T Considerations for Quality Control Monitoring of Machine Learning Models in Clinical Practice %A Faust,Louis %A Wilson,Patrick %A Asai,Shusaku %A Fu,Sunyang %A Liu,Hongfang %A Ruan,Xiaoyang %A Storlie,Curt %+ Robert D and Patricia E Kern Center for the Science of Health Care Delivery, Mayo Clinic, Mayo Clinic, 200 First St. SW, Rochester, MN, 55905, United States, 1 (507) 284 2511, Faust.Louis@mayo.edu %K artificial intelligence %K machine learning %K implementation science %K quality control %K monitoring %K patient safety %D 2024 %7 28.6.2024 %9 Viewpoint %J JMIR Med Inform %G English %X Integrating machine learning (ML) models into clinical practice presents a challenge of maintaining their efficacy over time. While existing literature offers valuable strategies for detecting declining model performance, there is a need to document the broader challenges and solutions associated with the real-world development and integration of model monitoring solutions. This work details the development and use of a platform for monitoring the performance of a production-level ML model operating in Mayo Clinic. In this paper, we aimed to provide a series of considerations and guidelines necessary for integrating such a platform into a team’s technical infrastructure and workflow. We have documented our experiences with this integration process, discussed the broader challenges encountered with real-world implementation and maintenance, and included the source code for the platform. Our monitoring platform was built as an R shiny application, developed and implemented over the course of 6 months. The platform has been used and maintained for 2 years and is still in use as of July 2023. The considerations necessary for the implementation of the monitoring platform center around 4 pillars: feasibility (what resources can be used for platform development?); design (through what statistics or models will the model be monitored, and how will these results be efficiently displayed to the end user?); implementation (how will this platform be built, and where will it exist within the IT ecosystem?); and policy (based on monitoring feedback, when and what actions will be taken to fix problems, and how will these problems be translated to clinical staff?). While much of the literature surrounding ML performance monitoring emphasizes methodological approaches for capturing changes in performance, there remains a battery of other challenges and considerations that must be addressed for successful real-world implementation. %M 38941140 %R 10.2196/50437 %U https://medinform.jmir.org/2024/1/e50437 %U https://doi.org/10.2196/50437 %U http://www.ncbi.nlm.nih.gov/pubmed/38941140 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e55000 %T Health Information System Strengthening During Antenatal Care in Haiti: Continuous Quality Improvement Study %A Casella Jean-Baptiste,Meredith %A Vital Julmiste,Thamar Monide %A Ball,Ellen %+ Hôpital Universitaire de Mirebalais, Sante Fanm, Rue Chatulee, Mirebalais, HT 5210, Haiti, 509 4892 3626, mjeanbaptiste@pih.org %K maternal health %K health informatics %K quality improvement %K Plan-Do-Study-Act %K PDSA %K maternal %K neonatal %K data collection %K prenatal %K outpatient %K electronic data %K nursing %K nursing staff %K nursing leadership %D 2024 %7 14.6.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Journey to 9 Plus (J9) is an integrated reproductive, maternal, neonatal, and child health approach to care that has at its core the goal of decreasing the rate of maternal and neonatal morbidity and mortality in rural Haiti. For the maximum effectiveness of this program, it is necessary that the data system be of the highest quality. OpenMRS, an electronic medical record (EMR) system, has been in place since 2013 throughout a tertiary referral hospital, the Hôpital Universitaire de Mirebalais, in Haiti and has been expanded for J9 data collection and reporting. The J9 program monthly reports showed that staff had limited time and capacity to perform double charting, which contributed to incomplete and inconsistent reports. Initial evaluation of the quality of EMR data entry showed that only 18% (58/325) of the J9 antenatal visits were being documented electronically at the start of this quality improvement project. Objective: This study aimed to improve the electronic documentation of outpatient antenatal care from 18% (58/325) to 85% in the EMR by J9 staff from November 2020 to September 2021. The experiences that this quality improvement project team encountered could help others improve electronic data collection as well as the transition from paper to electronic documentation within a burgeoning health care system. Methods: A continuous quality improvement strategy was undertaken as the best approach to improve the EMR data collection at Hôpital Universitaire de Mirebalais. The team used several continuous quality improvement tools to conduct this project: (1) a root cause analysis using Ishikawa and Pareto diagrams, (2) baseline evaluation measurements, and (3) Plan-Do-Study-Act improvement cycles to document incremental changes and the results of each change. Results: At the beginning of the quality improvement project in November 2020, the baseline data entry for antenatal visits was 18% (58/325). Ten months of improvement strategies resulted in an average of 89% (272/304) of antenatal visits documented in the EMR at point of care every month. Conclusions: The experiences that this quality improvement project team encountered can contribute to the transition from paper to electronic documentation within burgeoning health care systems. Essential to success was having a strong and dedicated nursing leadership to transition from paper to electronic data and motivated nursing staff to perform data collection to improve the quality of data and thus, the reports on patient outcomes. Engaging the nursing team closely in the design and implementation of EMR and quality improvement processes ensures long-term success while centering nurses as key change agents in patient care systems. %M 38875702 %R 10.2196/55000 %U https://formative.jmir.org/2024/1/e55000 %U https://doi.org/10.2196/55000 %U http://www.ncbi.nlm.nih.gov/pubmed/38875702 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 12 %N %P e54579 %T Mobile Health App and Web Platform (eDOL) for Medical Follow-Up of Patients With Chronic Pain: Cohort Study Involving the French eDOL National Cohort After 1 Year %A Delage,Noémie %A Cantagrel,Nathalie %A Soriot-Thomas,Sandrine %A Frost,Marie %A Deleens,Rodrigue %A Ginies,Patrick %A Eschalier,Alain %A Corteval,Alice %A Laveyssière,Alicia %A Phalip,Jules %A Bertin,Célian %A Pereira,Bruno %A Chenaf,Chouki %A Doreau,Bastien %A Authier,Nicolas %A , %A Kerckhove,Nicolas %+ Service de pharmacologie médicale, CHU Clermont-Ferrand, 58 rue Montalembert, Clermont-Ferrand, 63000, France, 33 473754833, nkerckhove@chu-clermontferrand.fr %K mHealth %K mobile health %K eHealth %K self-monitoring %K chronic pain %K observational study %D 2024 %7 12.6.2024 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Chronic pain affects approximately 30% of the general population, severely degrades quality of life and professional life, and leads to additional health care costs. Moreover, the medical follow-up of patients with chronic pain remains complex and provides only fragmentary data on painful daily experiences. This situation makes the management of patients with chronic pain less than optimal and may partly explain the lack of effectiveness of current therapies. Real-life monitoring of subjective and objective markers of chronic pain using mobile health (mHealth) programs could better characterize patients, chronic pain, pain medications, and daily impact to help medical management. Objective: This cohort study aimed to assess the ability of our mHealth tool (eDOL) to collect extensive real-life medical data from chronic pain patients after 1 year of use. The data collected in this way would provide new epidemiological and pathophysiological data on chronic pain. Methods: A French national cohort of patients with chronic pain treated at 18 pain clinics has been established and followed up using mHealth tools. This cohort makes it possible to collect the determinants and repercussions of chronic pain and their evolutions in a real-life context, taking into account all environmental events likely to influence chronic pain. The patients were asked to complete several questionnaires, body schemes, and weekly meters, and were able to interact with a chatbot and use educational modules on chronic pain. Physicians could monitor their patients’ progress in real time via an online platform. Results: The cohort study included 1427 patients and analyzed 1178 patients. The eDOL tool was able to collect various sociodemographic data; specific data for characterizing pain disorders, including body scheme; data on comorbidities related to chronic pain and its psychological and overall impact on patients’ quality of life; data on drug and nondrug therapeutics and their benefit-to-risk ratio; and medical or treatment history. Among the patients completing weekly meters, 49.4% (497/1007) continued to complete them after 3 months of follow-up, and the proportion stabilized at 39.3% (108/275) after 12 months of follow-up. Overall, despite a fairly high attrition rate over the follow-up period, the eDOL tool collected extensive data. This amount of data will increase over time and provide a significant volume of health data of interest for future research involving the epidemiology, care pathways, trajectories, medical management, sociodemographic characteristics, and other aspects of patients with chronic pain. Conclusions: This work demonstrates that the mHealth tool eDOL is able to generate a considerable volume of data concerning the determinants and repercussions of chronic pain and their evolutions in a real-life context. The eDOL tool can incorporate numerous parameters to ensure the detailed characterization of patients with chronic pain for future research and pain management. Trial Registration: ClinicalTrials.gov NCT04880096; https://clinicaltrials.gov/ct2/show/NCT04880096 %M 38865173 %R 10.2196/54579 %U https://mhealth.jmir.org/2024/1/e54579 %U https://doi.org/10.2196/54579 %U http://www.ncbi.nlm.nih.gov/pubmed/38865173 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e54811 %T Evaluating the Prevalence of Burnout Among Health Care Professionals Related to Electronic Health Record Use: Systematic Review and Meta-Analysis %A Wu,Yuxuan %A Wu,Mingyue %A Wang,Changyu %A Lin,Jie %A Liu,Jialin %A Liu,Siru %+ Information Center, West China Hospital, Sichuan University, 37 Guoxue Road, Chengdu, 610041, China, 86 28 85422306, Dljl8@163.com %K clinical decision support system %K electronic health record %K electronic medical record %K health information technology %K alert fatigue %K burnout %K health care professionals %K health care service %K EHR %K systematic review %K meta-analysis %K health information system %K clinician burnout %K health informatics %D 2024 %7 12.6.2024 %9 Review %J JMIR Med Inform %G English %X Background: Burnout among health care professionals is a significant concern, with detrimental effects on health care service quality and patient outcomes. The use of the electronic health record (EHR) system has been identified as a significant contributor to burnout among health care professionals. Objective: This systematic review and meta-analysis aims to assess the prevalence of burnout among health care professionals associated with the use of the EHR system, thereby providing evidence to improve health information systems and develop strategies to measure and mitigate burnout. Methods: We conducted a comprehensive search of the PubMed, Embase, and Web of Science databases for English-language peer-reviewed articles published between January 1, 2009, and December 31, 2022. Two independent reviewers applied inclusion and exclusion criteria, and study quality was assessed using the Joanna Briggs Institute checklist and the Newcastle-Ottawa Scale. Meta-analyses were performed using R (version 4.1.3; R Foundation for Statistical Computing), with EndNote X7 (Clarivate) for reference management. Results: The review included 32 cross-sectional studies and 5 case-control studies with a total of 66,556 participants, mainly physicians and registered nurses. The pooled prevalence of burnout among health care professionals in cross-sectional studies was 40.4% (95% CI 37.5%-43.2%). Case-control studies indicated a higher likelihood of burnout among health care professionals who spent more time on EHR-related tasks outside work (odds ratio 2.43, 95% CI 2.31-2.57). Conclusions: The findings highlight the association between the increased use of the EHR system and burnout among health care professionals. Potential solutions include optimizing EHR systems, implementing automated dictation or note-taking, employing scribes to reduce documentation burden, and leveraging artificial intelligence to enhance EHR system efficiency and reduce the risk of burnout. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42021281173; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021281173 %M 38865188 %R 10.2196/54811 %U https://medinform.jmir.org/2024/1/e54811 %U https://doi.org/10.2196/54811 %U http://www.ncbi.nlm.nih.gov/pubmed/38865188 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e47620 %T Physician Perspectives on Internet-Informed Patients: Systematic Review %A Lu,Qianfeng %A Schulz,Peter Johannes %+ Faculty of Communication, Culture and Society, Università della Svizzera italiana, Via Buffi 13, Lugano, 6900, Switzerland, 41 586664724, schulzp@usi.ch %K internet-informed patients %K physician-patient communication %K health information–seeking %K misinformation %K digital health %D 2024 %7 6.6.2024 %9 Review %J J Med Internet Res %G English %X Background: The internet has become a prevalent source of health information for patients. However, its accuracy and relevance are often questionable. While patients seek physicians’ expertise in interpreting internet health information, physicians’ perspectives on patients’ information-seeking behavior are less explored. Objective: This review aims to understand physicians’ perceptions of patients’ internet health information-seeking behavior as well as their communication strategies and the challenges and needs they face with internet-informed patients. Methods: An initial search in PubMed, Scopus, CINAHL, Communication and Mass Media Complete, and PsycINFO was conducted to collect studies published from January 1990 to August 1, 2022. A subsequent search on December 24, 2023, targeted recent studies published after the initial search cutoff date. Two reviewers independently performed title, abstract, and full-text screening, adhering to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement guidelines. Thematic analysis was then used to identify key themes and systematically categorize evidence from both qualitative and quantitative studies under these themes. Results: A total of 22 qualifying articles were identified after the search and screening process. Physicians were found to hold diverse views on patients’ internet searches, which can be viewed as a continuous spectrum of opinions ranging from positive to negative. While some physicians leaned distinctly toward either positive or negative perspectives, a significant number expressed more balanced views. These physicians recognized both the benefits, such as increased patient health knowledge and informed decision-making, and the potential harms, including misinformation and the triggering of negative emotions, such as patient anxiety or confusion, associated with patients’ internet health information seeking. Two communicative strategies were identified: the participative and defensive approaches. While the former seeks to guide internet-informed patients to use internet information with physicians’ expertise, the latter aims to discourage patients from using the internet to seek health information. Physicians’ perceptions were linked to their strategies: those holding positive views tended to adopt a participative approach, while those with negative views favored a defensive strategy. Some physicians claimed to shift between the 2 approaches depending on their interaction with a certain patient. We also identified several challenges and needs of physicians in dealing with internet-informed patients, including the time pressure to address internet-informed patient demands, a lack of structured training, and being uninformed about trustworthy internet sites that can be recommended to internet-informed patients. Conclusions: This review highlights the diverse perceptions that physicians hold toward internet-informed patients, as well as the interplay between their perceptions, communication strategies, and their interactions with individual patients. Incorporating elements into the medical teaching curriculum that introduce physicians to reliable internet health resources for patient guidance, coupled with providing updates on technological advancements, could be instrumental in equipping physicians to more effectively manage internet-informed patients. Trial Registration: PROSPERO CRD42022356317; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=356317 %M 38842920 %R 10.2196/47620 %U https://www.jmir.org/2024/1/e47620 %U https://doi.org/10.2196/47620 %U http://www.ncbi.nlm.nih.gov/pubmed/38842920 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e54334 %T Exploring Consumers’ Negative Electronic Word-of-Mouth of 5 Military Hospitals in Taiwan Through SERVQUAL and Flower of Services: Web Scraping Analysis %A Huang,Ching-Yuan %A Lee,Po-Chun %A Chen,Long-Hui %+ Department of Internal Medicine, Kaohsiung Armed Forces General Hospital, No.2, Zhongzheng 1st Rd., Lingya Dist., Kaohsiung, 80284, Taiwan, 886 953332550, chyun0124@gmail.com %K electronic word-of-mouth %K eWOM %K service quality %K SERVQUAL scale %K Flower of Services %K health care service quality %K military hospitals %D 2024 %7 29.5.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: In recent years, with the widespread use of the internet, the influence of electronic word-of-mouth (eWOM) has been increasingly recognized, particularly the significance of negative eWOM, which has surpassed positive eWOM in importance. Such reviews play a pivotal role in research related to service industry management, particularly in intangible service sectors such as hospitals, where they have become a reference point for improving service quality. Objective: This study comprehensively collected negative eWOM from 5 military hospitals in Taiwan that were at or above the level of regional teaching hospitals. It aimed to investigate service quality issues before and after the pandemic. The findings provide important references for formulating strategies to improve service quality. Methods: In this study, we used web scraping techniques to gather 1259 valid negative eWOM, covering the period from the inception of the first review to December 31, 2022. These reviews were categorized using content analysis based on the modified Parasuraman, Zeithaml, and Berry service quality (PZB SERVQUAL) scale and Flower of Services. Statistical data analysis was conducted to investigate the performance of service quality. Results: The annual count of negative reviews for each hospital has exhibited a consistent upward trajectory over the years, with a more pronounced increase following the onset of the pandemic. In the analysis, among the 5 dimensions of PZB SERVQUAL framework, the “Assurance” dimension yielded the least favorable results, registering a negative review rate as high as 58.3%. Closely trailing, the “Responsiveness” dimension recorded a negative review rate of 34.2%. When evaluating the service process, the subitem “In Service: Diagnosis/Examination/Medical/Hospitalization” exhibited the least satisfactory performance, with a negative review rate of 46.2%. This was followed by the subitem “In Service: Pre-diagnosis Waiting,” which had a negative review rate of 20.2%. To evaluate the average scores of negative reviews before and during the onset of the COVID-19 pandemic, independent sample t tests (2-tailed) were used. The analysis revealed statistically significant differences (P<.001). Furthermore, an ANOVA was conducted to investigate whether the length of the negative reviews impacted their ratings, which also showed significant differences (P=.01). Conclusions: Before and during the pandemic, there were significant differences in evaluating hospital services, and a higher word count in negative reviews indicated greater dissatisfaction with the service. Therefore, it is recommended that hospitals establish more comprehensive service quality management mechanisms, carefully respond to negative reviews, and categorize significant service deficiencies as critical events to prevent a decrease in overall service quality. Furthermore, during the service process, customers are particularly concerned about the attitude and responsiveness of health care personnel in the treatment process. Therefore, hospitals should enhance training and management in this area. %M 38809602 %R 10.2196/54334 %U https://formative.jmir.org/2024/1/e54334 %U https://doi.org/10.2196/54334 %U http://www.ncbi.nlm.nih.gov/pubmed/38809602 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e50853 %T The Effect of Artificial Intelligence on Patient-Physician Trust: Cross-Sectional Vignette Study %A Zondag,Anna G M %A Rozestraten,Raoul %A Grimmelikhuijsen,Stephan G %A Jongsma,Karin R %A van Solinge,Wouter W %A Bots,Michiel L %A Vernooij,Robin W M %A Haitjema,Saskia %+ Central Diagnostic Laboratory, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, 3584 CX, Netherlands, 31 631117922, a.g.m.zondag@umcutrecht.nl %K patient-physician relationship %K trust %K clinical decision support %K artificial intelligence %K digital health %K decision support system %D 2024 %7 28.5.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Clinical decision support systems (CDSSs) based on routine care data, using artificial intelligence (AI), are increasingly being developed. Previous studies focused largely on the technical aspects of using AI, but the acceptability of these technologies by patients remains unclear. Objective: We aimed to investigate whether patient-physician trust is affected when medical decision-making is supported by a CDSS. Methods: We conducted a vignette study among the patient panel (N=860) of the University Medical Center Utrecht, the Netherlands. Patients were randomly assigned into 4 groups—either the intervention or control groups of the high-risk or low-risk cases. In both the high-risk and low-risk case groups, a physician made a treatment decision with (intervention groups) or without (control groups) the support of a CDSS. Using a questionnaire with a 7-point Likert scale, with 1 indicating “strongly disagree” and 7 indicating “strongly agree,” we collected data on patient-physician trust in 3 dimensions: competence, integrity, and benevolence. We assessed differences in patient-physician trust between the control and intervention groups per case using Mann-Whitney U tests and potential effect modification by the participant’s sex, age, education level, general trust in health care, and general trust in technology using multivariate analyses of (co)variance. Results: In total, 398 patients participated. In the high-risk case, median perceived competence and integrity were lower in the intervention group compared to the control group but not statistically significant (5.8 vs 5.6; P=.16 and 6.3 vs 6.0; P=.06, respectively). However, the effect of a CDSS application on the perceived competence of the physician depended on the participant’s sex (P=.03). Although no between-group differences were found in men, in women, the perception of the physician’s competence and integrity was significantly lower in the intervention compared to the control group (P=.009 and P=.01, respectively). In the low-risk case, no differences in trust between the groups were found. However, increased trust in technology positively influenced the perceived benevolence and integrity in the low-risk case (P=.009 and P=.04, respectively). Conclusions: We found that, in general, patient-physician trust was high. However, our findings indicate a potentially negative effect of AI applications on the patient-physician relationship, especially among women and in high-risk situations. Trust in technology, in general, might increase the likelihood of embracing the use of CDSSs by treating professionals. %M 38805702 %R 10.2196/50853 %U https://www.jmir.org/2024/1/e50853 %U https://doi.org/10.2196/50853 %U http://www.ncbi.nlm.nih.gov/pubmed/38805702 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e53872 %T Assessing the Content and Effect of Web-Based Decision Aids for Postmastectomy Breast Reconstruction: Systematic Review and Meta-Analysis of Randomized Controlled Trials %A Yu,Lin %A Gong,Jianmei %A Sun,Xiaoting %A Zang,Min %A Liu,Lei %A Yu,Shengmiao %+ School of Nursing, Liaoning University of Chinese Traditional Medicine, No.79 Chongshan Dong Road, Shenyang, 110000, China, 86 17824909908, liulei0428@sina.com %K decision aids %K internet %K postmastectomy breast reconstruction %K decision conflicts %K mobile phone %D 2024 %7 27.5.2024 %9 Review %J J Med Internet Res %G English %X Background: Web-based decision aids have been shown to have a positive effect when used to improve the quality of decision-making for women facing postmastectomy breast reconstruction (PMBR). However, the existing findings regarding these interventions are still incongruent, and the overall effect is unclear. Objective: We aimed to assess the content of web-based decision aids and its impact on decision-related outcomes (ie, decision conflict, decision regret, informed choice, and knowledge), psychological-related outcomes (ie, satisfaction and anxiety), and surgical decision-making in women facing PMBR. Methods: This systematic review and meta-analysis followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A total of 6 databases, PubMed, Embase, Cochrane Library, CINAHL, PsycINFO, and Web of Science Core Collection, were searched starting at the time of establishment of the databases to May 2023, and an updated search was conducted on April 1, 2024. MeSH (Medical Subject Headings) terms and text words were used. The Cochrane Risk of Bias Tool for randomized controlled trials was used to assess the risk of bias. The certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluation approach. Results: In total, 7 studies included 579 women and were published between 2008 and 2023, and the sample size in each study ranged from 26 to 222. The results showed that web-based decision aids used audio and video to present the pros and cons of PMBR versus no PMBR, implants versus flaps, and immediate versus delayed PMBR and the appearance and feel of the PMBR results and the expected recovery time with photographs of actual patients. Web-based decision aids help improve PMBR knowledge, decisional conflict (mean difference [MD]=–5.43, 95% CI –8.87 to –1.99; P=.002), and satisfaction (standardized MD=0.48, 95% CI 0.00 to 0.95; P=.05) but have no effect on informed choice (MD=–2.80, 95% CI –8.54 to 2.94; P=.34), decision regret (MD=–1.55, 95% CI –6.00 to 2.90 P=.49), or anxiety (standardized MD=0.04, 95% CI –0.50 to 0.58; P=.88). The overall Grading of Recommendations, Assessment, Development, and Evaluation quality of the evidence was low. Conclusions: The findings suggest that the web-based decision aids provide a modern, low-cost, and high dissemination rate effective method to promote the improved quality of decision-making in women undergoing PMBR. Trial Registration: PROSPERO CRD42023450496; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=450496 %M 38801766 %R 10.2196/53872 %U https://www.jmir.org/2024/1/e53872 %U https://doi.org/10.2196/53872 %U http://www.ncbi.nlm.nih.gov/pubmed/38801766 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e54705 %T AI Quality Standards in Health Care: Rapid Umbrella Review %A Kuziemsky,Craig E %A Chrimes,Dillon %A Minshall,Simon %A Mannerow,Michael %A Lau,Francis %+ MacEwan University, 10700 104 Avenue, 7-257, Edmonton, AB, T5J4S2, Canada, 1 7806333290, kuziemskyc@macewan.ca %K artificial intelligence %K health care artificial intelligence %K health care AI %K rapid review %K umbrella review %K quality standard %D 2024 %7 22.5.2024 %9 Review %J J Med Internet Res %G English %X Background: In recent years, there has been an upwelling of artificial intelligence (AI) studies in the health care literature. During this period, there has been an increasing number of proposed standards to evaluate the quality of health care AI studies. Objective: This rapid umbrella review examines the use of AI quality standards in a sample of health care AI systematic review articles published over a 36-month period. Methods: We used a modified version of the Joanna Briggs Institute umbrella review method. Our rapid approach was informed by the practical guide by Tricco and colleagues for conducting rapid reviews. Our search was focused on the MEDLINE database supplemented with Google Scholar. The inclusion criteria were English-language systematic reviews regardless of review type, with mention of AI and health in the abstract, published during a 36-month period. For the synthesis, we summarized the AI quality standards used and issues noted in these reviews drawing on a set of published health care AI standards, harmonized the terms used, and offered guidance to improve the quality of future health care AI studies. Results: We selected 33 review articles published between 2020 and 2022 in our synthesis. The reviews covered a wide range of objectives, topics, settings, designs, and results. Over 60 AI approaches across different domains were identified with varying levels of detail spanning different AI life cycle stages, making comparisons difficult. Health care AI quality standards were applied in only 39% (13/33) of the reviews and in 14% (25/178) of the original studies from the reviews examined, mostly to appraise their methodological or reporting quality. Only a handful mentioned the transparency, explainability, trustworthiness, ethics, and privacy aspects. A total of 23 AI quality standard–related issues were identified in the reviews. There was a recognized need to standardize the planning, conduct, and reporting of health care AI studies and address their broader societal, ethical, and regulatory implications. Conclusions: Despite the growing number of AI standards to assess the quality of health care AI studies, they are seldom applied in practice. With increasing desire to adopt AI in different health topics, domains, and settings, practitioners and researchers must stay abreast of and adapt to the evolving landscape of health care AI quality standards and apply these standards to improve the quality of their AI studies. %M 38776538 %R 10.2196/54705 %U https://www.jmir.org/2024/1/e54705 %U https://doi.org/10.2196/54705 %U http://www.ncbi.nlm.nih.gov/pubmed/38776538 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e55623 %T Implementation of Inpatient Electronic Consultations During the COVID-19 Crisis and Its Sustainability Beyond the Pandemic: Quality Improvement Study %A Aledia,Anna S %A Dangodara,Amish A %A Amin,Aanya A %A Amin,Alpesh N %+ Department of Medicine & Hospital Medicine, University of California, Irvine, 333 City Boulevard West, Suite 500, Orange, CA, 92868, United States, 1 714 456 3785, anamin@uci.edu %K COVID-19 %K electronic consultation %K eConsult %K e-consult %K inpatient %K consultations %K pandemic %K infectious %K novel coronavirus %K coronavirus %K patients %K patient %K staff %K health care %K health care providers %K tool %K tools %K effectiveness %D 2024 %7 16.5.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Limiting in-person contact was a key strategy for controlling the spread of the highly infectious novel coronavirus (COVID-19). To protect patients and staff from the risk of infection while providing continued access to necessary health care services, we implemented a new electronic consultation (e-consult) service that allowed referring providers to receive subspecialty consultations for patients who are hospitalized and do not require in-person evaluation by the specialist. Objective: We aimed to assess the impact of implementing e-consults in the inpatient setting to reduce avoidable face-to-face referrals during the COVID-19 pandemic. Methods: This quality improvement study evaluated all inpatient e-consults ordered from July 2020 to December 2022 at the University of California Irvine Medical Center. The impact of e-consults was assessed by evaluating use (eg, number of e-consults ordered), e-consult response times, and outcome of the e-consult requests (eg, resolved electronically or converted to the in-person evaluation of patient). Results: There were 1543 inpatient e-consults ordered across 11 participating specialties. A total of 53.5% (n=826) of requests were addressed electronically, without the need for a formal in-person evaluation of the patient. The median time between ordering an e-consult and a specialist documenting recommendations in an e-consult note was 3.7 (IQR 1.3-8.2) hours across all specialties, contrasted with 7.3 (IQR 3.6-22.0) hours when converted to an in-person consult (P<.001). The monthly volume of e-consult requests increased, coinciding with surges of COVID-19 cases in California. After the peaks of the COVID-19 crisis subsided, the use of inpatient e-consults persisted at a rate well above the precrisis levels. Conclusions: An inpatient e-consult service was successfully implemented, resulting in fewer unnecessary face-to-face consultations and significant reductions in the response times for consults requested on patients who are hospitalized and do not require an in-person evaluation. Thus, e-consults provided timely, efficient delivery of inpatient consultation services for appropriate problems while minimizing the risk of direct transmission of the COVID-19 virus between health care providers and patients. The service also demonstrated its value as a tool for effective inpatient care coordination beyond the peaks of the pandemic leading to the sustainability of service and value. %M 38754103 %R 10.2196/55623 %U https://www.jmir.org/2024/1/e55623 %U https://doi.org/10.2196/55623 %U http://www.ncbi.nlm.nih.gov/pubmed/38754103 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e54043 %T Grocery Delivery to Support Individuals With Type 2 Diabetes: Protocol for a Pilot Quality Improvement Program %A Oshman,Lauren %A Waselewski,Marika %A Hisamatsu,Rina %A Kim,Noa %A Young,Larrea %A Hafez Griauzde,Dina %A Chang,Tammy %+ Department of Family Medicine, University of Michigan, 2800 Plymouth Road, Building 14, Room G128, Ann Arbor, MI, 48109, United States, 1 7347304636, tachang@med.umich.edu %K T2D %K type 2 diabetes %K food insecurity %K low carbohydrate %K quality improvement %K healthy eating %K grocery %K delivery program %K diabetes %K T2DM %K type 2 diabetes mellitus %K low-income %K US %K United States %K adults %K adult %K low diet quality %K carbohydrate %K carbohydrates %K glycemic control %K nutrition education %D 2024 %7 15.5.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: People with low income are disproportionately affected by type 2 diabetes (T2D), and 17.6% of US adults with T2D experience food insecurity and low diet quality. Low-carbohydrate eating plans can improve glycemic control, promote weight loss, and are associated with improved cardiometabolic health and all-cause mortality. Little is known about supporting low-carbohydrate eating for people with T2D, although food-as-medicine interventions paired with nutrition education offer a promising solution. Objective: This program aims to support the initiation of dietary changes by using grocery delivery and low-carbohydrate education to increase the quality of low-carbohydrate nutrition among people with T2D and food insecurity. Methods: This program was a nonrandomized pilot conducted at 21 primary care practices in Michigan. Adults with T2D and food insecurity or low income were eligible to enroll. Patients were referred by primary care clinic staff. All participants received the 3-month program, which included monthly US $80 credits for healthy foods, free grocery delivery from Shipt, and low-carbohydrate nutrition education. Food credits were restricted to the purchase of healthy foods. Education materials, developed in collaboration with providers and patients, included print, digital, interactive web, and video formats. At enrollment, participants completed a survey including demographics, diabetes health, diet and physical activity, and diabetes management and knowledge. After the 3-month program, participants completed a survey with repeat assessments of diabetes health, diet and physical activity, and diabetes management and knowledge. Perspectives on participant experience and perceived program impact, food purchasing behaviors, and use of educational materials were also collected. Diabetes health information was supplemented with data from participant medical records. We plan to perform mixed methods analysis to assess program feasibility, acceptability, and impact. Primary quality improvement (QI) measures are the number of patients referred and enrolled, use of US $80 food credits, analysis of food purchasing behavior, participant experience with the program, and program costs. Secondary QI measures include changes in hemoglobin A1c, weight, medications, self-efficacy, diabetes and carbohydrate knowledge, and activity between baseline and follow-up. Results: This program started in October 2022. Data collection is expected to be concluded in June 2024. A total of 151 patients were referred to the program, and 83 (55%) were enrolled. The average age was 57 (SD 13; range 18-86) years, 72% (57/79) were female, 90% (70/78) were White, and 96% (74/77) were of non-Hispanic ethnicity. All participants successfully ordered grocery delivery during the program. Conclusions: This pilot QI program aimed to improve diet quality among people with T2D and food insecurity by using grocery delivery and low-carbohydrate nutrition education. Our findings may help inform the implementation of future QI programs and research studies on food-as-medicine interventions that include grocery delivery and education for people with T2D. International Registered Report Identifier (IRRID): DERR1-10.2196/54043 %M 38748461 %R 10.2196/54043 %U https://www.researchprotocols.org/2024/1/e54043 %U https://doi.org/10.2196/54043 %U http://www.ncbi.nlm.nih.gov/pubmed/38748461 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e51514 %T Suitability of the Current Health Technology Assessment of Innovative Artificial Intelligence-Based Medical Devices: Scoping Literature Review %A Farah,Line %A Borget,Isabelle %A Martelli,Nicolas %A Vallee,Alexandre %+ Innovation Center for Medical Devices Department, Foch Hospital, 40 rue Worth, Suresnes, 92150, France, 33 952329655, line.farah1@gmail.com %K artificial intelligence %K machine learning %K health technology assessment %K medical devices %K evaluation %D 2024 %7 13.5.2024 %9 Review %J J Med Internet Res %G English %X Background: Artificial intelligence (AI)–based medical devices have garnered attention due to their ability to revolutionize medicine. Their health technology assessment framework is lacking. Objective: This study aims to analyze the suitability of each health technology assessment (HTA) domain for the assessment of AI-based medical devices. Methods: We conducted a scoping literature review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. We searched databases (PubMed, Embase, and Cochrane Library), gray literature, and HTA agency websites. Results: A total of 10.1% (78/775) of the references were included. Data quality and integration are vital aspects to consider when describing and assessing the technical characteristics of AI-based medical devices during an HTA process. When it comes to implementing specialized HTA for AI-based medical devices, several practical challenges and potential barriers could be highlighted and should be taken into account (AI technological evolution timeline, data requirements, complexity and transparency, clinical validation and safety requirements, regulatory and ethical considerations, and economic evaluation). Conclusions: The adaptation of the HTA process through a methodological framework for AI-based medical devices enhances the comparability of results across different evaluations and jurisdictions. By defining the necessary expertise, the framework supports the development of a skilled workforce capable of conducting robust and reliable HTAs of AI-based medical devices. A comprehensive adapted HTA framework for AI-based medical devices can provide valuable insights into the effectiveness, cost-effectiveness, and societal impact of AI-based medical devices, guiding their responsible implementation and maximizing their benefits for patients and health care systems. %M 38739911 %R 10.2196/51514 %U https://www.jmir.org/2024/1/e51514 %U https://doi.org/10.2196/51514 %U http://www.ncbi.nlm.nih.gov/pubmed/38739911 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e52397 %T Patient and Provider Perspectives About the Use of Patient-Generated Health Data During Pregnancy: Qualitative Exploratory Study %A MacEwan,Sarah R %A Olvera,Ramona G %A Jonnalagadda,Pallavi %A Fareed,Naleef %A McAlearney,Ann Scheck %+ Division of General Internal Medicine, College of Medicine, The Ohio State University, 700 Ackerman Rd, Suite 4100, Columbus, OH, 43202, United States, 1 614 293 0164, Sarah.MacEwan@osumc.edu %K patient-generated health data %K patient-centered care %K obstetrics %K postpartum period %K qualitative methods %D 2024 %7 8.5.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: There is increasing interest in using patient-generated health data (PGHD) to improve patient-centered care during pregnancy. However, little research has examined the perspectives of patients and providers as they report, collect, and use PGHD to inform obstetric care. Objective: This study aims to explore the perspectives of patients and providers about the use of PGHD during pregnancy, including the benefits and challenges of reporting, collecting, and using these data, as well as considerations for expanding the use of PGHD to improve obstetric care. Methods: We conducted one-on-one interviews with 30 pregnant or postpartum patients and 14 health care providers from 2 obstetrics clinics associated with an academic medical center. Semistructured interview guides included questions for patients about their experience and preferences for sharing PGHD and questions for providers about current processes for collecting PGHD, opportunities to improve or expand the collection of PGHD, and challenges faced when collecting and using this information. Interviews were conducted by phone or videoconference and were audio recorded, transcribed verbatim, and deidentified. Interview transcripts were analyzed deductively and inductively to characterize and explore themes in the data. Results: Patients and providers described how PGHD, including physiologic measurements and experience of symptoms, were currently collected during and between in-person clinic visits for obstetric care. Both patients and providers reported positive perceptions about the collection and use of PGHD during pregnancy. Reported benefits of collecting PGHD included the potential to use data to directly inform patient care (eg, identify issues and adjust medication) and to encourage ongoing patient involvement in their care (eg, increase patient attention to their health). Patients and providers had suggestions for expanding the collection and use of PGHD during pregnancy, and providers also shared considerations about strategies that could be used to expand PGHD collection and use. These strategies included considering the roles of both patients and providers in reporting and interpreting PGHD. Providers also noted the need to consider the unintended consequences of using PGHD that should be anticipated and addressed. Conclusions: Acknowledging the challenges, suggestions, and considerations voiced by patients and providers can inform the development and implementation of strategies to effectively collect and use PGHD to support patient-centered care during pregnancy. %M 38718395 %R 10.2196/52397 %U https://formative.jmir.org/2024/1/e52397 %U https://doi.org/10.2196/52397 %U http://www.ncbi.nlm.nih.gov/pubmed/38718395 %0 Journal Article %@ 2152-7202 %I JMIR Publications %V 16 %N %P e50092 %T The Effect of Using a Client-Accessible Health Record on Perceived Quality of Care: Interview Study Among Parents and Adolescents %A Benjamins,Janine %A de Vet,Emely %A de Mortier,Chloe A %A Haveman-Nies,Annemien %+ Stichting Jeugd Noord Veluwe, Stationsplein 18E, Nunspeet, 8071 CH, Netherlands, 31 612329494, j.benjamins@cjgnoordveluwe.nl %K electronic health record %K EHR %K personal health record %K child health services %K child health %K child welfare %K adolescent health services %K pediatrics %K parent %K care quality %K perceived quality of care %K patient experience %K client perception %K quality of care %K parent %K adolescent %K patient portal %K client portal %K qualitative study %D 2024 %7 23.4.2024 %9 Original Paper %J J Particip Med %G English %X Background: Patient-accessible electronic health records (PAEHRs) are assumed to enhance the quality of care, expressed in terms of safety, effectiveness, timeliness, person centeredness, efficiency, and equity. However, research on the impact of PAEHRs on the perceived quality of care among parents, children, and adolescents is largely lacking. In the Netherlands, a PAEHR (Iuvenelis) was developed for preventive child health care and youth care. Parents and adolescents had access to its full content, could manage appointments, ask questions, and comment on written reports. Objective: This study aims to assess whether and how using this PAEHR contributes to perceived quality of care from a client’s perspective. Methods: We chose a qualitative design with a phenomenological approach to explore how parents and adolescents perceived the impact of using a PAEHR on quality of care. In-depth interviews that simultaneously included 1 to 3 people were conducted in 2021. In total, 20 participants were included in the study, representing parents and adolescents, both sexes, different educational levels, different native countries, and all participating municipalities. Within this group, 7 of 13 (54%) parents had not previously been informed about the existence of a client portal. Their expectations of using the client portal, in relation to quality of care, were discussed after a demonstration of the portal. Results: Parents and adolescents perceived that using Iuvenelis contributed to the quality of care because they felt better informed and more involved in the care process than before the introduction of Iuvenelis. Moreover, they experienced more control over their health data, faster and simpler access to their health information, and found it easier to manage appointments or ask questions at their convenience. Parents from a migratory background, among whom 6 of 7 (86%) had not previously been informed about the portal, expected that portal access would enhance their understanding of and control over their care processes. The parents expressed concerns about equity because parents from a migratory background might have less access to the service. Nevertheless, portal usability was regarded as high. Furthermore, both parents and adolescents saw room for improvement in the broader interdisciplinary use of Iuvenelis and the quality of reporting. Conclusions: Using Iuvenelis can contribute to the client-experienced quality of care, more specifically to perceived person centeredness, timeliness, safety, efficiency, and integration of care. However, some quality aspects, such as equity, still need addressing. In general, client information about the portal needs to be improved, specifically focusing on people in vulnerable circumstances, such as those from migratory backgrounds. In addition, to maximize the potential benefit of using Iuvenelis, stimulating a person-centered attitude among professionals is important. Considering the small number of adolescent participants (n=7), adding quantitative data from a structured survey could strengthen the available evidence. %M 38652532 %R 10.2196/50092 %U https://jopm.jmir.org/2024/1/e50092 %U https://doi.org/10.2196/50092 %U http://www.ncbi.nlm.nih.gov/pubmed/38652532 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e53362 %T Needs and Experiences With Health Care Providers of Adult Rare Disease Patients and Caregivers of People With Rare Diseases: Protocol for a Qualitative Study %A Černe,Tina %A Turk,Eva %A Mirosevic,Spela %A Rotar Pavlič,Danica %+ Deparment of Family Medicine, Univeristy of Ljubljana, Poljanski nasip 58, Ljubljana, 1000, Slovenia, 386 041920083, tina.cerne@mf.uni-lj.si %K rare diseases %K patients %K caregivers %K needs %K barriers %K access to health care %D 2024 %7 22.4.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: Rare diseases in Europe are defined as diseases with a prevalence of less than 5 per 10,000 people. Despite their individual rarity, the total number of rare diseases is considerable. Rare diseases are often chronic and complex, affecting physical, mental, and neurological health. People with rare diseases face challenges such as delayed diagnosis, limited medical support, and financial burden. Caregivers, usually family members, bear significant physical and emotional burdens. Understanding the experiences of patients with rare disease and their caregivers is critical to effective care, but this is still underresearched. Better support and understanding of the challenges faced by both patients and caregivers is clearly needed. Our study will explore the experiences and needs of people with rare diseases and caregivers of people with rare diseases in relation to accessing health services. Objective: This study aims to explore the experiences of patients with rare disease and their caregivers with Slovenian health care providers and to create a theoretical model of needs and experiences. Methods: This is a qualitative thematic analysis study, using the codebook approach. The study will conduct semi–open-ended interviews to understand the experiences and needs of people with rare diseases and caregivers of people with rare diseases in relation to accessing health services. The interview questions will be based on an extensive literature review. Data from the interviews will be analyzed using thematic analysis to identify patterns and build a thematic map. Data will be analyzed by at least 2 coders. To ensure reliability, respondent validation will be conducted and negative cases investigated. Any discrepancies will be resolved by consulting the entire research team until a consensus is reached. Results: This study was not specifically funded. However, author TČ is supported by grant number P3-0339 from the Slovenian Agency for Research and Innovation. This study was approved by the Medical Ethics Committee of the Republic of Slovenia (0120-47/2022/3), and recruitment is expected to begin in May 2024, with data analysis results anticipated by the end of 2025. Conclusions: This study will fill an important research gap in Slovenia by exploring the needs and experiences of people living with rare diseases and their caregivers. The results will contribute to the broader field of rare diseases and add knowledge that can inform future research processes and intervention strategies. It also aims to identify neglected areas that have a significant impact on the lives of people with rare diseases. This study is important not only because it addresses the immediate needs of the Slovenian rare disease community, but also because it contributes to a discussion on patient-centered care, health policy design, and the inclusion of psychosocial components in health care. International Registered Report Identifier (IRRID): PRR1-10.2196/53362 %M 38648088 %R 10.2196/53362 %U https://www.researchprotocols.org/2024/1/e53362 %U https://doi.org/10.2196/53362 %U http://www.ncbi.nlm.nih.gov/pubmed/38648088 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e47125 %T Evaluating Algorithmic Bias in 30-Day Hospital Readmission Models: Retrospective Analysis %A Wang,H Echo %A Weiner,Jonathan P %A Saria,Suchi %A Kharrazi,Hadi %+ Bloomberg School of Public Health, Johns Hopkins University, 624 N Broadway, Hampton House, Baltimore, MD, United States, 1 443 287 8264, kharrazi@jhu.edu %K algorithmic bias %K model bias %K predictive models %K model fairness %K health disparity %K hospital readmission %K retrospective analysis %D 2024 %7 18.4.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: The adoption of predictive algorithms in health care comes with the potential for algorithmic bias, which could exacerbate existing disparities. Fairness metrics have been proposed to measure algorithmic bias, but their application to real-world tasks is limited. Objective: This study aims to evaluate the algorithmic bias associated with the application of common 30-day hospital readmission models and assess the usefulness and interpretability of selected fairness metrics. Methods: We used 10.6 million adult inpatient discharges from Maryland and Florida from 2016 to 2019 in this retrospective study. Models predicting 30-day hospital readmissions were evaluated: LACE Index, modified HOSPITAL score, and modified Centers for Medicare & Medicaid Services (CMS) readmission measure, which were applied as-is (using existing coefficients) and retrained (recalibrated with 50% of the data). Predictive performances and bias measures were evaluated for all, between Black and White populations, and between low- and other-income groups. Bias measures included the parity of false negative rate (FNR), false positive rate (FPR), 0-1 loss, and generalized entropy index. Racial bias represented by FNR and FPR differences was stratified to explore shifts in algorithmic bias in different populations. Results: The retrained CMS model demonstrated the best predictive performance (area under the curve: 0.74 in Maryland and 0.68-0.70 in Florida), and the modified HOSPITAL score demonstrated the best calibration (Brier score: 0.16-0.19 in Maryland and 0.19-0.21 in Florida). Calibration was better in White (compared to Black) populations and other-income (compared to low-income) groups, and the area under the curve was higher or similar in the Black (compared to White) populations. The retrained CMS and modified HOSPITAL score had the lowest racial and income bias in Maryland. In Florida, both of these models overall had the lowest income bias and the modified HOSPITAL score showed the lowest racial bias. In both states, the White and higher-income populations showed a higher FNR, while the Black and low-income populations resulted in a higher FPR and a higher 0-1 loss. When stratified by hospital and population composition, these models demonstrated heterogeneous algorithmic bias in different contexts and populations. Conclusions: Caution must be taken when interpreting fairness measures’ face value. A higher FNR or FPR could potentially reflect missed opportunities or wasted resources, but these measures could also reflect health care use patterns and gaps in care. Simply relying on the statistical notions of bias could obscure or underplay the causes of health disparity. The imperfect health data, analytic frameworks, and the underlying health systems must be carefully considered. Fairness measures can serve as a useful routine assessment to detect disparate model performances but are insufficient to inform mechanisms or policy changes. However, such an assessment is an important first step toward data-driven improvement to address existing health disparities. %M 38422347 %R 10.2196/47125 %U https://www.jmir.org/2024/1/e47125 %U https://doi.org/10.2196/47125 %U http://www.ncbi.nlm.nih.gov/pubmed/38422347 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 11 %N %P e46698 %T Usability of an Automated System for Real-Time Monitoring of Shared Decision-Making for Surgery: Mixed Methods Evaluation %A Hoffmann,Christin %A Avery,Kerry %A Macefield,Rhiannon %A Dvořák,Tadeáš %A Snelgrove,Val %A Blazeby,Jane %A Hopkins,Della %A Hickey,Shireen %A Gibbison,Ben %A Rooshenas,Leila %A Williams,Adam %A Aning,Jonathan %A Bekker,Hilary L %A McNair,Angus GK %A , %+ National Institute for Health and Care Research Bristol Biomedical Research Centre, Bristol Centre for Surgical Research, Bristol Medical School: Population Health Sciences, University of Bristol, Canynge Hall, 39 Whatley Road, Bristol, BS8 2PS, United Kingdom, 44 117 455 5993, c.hoffmann@bristol.ac.uk %K surgery %K shared decision-making %K patient participation %K mixed methods %K surgery %K real-time measurement %K patient-reported measure %K electronic data collection %K usability %K data collection %K patient reported %K satisfaction %K mobile phone %D 2024 %7 10.4.2024 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Improving shared decision-making (SDM) for patients has become a health policy priority in many countries. Achieving high-quality SDM is particularly important for approximately 313 million surgical treatment decisions patients make globally every year. Large-scale monitoring of surgical patients’ experience of SDM in real time is needed to identify the failings of SDM before surgery is performed. We developed a novel approach to automating real-time data collection using an electronic measurement system to address this. Examining usability will facilitate its optimization and wider implementation to inform interventions aimed at improving SDM. Objective: This study examined the usability of an electronic real-time measurement system to monitor surgical patients’ experience of SDM. We aimed to evaluate the metrics and indicators relevant to system effectiveness, system efficiency, and user satisfaction. Methods: We performed a mixed methods usability evaluation using multiple participant cohorts. The measurement system was implemented in a large UK hospital to measure patients’ experience of SDM electronically before surgery using 2 validated measures (CollaboRATE and SDM-Q-9). Quantitative data (collected between April 1 and December 31, 2021) provided measurement system metrics to assess system effectiveness and efficiency. We included adult patients booked for urgent and elective surgery across 7 specialties and excluded patients without the capacity to consent for medical procedures, those without access to an internet-enabled device, and those undergoing emergency or endoscopic procedures. Additional groups of service users (group 1: public members who had not engaged with the system; group 2: a subset of patients who completed the measurement system) completed user-testing sessions and semistructured interviews to assess system effectiveness and user satisfaction. We conducted quantitative data analysis using descriptive statistics and calculated the task completion rate and survey response rate (system effectiveness) as well as the task completion time, task efficiency, and relative efficiency (system efficiency). Qualitative thematic analysis identified indicators of and barriers to good usability (user satisfaction). Results: A total of 2254 completed surveys were returned to the measurement system. A total of 25 service users (group 1: n=9; group 2: n=16) participated in user-testing sessions and interviews. The task completion rate was high (169/171, 98.8%) and the survey response rate was good (2254/5794, 38.9%). The median task completion time was 3 (IQR 2-13) minutes, suggesting good system efficiency and effectiveness. The qualitative findings emphasized good user satisfaction. The identified themes suggested that the measurement system is acceptable, easy to use, and easy to access. Service users identified potential barriers and solutions to acceptability and ease of access. Conclusions: A mixed methods evaluation of an electronic measurement system for automated, real-time monitoring of patients’ experience of SDM showed that usability among patients was high. Future pilot work will optimize the system for wider implementation to ultimately inform intervention development to improve SDM. International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2023-079155 %M 38598276 %R 10.2196/46698 %U https://humanfactors.jmir.org/2024/1/e46698 %U https://doi.org/10.2196/46698 %U http://www.ncbi.nlm.nih.gov/pubmed/38598276 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e54002 %T The Use of Medical Services for Low-Acuity Emergency Cases in Germany: Protocol for a Multicenter Observational Pilot Study %A Nau,Lara Maria %A Laux,Gunter %A Altiner,Attila %A Szecsenyi,Joachim %A Leutgeb,Rüdiger %+ Department of General Practice and Health Services Research, University of Heidelberg, Im Neuenheimer Feld 130, Heidelberg, 69120, Germany, 49 622156310446, ruediger.leutgeb@med.uni-heidelberg.de %K emergency medical service %K EMS %K ambulance misuse %K low-acuity calls %K emergency department %K paramedics %K rescue operations %D 2024 %7 10.4.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: The increasing number of requests for help for acutely ill patients and their management is a major problem in the health systems of many countries, but especially in Germany. Rescue coordination centers and ambulances in Germany are increasingly overloaded. As a result, rides as a part of rescue operations have been increasing in length for years, yet a relevant proportion of these operations represent low-acuity calls (LACs). The basic objective of this pilot study is the quantitative analysis of the potential misuse of requests to the rescue control center. Indications for alternative treatment options and how to handle these treatment options in nonacute, non–life-threatening health conditions, such as minor injuries or minor infectious diseases, will be assessed. The identification of these LACs is vital in order to prevent health care resources in emergency medical care becoming inadequate. Objective: The overarching goal of this study is to determine the percentage of unnecessary rescue missions on site and subsequently to obtain an impression of the paramedics’ assessment of alternative treatment options or alternative methods of rescue transportation. Methods: This will be an exploratory, noninterventional, cross-sectional study with a quantitative approach. The study is multicentric, with 21 ambulances in 12 different locations. The data for this study were collected via a questionnaire, newly developed for this study, for rescue personnel. Additionally, secondary data from the responsible control center will be linked and processed in an initial descriptive analysis. This descriptive analysis will form the basis for a subsequent variance analysis. Results: Data collection started as projected on September 18, 2023, and was ongoing until end of November 2023. We expect the documentation of several thousand rescue operations. We expect the following study results: (1) many unnecessary rescue operations, (2) immediate on-site assessment of correct care and treatment, and (3) patients’ reasons for calling a rescue coordination center. Conclusions: To our knowledge, this is the first observational study in which acute rescue operations are recorded on site. The focus of this study is on the trained paramedics’ assessment of whether rescue operations are necessary or not. Additionally, alternative treatments, such as out-of-hours care service or primary care service, are shown for each individual case. The study also intends to cover the question of which factors are relevant and statistically significantly connected to the misuse of ambulances. Trial Registration: German Register for Clinical Studies (Deutsches Register für Klinische Studien) DRKS00032510; https://drks.de/search/en/trial/DRKS00032510 International Registered Report Identifier (IRRID): DERR1-10.2196/54002 %M 38598281 %R 10.2196/54002 %U https://www.researchprotocols.org/2024/1/e54002 %U https://doi.org/10.2196/54002 %U http://www.ncbi.nlm.nih.gov/pubmed/38598281 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e54278 %T Effect of Performance-Based Nonfinancial Incentives on Data Quality in Individual Medical Records of Institutional Births: Quasi-Experimental Study %A Taye,Biniam Kefiyalew %A Gezie,Lemma Derseh %A Atnafu,Asmamaw %A Mengiste,Shegaw Anagaw %A Kaasbøll,Jens %A Gullslett,Monika Knudsen %A Tilahun,Binyam %+ Ministry of Health, The Federal Democratic Republic of Ethiopia, Zambia street, Addis Ababa, Ethiopia, 251 910055867, bini.bhi2013@gmail.com %K individual medical records %K data quality %K completeness %K consistency %K nonfinancial incentives %K institutional birth %K health care quality %K quasi-experimental design %K Ethiopia %D 2024 %7 5.4.2024 %9 Original Paper %J JMIR Med Inform %G English %X Background: Despite the potential of routine health information systems in tackling persistent maternal deaths stemming from poor service quality at health facilities during and around childbirth, research has demonstrated their suboptimal performance, evident from the incomplete and inaccurate data unfit for practical use. There is a consensus that nonfinancial incentives can enhance health care providers’ commitment toward achieving the desired health care quality. However, there is limited evidence regarding the effectiveness of nonfinancial incentives in improving the data quality of institutional birth services in Ethiopia. Objective: This study aimed to evaluate the effect of performance-based nonfinancial incentives on the completeness and consistency of data in the individual medical records of women who availed institutional birth services in northwest Ethiopia. Methods: We used a quasi-experimental design with a comparator group in the pre-post period, using a sample of 1969 women’s medical records. The study was conducted in the “Wegera” and “Tach-armacheho” districts, which served as the intervention and comparator districts, respectively. The intervention comprised a multicomponent nonfinancial incentive, including smartphones, flash disks, power banks, certificates, and scholarships. Personal records of women who gave birth within 6 months before (April to September 2020) and after (February to July 2021) the intervention were included. Three distinct women’s birth records were examined: the integrated card, integrated individual folder, and delivery register. The completeness of the data was determined by examining the presence of data elements, whereas the consistency check involved evaluating the agreement of data elements among women’s birth records. The average treatment effect on the treated (ATET), with 95% CIs, was computed using a difference-in-differences model. Results: In the intervention district, data completeness in women’s personal records was nearly 4 times higher (ATET 3.8, 95% CI 2.2-5.5; P=.02), and consistency was approximately 12 times more likely (ATET 11.6, 95% CI 4.18-19; P=.03) than in the comparator district. Conclusions: This study indicates that performance-based nonfinancial incentives enhance data quality in the personal records of institutional births. Health care planners can adapt these incentives to improve the data quality of comparable medical records, particularly pregnancy-related data within health care facilities. Future research is needed to assess the effectiveness of nonfinancial incentives across diverse contexts to support successful scale-up. %M 38578684 %R 10.2196/54278 %U https://medinform.jmir.org/2024/1/e54278 %U https://doi.org/10.2196/54278 %U http://www.ncbi.nlm.nih.gov/pubmed/38578684 %0 Journal Article %@ 2291-9694 %I %V 12 %N %P e51171 %T Scalable Approach to Consumer Wearable Postmarket Surveillance: Development and Validation Study %A Yoo,Richard M %A Viggiano,Ben T %A Pundi,Krishna N %A Fries,Jason A %A Zahedivash,Aydin %A Podchiyska,Tanya %A Din,Natasha %A Shah,Nigam H %K consumer wearable devices %K atrial fibrillation %K postmarket surveillance %K surveillance %K monitoring %K artificial intelligence %K machine learning %K natural language processing %K NLP %K wearable %K wearables %K labeler %K heart %K cardiology %K arrhythmia %K diagnose %K diagnosis %K labeling %K classifier %K EHR %K electronic health record %K electronic health records %K consumer %K consumers %K device %K devices %K evaluation %D 2024 %7 4.4.2024 %9 %J JMIR Med Inform %G English %X Background: With the capability to render prediagnoses, consumer wearables have the potential to affect subsequent diagnoses and the level of care in the health care delivery setting. Despite this, postmarket surveillance of consumer wearables has been hindered by the lack of codified terms in electronic health records (EHRs) to capture wearable use. Objective: We sought to develop a weak supervision–based approach to demonstrate the feasibility and efficacy of EHR-based postmarket surveillance on consumer wearables that render atrial fibrillation (AF) prediagnoses. Methods: We applied data programming, where labeling heuristics are expressed as code-based labeling functions, to detect incidents of AF prediagnoses. A labeler model was then derived from the predictions of the labeling functions using the Snorkel framework. The labeler model was applied to clinical notes to probabilistically label them, and the labeled notes were then used as a training set to fine-tune a classifier called Clinical-Longformer. The resulting classifier identified patients with an AF prediagnosis. A retrospective cohort study was conducted, where the baseline characteristics and subsequent care patterns of patients identified by the classifier were compared against those who did not receive a prediagnosis. Results: The labeler model derived from the labeling functions showed high accuracy (0.92; F1-score=0.77) on the training set. The classifier trained on the probabilistically labeled notes accurately identified patients with an AF prediagnosis (0.95; F1-score=0.83). The cohort study conducted using the constructed system carried enough statistical power to verify the key findings of the Apple Heart Study, which enrolled a much larger number of participants, where patients who received a prediagnosis tended to be older, male, and White with higher CHA2DS2-VASc (congestive heart failure, hypertension, age ≥75 years, diabetes, stroke, vascular disease, age 65-74 years, sex category) scores (P<.001). We also made a novel discovery that patients with a prediagnosis were more likely to use anticoagulants (525/1037, 50.63% vs 5936/16,560, 35.85%) and have an eventual AF diagnosis (305/1037, 29.41% vs 262/16,560, 1.58%). At the index diagnosis, the existence of a prediagnosis did not distinguish patients based on clinical characteristics, but did correlate with anticoagulant prescription (P=.004 for apixaban and P=.01 for rivaroxaban). Conclusions: Our work establishes the feasibility and efficacy of an EHR-based surveillance system for consumer wearables that render AF prediagnoses. Further work is necessary to generalize these findings for patient populations at other sites. %R 10.2196/51171 %U https://medinform.jmir.org/2024/1/e51171 %U https://doi.org/10.2196/51171 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e54330 %T Impacts of an Acute Care Telenursing Program on Discharge, Patient Experience, and Nursing Experience: Retrospective Cohort Comparison Study %A Bruce,Courtenay R %A Klahn,Steve %A Randle,Lindsay %A Li,Xin %A Sayali,Kelkar %A Johnson,Barbara %A Gomez,Melissa %A Howard,Meagan %A Schwartz,Roberta %A Sasangohar,Farzan %+ Houston Methodist, 8100 Greenbriar Drive, Houston, TX, 77030, United States, 1 281 620 9040, crbruce@houstonmethodist.org %K telenursing %K telemedicine %K patient discharge %K health personnel %K surveys and questionnaires %K patient outcome assessment %D 2024 %7 4.4.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Despite widespread growth of televisits and telemedicine, it is unclear how telenursing could be applied to augment nurse labor and support nursing. Objective: This study evaluated a large-scale acute care telenurse (ACTN) program to support web-based admission and discharge processes for hospitalized patients. Methods: A retrospective, observational cohort comparison was performed in a large academic hospital system (approximately 2100 beds) in Houston, Texas, comparing patients in our pilot units for the ACTN program (telenursing cohort) between June 15, 2022, and December 31, 2022, with patients who did not participate (nontelenursing cohort) in the same units and timeframe. We used a case mix index analysis to confirm comparable patient cases between groups. The outcomes investigated were patient experience, measured using the Hospital Consumer Assessment of Health Care Providers and Systems (HCAHCPS) survey; nursing experience, measured by a web-based questionnaire with quantitative multiple-choice and qualitative open-ended questions; time of discharge during the day (from electronic health record data); and duration of discharge education processes. Results: Case mix index analysis found no significant case differences between cohorts (P=.75). For the first 4 units that rolled out in phase 1, all units experienced improvement in at least 4 and up to 7 HCAHCPS domains. Scores for “communication with doctors” and “would recommend hospital” were improved significantly (P=.03 and P=.04, respectively) in 1 unit in phase 1. The impact of telenursing in phases 2 and 3 was mixed. However, “communication with doctors” was significantly improved in 2 units (P=.049 and P=.002), and the overall rating of the hospital and the ”would recommend hospital” scores were significantly improved in 1 unit (P=.02 and P=04, respectively). Of 289 nurses who were invited to participate in the survey, 106 completed the nursing experience survey (response rate 106/289, 36.7%). Of the 106 nurses, 101 (95.3%) indicated that the ACTN program was very helpful or somewhat helpful to them as bedside nurses. The only noticeable difference between the telenursing and nontelenursing cohorts for the time of day discharge was a shift in the volume of patients discharged before 2 PM compared to those discharged after 2 PM at a hospital-wide level. The ACTN admissions averaged 12 minutes and 6 seconds (SD 7 min and 29 s), and the discharges averaged 14 minutes and 51 seconds (SD 8 min and 10 s). The average duration for ACTN calls was 13 minutes and 17 seconds (SD 7 min and 52 s). Traditional cohort standard practice (nontelenursing cohort) of a bedside nurse engaging in discharge and admission processes was 45 minutes, consistent with our preimplementation time study. Conclusions: This study shows that ACTN programs are feasible and associated with improved outcomes for patient and nursing experience and reducing time allocated to admission and discharge education. %M 38573753 %R 10.2196/54330 %U https://www.jmir.org/2024/1/e54330 %U https://doi.org/10.2196/54330 %U http://www.ncbi.nlm.nih.gov/pubmed/38573753 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e49643 %T Data-Driven Identification of Factors That Influence the Quality of Adverse Event Reports: 15-Year Interpretable Machine Learning and Time-Series Analyses of VigiBase and QUEST %A Choo,Sim Mei %A Sartori,Daniele %A Lee,Sing Chet %A Yang,Hsuan-Chia %A Syed-Abdul,Shabbir %+ Graduate Institute of Biomedical Informatics, Taipei Medical University, 301 Yuantong Rd, , Taipei, 235, Taiwan, 886 66202589 ext 10930, drshabbir@tmu.edu.tw %K pharmacovigilance %K medication safety %K big data analysis %K feature selection %K interpretable machine learning %D 2024 %7 3.4.2024 %9 Original Paper %J JMIR Med Inform %G English %X Background: The completeness of adverse event (AE) reports, crucial for assessing putative causal relationships, is measured using the vigiGrade completeness score in VigiBase, the World Health Organization global database of reported potential AEs. Malaysian reports have surpassed the global average score (approximately 0.44), achieving a 5-year average of 0.79 (SD 0.23) as of 2019 and approaching the benchmark for well-documented reports (0.80). However, the contributing factors to this relatively high report completeness score remain unexplored. Objective: This study aims to explore the main drivers influencing the completeness of Malaysian AE reports in VigiBase over a 15-year period using vigiGrade. A secondary objective was to understand the strategic measures taken by the Malaysian authorities leading to enhanced report completeness across different time frames. Methods: We analyzed 132,738 Malaysian reports (2005-2019) recorded in VigiBase up to February 2021 split into historical International Drug Information System (INTDIS; n=63,943, 48.17% in 2005-2016) and newer E2B (n=68,795, 51.83% in 2015-2019) format subsets. For machine learning analyses, we performed a 2-stage feature selection followed by a random forest classifier to identify the top features predicting well-documented reports. We subsequently applied tree Shapley additive explanations to examine the magnitude, prevalence, and direction of feature effects. In addition, we conducted time-series analyses to evaluate chronological trends and potential influences of key interventions on reporting quality. Results: Among the analyzed reports, 42.84% (56,877/132,738) were well documented, with an increase of 65.37% (53,929/82,497) since 2015. Over two-thirds (46,186/68,795, 67.14%) of the Malaysian E2B reports were well documented compared to INTDIS reports at 16.72% (10,691/63,943). For INTDIS reports, higher pharmacovigilance center staffing was the primary feature positively associated with being well documented. In recent E2B reports, the top positive features included reaction abated upon drug dechallenge, reaction onset or drug use duration of <1 week, dosing interval of <1 day, reports from public specialist hospitals, reports by pharmacists, and reaction duration between 1 and 6 days. In contrast, reports from product registration holders and other health care professionals and reactions involving product substitution issues negatively affected the quality of E2B reports. Multifaceted strategies and interventions comprising policy changes, continuity of education, and human resource development laid the groundwork for AE reporting in Malaysia, whereas advancements in technological infrastructure, pharmacovigilance databases, and reporting tools concurred with increases in both the quantity and quality of AE reports. Conclusions: Through interpretable machine learning and time-series analyses, this study identified key features that positively or negatively influence the completeness of Malaysian AE reports and unveiled how Malaysia has developed its pharmacovigilance capacity via multifaceted strategies and interventions. These findings will guide future work in enhancing pharmacovigilance and public health. %M 38568722 %R 10.2196/49643 %U https://medinform.jmir.org/2024/1/e49643 %U https://doi.org/10.2196/49643 %U http://www.ncbi.nlm.nih.gov/pubmed/38568722 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e54395 %T Telemedicine-Based Risk Program to Prevent Falls Among Older Adults: Protocol for a Randomized Quality Improvement Trial %A Rein,David B %A Hackney,Madeleine E %A Haddad,Yara K %A Sublett,Farah A %A Moreland,Briana %A Imhof,Laurie %A Peterson,Cora %A Legha,Jaswinder K %A Mark,Janice %A Vaughan,Camille P %A Johnson II,Theodore M %A Bergen,Gwen %A , %+ Department of Public Health, NORC at the University of Chicago, 1447 Peachtree St NE #700, Atlanta, GA, 30309, United States, 1 4048230318, rein-david@norc.org %K aging %K cost-effectiveness %K elderly %K fall risk screening %K fall risk %K falls %K medication management %K older adults %K physical therapy %K prevention %K public health %K telemedicine %D 2024 %7 26.3.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: The Center for Disease Control and Prevention’s Stopping Elderly Accidents, Deaths, and Injuries (STEADI) initiative offers health care providers tools and resources to assist with fall risk screening and multifactorial fall risk assessment and interventions. Its effectiveness has never been evaluated in a randomized trial. Objective: This study aims to describe the protocol for the STEADI Options Randomized Quality Improvement Trial (RQIT), which was designed to evaluate the impact on falls and all-cause health expenditures of a telemedicine-based form of STEADI implemented among older adults aged 65 years and older, within a primary care setting. Methods: STEADI Options was a pragmatic RQIT implemented within a health system comparing a telemedicine version of the STEADI fall risk assessment to the standard of care (SOC). Before screening, we randomized all eligible patients in participating clinics into the STEADI arm or SOC arm based on their scheduled provider. All received the Stay Independent screener (SIS) to determine fall risk. Patients were considered at risk for falls if they scored 4 or more on the SIS or answered affirmatively to any 1 of the 3 key questions within the SIS. Patients screened at risk for falls and randomized to the STEADI arm were offered a registered nurse (RN)–led STEADI assessment through telemedicine; the RN provided assessment results and recommendations to the providers, who were advised to discuss fall-prevention strategies with their patients. Patients screened at risk for falls and randomized to the SOC arm were asked to participate in study data collection only. Data on recruitment, STEADI assessments, use of recommended prevention services, medications, and fall occurrences were collected using electronic health records and patient surveys. Using staff time diaries and administrative records, the study prospectively collected data on STEADI implementation costs and all-cause outpatient and inpatient charges incurred over the year following enrollment. Results: The study enrolled 720 patients (n=307, 42.6% STEADI arm; n=353, 49% SOC arm; and n=60, 8.3% discontinued arm) from September 2020 to December 2021. Follow-up data collection was completed in January 2023. As of February 2024, data analysis is complete, and results are expected to be published by the end of 2025. Conclusions: The STEADI RQIT evaluates the impact of a telemedicine-based, STEADI-based fall risk assessment on falls and all-cause health expenditures and can provide information on the intervention’s effectiveness and cost-effectiveness. Trial Registration: ClinicalTrials.gov NCT05390736, http://clinicaltrials.gov/ct2/show/NCT05390736 International Registered Report Identifier (IRRID): RR1-10.2196/54395 %M 38346180 %R 10.2196/54395 %U https://www.researchprotocols.org/2024/1/e54395 %U https://doi.org/10.2196/54395 %U http://www.ncbi.nlm.nih.gov/pubmed/38346180 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e47715 %T The Impact of Digital Hospitals on Patient and Clinician Experience: Systematic Review and Qualitative Evidence Synthesis %A Canfell,Oliver J %A Woods,Leanna %A Meshkat,Yasaman %A Krivit,Jenna %A Gunashanhar,Brinda %A Slade,Christine %A Burton-Jones,Andrew %A Sullivan,Clair %+ Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Level 5 Health Sciences Building, Central, Fig Tree Cres, Brisbane, 4006, Australia, 61 731765530, o.canfell@uq.edu.au %K electronic medical record %K electronic health record %K health care professionals %K patients %K patient satisfaction %K hospitals %K eHealth %K attitude %K perception %K systematic %K digital hospital %K digital hospitals %K experience %K satisfaction %D 2024 %7 11.3.2024 %9 Review %J J Med Internet Res %G English %X Background: The digital transformation of health care is advancing rapidly. A well-accepted framework for health care improvement is the Quadruple Aim: improved clinician experience, improved patient experience, improved population health, and reduced health care costs. Hospitals are attempting to improve care by using digital technologies, but the effectiveness of these technologies is often only measured against cost and quality indicators, and less is known about the clinician and patient experience. Objective: This study aims to conduct a systematic review and qualitative evidence synthesis to assess the clinician and patient experience of digital hospitals. Methods: The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and ENTREQ (Enhancing the Transparency in Reporting the Synthesis of Qualitative Research) guidelines were followed. The PubMed, Embase, Scopus, CINAHL, and PsycINFO databases were searched from January 2010 to June 2022. Studies that explored multidisciplinary clinician or adult inpatient experiences of digital hospitals (with a full electronic medical record) were included. Study quality was assessed using the Mixed Methods Appraisal Tool. Data synthesis was performed narratively for quantitative studies. Qualitative evidence synthesis was performed via (1) automated machine learning text analytics using Leximancer (Leximancer Pty Ltd) and (2) researcher-led inductive synthesis to generate themes. Results: A total of 61 studies (n=39, 64% quantitative; n=15, 25% qualitative; and n=7, 11% mixed methods) were included. Most studies (55/61, 90%) investigated clinician experiences, whereas few (10/61, 16%) investigated patient experiences. The study populations ranged from 8 to 3610 clinicians, 11 to 34,425 patients, and 5 to 2836 hospitals. Quantitative outcomes indicated that clinicians had a positive overall satisfaction (17/24, 71% of the studies) with digital hospitals, and most studies (11/19, 58%) reported a positive sentiment toward usability. Data accessibility was reported positively, whereas adaptation, clinician-patient interaction, and workload burnout were reported negatively. The effects of digital hospitals on patient safety and clinicians’ ability to deliver patient care were mixed. The qualitative evidence synthesis of clinician experience studies (18/61, 30%) generated 7 themes: inefficient digital documentation, inconsistent data quality, disruptions to conventional health care relationships, acceptance, safety versus risk, reliance on hybrid (digital and paper) workflows, and patient data privacy. There was weak evidence of a positive association between digital hospitals and patient satisfaction scores. Conclusions: Clinicians’ experience of digital hospitals appears positive according to high-level indicators (eg, overall satisfaction and data accessibility), but the qualitative evidence synthesis revealed substantive tensions. There is insufficient evidence to draw a definitive conclusion on the patient experience within digital hospitals, but indications appear positive or agnostic. Future research must prioritize equitable investigation and definition of the digital clinician and patient experience to achieve the Quadruple Aim of health care. %M 38466978 %R 10.2196/47715 %U https://www.jmir.org/2024/1/e47715 %U https://doi.org/10.2196/47715 %U http://www.ncbi.nlm.nih.gov/pubmed/38466978 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e51560 %T Frameworks, Dimensions, Definitions of Aspects, and Assessment Methods for the Appraisal of Quality of Health Data for Secondary Use: Comprehensive Overview of Reviews %A Declerck,Jens %A Kalra,Dipak %A Vander Stichele,Robert %A Coorevits,Pascal %+ Department of Public Health and Primary Care, Unit of Medical Informatics and Statistics, Ghent University, Campus UZ-Ghent, Entrance 42, 6th Floor, Corneel Heymanslaan 10, Ghent, 9000, Belgium, 32 93323628, jens.declerck@ugent.be %K data quality %K data quality dimensions %K data quality assessment %K secondary use %K data quality framework %K fit for purpose %D 2024 %7 6.3.2024 %9 Review %J JMIR Med Inform %G English %X Background: Health care has not reached the full potential of the secondary use of health data because of—among other issues—concerns about the quality of the data being used. The shift toward digital health has led to an increase in the volume of health data. However, this increase in quantity has not been matched by a proportional improvement in the quality of health data. Objective: This review aims to offer a comprehensive overview of the existing frameworks for data quality dimensions and assessment methods for the secondary use of health data. In addition, it aims to consolidate the results into a unified framework. Methods: A review of reviews was conducted including reviews describing frameworks of data quality dimensions and their assessment methods, specifically from a secondary use perspective. Reviews were excluded if they were not related to the health care ecosystem, lacked relevant information related to our research objective, and were published in languages other than English. Results: A total of 22 reviews were included, comprising 22 frameworks, with 23 different terms for dimensions, and 62 definitions of dimensions. All dimensions were mapped toward the data quality framework of the European Institute for Innovation through Health Data. In total, 8 reviews mentioned 38 different assessment methods, pertaining to 31 definitions of the dimensions. Conclusions: The findings in this review revealed a lack of consensus in the literature regarding the terminology, definitions, and assessment methods for data quality dimensions. This creates ambiguity and difficulties in developing specific assessment methods. This study goes a step further by assigning all observed definitions to a consolidated framework of 9 data quality dimensions. %M 38446534 %R 10.2196/51560 %U https://medinform.jmir.org/2024/1/e51560 %U https://doi.org/10.2196/51560 %U http://www.ncbi.nlm.nih.gov/pubmed/38446534 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e52766 %T Investigating Digital Patient-Reported Outcome Measures in Patient-Centered Diabetes Specialist Outpatient Care (DigiDiaS): Protocol for a Multimethod Prospective Observational Study %A Torbjørnsen,Astrid %A Spildo,Ingeborg %A Mollestad,Maria Aadland %A Jensen,Annesofie Lunde %A Singstad,Tone %A Weldingh,Nina Mickelson %A Joranger,Pål %A Ribu,Lis %A Holmen,Heidi %+ Department of Nursing and Health Promotion, Faculty of Health Sciences, Oslo Metropolitan University – OsloMet, Postboks 4, St. Olavs plass, Oslo, 0130, Norway, 47 67236199, astridto@oslomet.no %K patient-reported outcome measures %K PROMs %K diabetes mellitus %K DM %K type 1 %K patient acceptance of health care %K telemedicine %K mobile apps %K mobile phone %D 2024 %7 5.3.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: Living with type 1 diabetes is challenging, and to support self-management, repeated consultations in specialist outpatient care are often required. The emergence of new digital solutions has revolutionized how health care services can be patient centered, providing unprecedented opportunities for flexible, high-quality care. However, there is a lack of studies exploring how the use of digital patient-reported outcome measures (PROMs) for flexible specialist care affects diabetes self-management. To provide new knowledge on the relevance of using PROMs in standard care, we have designed a multimethod prospective study. Objective: The overall aim of this protocol is to describe our prospective multimethod observational study designed to investigate digital PROMs in a routine specialist outpatient setting for flexible patient-centered diabetes care (DigiDiaS). Methods: This protocol outlines the design of a multimethod prospective observational cohort study that includes data from electronic health records, self-reported questionnaires, clinical consultation field observations, and individual in-depth interviews with patients and diabetes health care personnel. All patients with type 1 diabetes at a designated outpatient clinic were invited to participate and use the digital PROM implemented in clinical care. Both users and nonusers of the digital PROM were eligible for the prospective study, allowing for a comparison of the two groups. Data were collected at baseline and after 12 months, including self-management as the primary outcome assessed using the Patient Activation Measure, along with the secondary outcomes of digital health literacy, quality of life, health economy, and clinical variables such as glycated hemoglobin. Results: The digital solution was implemented for routine clinical care in the department in November 2021, and data collection for the prospective study started in October 2022. As of September 6, 2023, 84.6% (186/220) of patients among those in the digital PROM and 15.5% (34/220) of patients among the nonusers have consented to participate. We expect the study to have enough participants by the autumn of 2023. With 1 year of follow-up, the results are expected by spring 2025. Conclusions: In conclusion, a multimethod prospective observational cohort study can offer valuable insights into the relevance, effectiveness, and acceptability of digital tools using PROMs in diabetes specialist care. Such knowledge is crucial for achieving broad and successful implementation and use of these tools in a large diabetes outpatient clinic. International Registered Report Identifier (IRRID): DERR1-10.2196/52766 %M 38441955 %R 10.2196/52766 %U https://www.researchprotocols.org/2024/1/e52766 %U https://doi.org/10.2196/52766 %U http://www.ncbi.nlm.nih.gov/pubmed/38441955 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e51153 %T Ethical and Quality of Care-Related Challenges of Digital Health Twins in Older Care Settings: Protocol for a Scoping Review %A Jabin,Md Shafiqur Rahman %A Yaroson,Emillia Vann %A Ilodibe,Adaobi %A Eldabi,Tillal %+ Faculty of Health Studies, University of Bradford, Horton A, Room: 2.10, Richmond Road, Bradford, BD7 1DP, United Kingdom, 44 7915673612, mjabin@bradford.ac.uk %K accessibility %K data security %K effectiveness %K equality %K health equity %K patient safety %K right to privacy %K social care %D 2024 %7 23.2.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: Digital health twins (DHTs) have been evolving with their diverse applications in medicine, specifically in older care settings, with the increasing demands of older adults. DHTs have already contributed to improving the quality of dementia and trauma care, cardiac treatment, and health care services for older individuals. Despite its many benefits, the optimum implementation of DHTs has faced several challenges associated with ethical issues, quality of care, management and leadership, and design considerations in older care settings. Since the need for such care is continuously rising and there is evident potential for DHTs to meet those needs, this review aims to map key concepts to address the gaps in the research knowledge to improve DHT implementation. Objective: The review aims to compile and synthesize the best available evidence regarding the problems encountered by older adults and care providers associated with the application of DHTs. The synthesis will collate the evidence of the issues associated with quality of care, the ethical implications of DHTs, and the strategies undertaken to overcome those challenges in older care settings. Methods: The review will follow the Joanna Briggs Institute (JBI) methodology. The published studies will be searched through CINAHL, MEDLINE, JBI, and Web of Science, and the unpublished studies through Mednar, Trove, OCLC WorldCat, and Dissertations and Theses. Studies published in English from 2002 will be considered. This review will include studies of older individuals (aged 65 years or older) undergoing care delivery associated with DHTs and their respective care providers. The concept will include the application of the technology, and the context will involve studies based on the older care setting. A broad scope of evidence, including quantitative, qualitative, text and opinion studies, will be considered. A total of 2 independent reviewers will screen the titles and abstracts and then review the full text. Data will be extracted from the included studies using a data extraction tool developed for this study. Results: The results will be presented in a PRISMA-ScR (Preferred Reporting Items for Systematic Review and Meta-Analysis extension for Scoping Reviews) flow diagram. A draft charting table will be developed as a data extraction tool. The results will be presented as a “map” of the data in a logical, diagrammatic, or tabular form in a descriptive format. Conclusions: The evidence synthesis is expected to uncover the shreds of evidence required to address the ethical and care quality-related challenges associated with applying DHTs. A synthesis of various strategies used to overcome identified challenges will provide more prospects for adopting them elsewhere and create a resource allocation model for older individuals. International Registered Report Identifier (IRRID): DERR1-10.2196/51153 %M 38393771 %R 10.2196/51153 %U https://www.researchprotocols.org/2024/1/e51153 %U https://doi.org/10.2196/51153 %U http://www.ncbi.nlm.nih.gov/pubmed/38393771 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e46308 %T Timing, Indicators, and Approaches to Digital Patient Experience Evaluation: Umbrella Systematic Review %A Wang,Tingting %A Giunti,Guido %A Goossens,Richard %A Melles,Marijke %+ Department of Human-Centered Design, Faculty of Industrial Design Engineering, Delft University of Technology, Gebouw 32, Landbergstraat 15, Delft, 2628 CE, Netherlands, 31 623018218, t.wang-8@tudelft.nl %K digital health %K eHealth %K telemedicine %K mobile health %K mHealth %K patient experience %K user experience %K evaluation timing %K evaluation indicators %K evaluation approaches %K user-centered design %K patient-centered care %K human-computer interaction %K mobile phone %D 2024 %7 5.2.2024 %9 Review %J J Med Internet Res %G English %X Background: The increasing prevalence of DH applications has outpaced research and practice in digital health (DH) evaluations. Patient experience (PEx) was reported as one of the challenges facing the health system by the World Health Organization. To generate evidence on DH and promote the appropriate integration and use of technologies, a standard evaluation of PEx in DH is required. Objective: This study aims to systematically identify evaluation timing considerations (ie, when to measure), evaluation indicators (ie, what to measure), and evaluation approaches (ie, how to measure) with regard to digital PEx. The overall aim of this study is to generate an evaluation guide for further improving digital PEx evaluation. Methods: This is a 2-phase study parallel to our previous study. In phase 1, literature reviews related to PEx in DH were systematically searched from Scopus, PubMed, and Web of Science databases. Two independent raters conducted 2 rounds of paper screening, including title and abstract screening and full-text screening, and assessed the interrater reliability for 20% (round 1: 23/115 and round 2: 12/58) random samples using the Fleiss-Cohen coefficient (round 1: k1=0.88 and round 2: k2=0.80). When reaching interrater reliability (k>0.60), TW conducted the rest of the screening process, leaving any uncertainties for group discussions. Overall, 38% (45/119) of the articles were considered eligible for further thematic analysis. In phase 2, to check if there were any meaningful novel insights that would change our conclusions, we performed an updated literature search in which we collected 294 newly published reviews, of which 102 (34.7%) were identified as eligible articles. We considered them to have no important changes to our original results on the research objectives. Therefore, they were not integrated into the synthesis of this review and were used as supplementary materials. Results: Our review highlights 5 typical evaluation objectives that serve 5 stakeholder groups separately. We identified a set of key evaluation timing considerations and classified them into 3 categories: intervention maturity stages, timing of the evaluation, and timing of data collection. Information on evaluation indicators of digital PEx was identified and summarized into 3 categories (intervention outputs, patient outcomes, and health care system impact), 9 themes, and 22 subthemes. A set of evaluation theories, common study designs, data collection methods and instruments, and data analysis approaches was captured, which can be used or adapted to evaluate digital PEx. Conclusions: Our findings enabled us to generate an evaluation guide to help DH intervention researchers, designers, developers, and program evaluators evaluate digital PEx. Finally, we propose 6 directions for encouraging further digital PEx evaluation research and practice to address the challenge of poor PEx. %M 38315545 %R 10.2196/46308 %U https://www.jmir.org/2024/1/e46308 %U https://doi.org/10.2196/46308 %U http://www.ncbi.nlm.nih.gov/pubmed/38315545 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e53302 %T Clinical Informatics Team Members’ Perspectives on Health Information Technology Safety After Experiential Learning and Safety Process Development: Qualitative Descriptive Study %A Recsky,Chantelle %A Rush,Kathy L %A MacPhee,Maura %A Stowe,Megan %A Blackburn,Lorraine %A Muniak,Allison %A Currie,Leanne M %+ School of Nursing, University of British Columbia, T201-2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada, 1 604 822 7417, chantelle.recsky@ubc.ca %K informatics %K community health services %K knowledge translation %K qualitative research %K patient safety %D 2024 %7 5.2.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Although intended to support improvement, the rapid adoption and evolution of technologies in health care can also bring about unintended consequences related to safety. In this project, an embedded researcher with expertise in patient safety and clinical education worked with a clinical informatics team to examine safety and harm related to health information technologies (HITs) in primary and community care settings. The clinical informatics team participated in learning activities around relevant topics (eg, human factors, high reliability organizations, and sociotechnical systems) and cocreated a process to address safety events related to technology (ie, safety huddles and sociotechnical analysis of safety events). Objective: This study aimed to explore clinical informaticians’ experiences of incorporating safety practices into their work. Methods: We used a qualitative descriptive design and conducted web-based focus groups with clinical informaticians. Thematic analysis was used to analyze the data. Results: A total of 10 informants participated. Barriers to addressing safety and harm in their context included limited prior knowledge of HIT safety, previous assumptions and perspectives, competing priorities and organizational barriers, difficulty with the reporting system and processes, and a limited number of reports for learning. Enablers to promoting safety and mitigating harm included participating in learning sessions, gaining experience analyzing reported events, participating in safety huddles, and role modeling and leadership from the embedded researcher. Individual outcomes included increased ownership and interest in HIT safety, the development of a sociotechnical systems perspective, thinking differently about safety, and increased consideration for user perspectives. Team outcomes included enhanced communication within the team, using safety events to inform future work and strategic planning, and an overall promotion of a culture of safety. Conclusions: As HITs are integrated into care delivery, it is important for clinical informaticians to recognize the risks related to safety. Experiential learning activities, including reviewing safety event reports and participating in safety huddles, were identified as particularly impactful. An HIT safety learning initiative is a feasible approach for clinical informaticians to become more knowledgeable and engaged in HIT safety issues in their work. %M 38315544 %R 10.2196/53302 %U https://formative.jmir.org/2024/1/e53302 %U https://doi.org/10.2196/53302 %U http://www.ncbi.nlm.nih.gov/pubmed/38315544 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 12 %N %P e53262 %T mHealth Apps for the Self-Management of Low Back Pain: Systematic Search in App Stores and Content Analysis %A Zhou,Tianyu %A Salman,David %A McGregor,Alison %+ Department of Surgery and Cancer, Imperial College London, MSk lab, Sir Michael Uren Hub, 86 Wood Lan, London, W12 0BZ, United Kingdom, 44 7421760832, t.zhou20@imperial.ac.uk %K smartphone %K mHealth %K mobile health %K low back pain %K self-management %K treatment interventions %K mobile phone %D 2024 %7 1.2.2024 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: With the rapid development of mobile health (mHealth) technology, many health apps have been introduced to the commercial market for people with back pain conditions. However, little is known about their content, quality, approaches to care for low back pain (LBP), and associated risks of use. Objective: The aims of this research were to (1) identify apps for the self-management of LBP currently on the market and (2) assess their quality, intervention content, theoretical approaches, and risk-related approaches. Methods: The UK iTunes and Google Play stores were initially searched for apps related to the self-management of LBP in May 2022. A repeat search in June 2023 was conducted to ensure that any relevant new apps developed in the last year were incorporated into the review. A total of 3 keywords recommended by the Cochrane Back and Neck Group were used to search apps “low back pain,” “back pain,” and “lumbago.” The quality of the apps was assessed by using the 5-point Mobile App Rating Scale (MARS). Results: A total of 69 apps (25 iOS and 44 Android) met the inclusion criteria. These LBP self-management apps mainly provide recommendations on muscle stretching (n=51, 73.9%), muscle strengthening (n=42, 60.9%), core stability exercises (n=32, 46.4%), yoga (n=19, 27.5%), and information about LBP mechanisms (n=17, 24.6%). Most interventions (n=14, 78%) are consistent with the recommendations in the National Institute for Health and Care Excellence (NICE) guidelines. The mean (SD) MARS overall score of included apps was 2.4 (0.44) out of a possible 5 points. The functionality dimension was associated with the highest score (3.0), whereas the engagement and information dimension resulted in the lowest score (2.1). Regarding theoretical and risk-related approaches, 18 (26.1%) of the 69 apps reported the rate of intervention progression, 11 (15.9%) reported safety checks, only 1 (1.4%) reported personalization of care, and none reported the theoretical care model or the age group targeted. Conclusions: mHealth apps are potentially promising alternatives to help people manage their LBP; however, most of the LBP self-management apps were of poor quality and did not report the theoretical approaches to care and their associated risks. Although nearly all apps reviewed included a component of care listed in the NICE guidelines, the model of care delivery or embracement of care principles such as the application of a biopsychosocial model was unclear. %M 38300700 %R 10.2196/53262 %U https://mhealth.jmir.org/2024/1/e53262 %U https://doi.org/10.2196/53262 %U http://www.ncbi.nlm.nih.gov/pubmed/38300700 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e54213 %T Model for Doctor of Nursing Practice Projects Based on Cross-Fertilization Between Improvement and Implementation Sciences: Protocol for Quality Improvement and Program Evaluation Studies %A Sowan,Azizeh %A Chinman,Matthew %+ School of Nursing, The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX, 7975, United States, 1 210 567 5799, sowan@uthscsa.edu %K quality improvement %K implementation %K Doctor of Nursing Practice %K model %K methodology %K Nursing %K Doctor of Nursing %K hybrid approach %K implementation sciences %K scholarship %K scholars %K Nursing Practice Program %K nursing program %D 2024 %7 31.1.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: Hundreds of nursing professionals graduate each year from Doctor of Nursing Practice (DNP) programs, entrusted with roles as practice scholars and leaders. Graduates are tasked to lead multidisciplinary knowledge implementation projects to improve safety, quality, and key performance metrics. Nevertheless, there is a continued lack of agreement and faculty dissatisfaction with the format, focus, and results of the DNP graduation projects. The use of a wide range of models and methodologies from different sciences for knowledge implementation introduces challenges to DNP students; affects the scientific rigor of the projects; and results in the overuse, superficial use, or misuse of the models. Quality improvement (QI) and program evaluation studies are substantial investments that may lead to waste and even harm if not well conducted. Traditional QI methodologies, commonly used in DNP projects, were found to be uncertain in improving health care outcomes. The complexity of health care systems calls for cross-fertilization between improvement and implementation sciences to improve health care outcomes. Objective: This study describes the development, implementation, and evaluation of a hybrid model for QI and program evaluation studies to guide scholarship in the DNP program. Methods: The hybrid model was based on cross-fertilization between improvement and implementation sciences. The model adapted the Getting to Outcome (GTO) and Knowledge to Action (KTA) models as the overarching process models for knowledge implementation. Within each phase of the GTO and KTA models, expected barriers and facilitators for the implementation and adoption of innovation were identified based on the CFIR (Consolidated Framework for Implementation Research). Accordingly, strategies to facilitate the implementation and adoption of innovations were identified based on a refined list of implementation strategies and QI tools. The choice of these models was based on the top 5 criteria for selecting implementation science theories and frameworks. Seven DNP students used the hybrid model to conduct QI projects. Students evaluated their experiences by responding to a Qualtrics survey. Results: The hybrid model encouraged a comprehensive systematic way of thinking, provided tools essential to implementation success, emphasized the need for adaptability in implementation, maintained rigor in QI, and guided the sustainability of change initiatives. Some of the challenges faced by students included finding reliable and valid measures, attaining and maintaining staff buy-in, and competing organizational priorities. Conclusions: Cross-fertilization between improvement and implementation sciences provided a roadmap and systematic thinking for successful QI projects in the DNP program. The integration of the CFIR with the GTO or KTA process models, enforced by the use of evidence-based implementation strategies and QI tools, reflected the complexity of health care systems and emphasized the need for adaptability in implementation. International Registered Report Identifier (IRRID): RR1-10.2196/54213 %M 38294860 %R 10.2196/54213 %U https://www.researchprotocols.org/2024/1/e54213 %U https://doi.org/10.2196/54213 %U http://www.ncbi.nlm.nih.gov/pubmed/38294860 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e47430 %T The Reporting Quality of Machine Learning Studies on Pediatric Diabetes Mellitus: Systematic Review %A Zrubka,Zsombor %A Kertész,Gábor %A Gulácsi,László %A Czere,János %A Hölgyesi,Áron %A Nezhad,Hossein Motahari %A Mosavi,Amir %A Kovács,Levente %A Butte,Atul J %A Péntek,Márta %+ HECON Health Economics Research Center, University Research and Innovation Center, Óbuda University, Bécsi út 96/b, Budapest, 1034, Hungary, 36 302029415, zrubka.zsombor@uni-obuda.hu %K diabetes mellitus %K children %K adolescent %K pediatric %K machine learning %K Minimum Information About Clinical Artificial Intelligence Modelling %K MI-CLAIM %K reporting quality %D 2024 %7 19.1.2024 %9 Review %J J Med Internet Res %G English %X Background: Diabetes mellitus (DM) is a major health concern among children with the widespread adoption of advanced technologies. However, concerns are growing about the transparency, replicability, biasedness, and overall validity of artificial intelligence studies in medicine. Objective: We aimed to systematically review the reporting quality of machine learning (ML) studies of pediatric DM using the Minimum Information About Clinical Artificial Intelligence Modelling (MI-CLAIM) checklist, a general reporting guideline for medical artificial intelligence studies. Methods: We searched the PubMed and Web of Science databases from 2016 to 2020. Studies were included if the use of ML was reported in children with DM aged 2 to 18 years, including studies on complications, screening studies, and in silico samples. In studies following the ML workflow of training, validation, and testing of results, reporting quality was assessed via MI-CLAIM by consensus judgments of independent reviewer pairs. Positive answers to the 17 binary items regarding sufficient reporting were qualitatively summarized and counted as a proxy measure of reporting quality. The synthesis of results included testing the association of reporting quality with publication and data type, participants (human or in silico), research goals, level of code sharing, and the scientific field of publication (medical or engineering), as well as with expert judgments of clinical impact and reproducibility. Results: After screening 1043 records, 28 studies were included. The sample size of the training cohort ranged from 5 to 561. Six studies featured only in silico patients. The reporting quality was low, with great variation among the 21 studies assessed using MI-CLAIM. The number of items with sufficient reporting ranged from 4 to 12 (mean 7.43, SD 2.62). The items on research questions and data characterization were reported adequately most often, whereas items on patient characteristics and model examination were reported adequately least often. The representativeness of the training and test cohorts to real-world settings and the adequacy of model performance evaluation were the most difficult to judge. Reporting quality improved over time (r=0.50; P=.02); it was higher than average in prognostic biomarker and risk factor studies (P=.04) and lower in noninvasive hypoglycemia detection studies (P=.006), higher in studies published in medical versus engineering journals (P=.004), and higher in studies sharing any code of the ML pipeline versus not sharing (P=.003). The association between expert judgments and MI-CLAIM ratings was not significant. Conclusions: The reporting quality of ML studies in the pediatric population with DM was generally low. Important details for clinicians, such as patient characteristics; comparison with the state-of-the-art solution; and model examination for valid, unbiased, and robust results, were often the weak points of reporting. To assess their clinical utility, the reporting standards of ML studies must evolve, and algorithms for this challenging population must become more transparent and replicable. %M 38241075 %R 10.2196/47430 %U https://www.jmir.org/2024/1/e47430 %U https://doi.org/10.2196/47430 %U http://www.ncbi.nlm.nih.gov/pubmed/38241075 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e53002 %T Application of Failure Mode and Effects Analysis to Improve the Quality of the Front Page of Electronic Medical Records in China: Cross-Sectional Data Mapping Analysis %A Zhan,Siyi %A Ding,Liping %A Li,Hui %A Su,Aonan %+ Zhejiang Provincial People's Hospital, No. 158, Shangtang Rd, Hangzhou, 310000, China, 86 18814885258, suaonan_512917@126.com %K front page %K EMR system %K electronic medical record %K failure mode and effects analysis %K FMEA %K measures %D 2024 %7 19.1.2024 %9 Original Paper %J JMIR Med Inform %G English %X Background: The completeness and accuracy of the front pages of electronic medical records (EMRs) are crucial for evaluating hospital performance and for health insurance payments to inpatients. However, the quality of the first page of EMRs in China's medical system is not satisfactory, which can be partly attributed to deficiencies in the EMR system. Failure mode and effects analysis (FMEA) is a proactive risk management tool that can be used to investigate the potential failure modes in an EMR system and analyze the possible consequences. Objective: The purpose of this study was to preemptively identify the potential failures of the EMR system in China and their causes and effects in order to prevent such failures from recurring. Further, we aimed to implement corresponding improvements to minimize system failure modes. Methods: From January 1, 2020, to May 31, 2022, 10 experts, including clinicians, engineers, administrators, and medical record coders, in Zhejiang People’s Hospital conducted FMEA to improve the quality of the front page of the EMR. The completeness and accuracy of the front page and the risk priority numbers were compared before and after the implementation of specific improvement measures. Results: We identified 2 main processes and 6 subprocesses for improving the EMR system. We found that there were 13 potential failure modes, including data messaging errors, data completion errors, incomplete quality control, and coding errors. A questionnaire survey administered to random physicians and coders showed 7 major causes for these failure modes. Therefore, we established quality control rules for medical records and embedded them in the system. We also integrated the medical insurance system and the front page of the EMR on the same interface and established a set of intelligent front pages in the EMR management system. Further, we revamped the quality management systems such as communicating with physicians regularly and conducting special training seminars. The overall accuracy and integrity rate of the front page (P<.001) of the EMR increased significantly after implementation of the improvement measures, while the risk priority number decreased. Conclusions: In this study, we were able to identify the potential failure modes in the front page of the EMR system by using the FMEA method and implement corresponding improvement measures in order to minimize recurring errors in the health care services in China. %M 38241064 %R 10.2196/53002 %U https://medinform.jmir.org/2024/1/e53002 %U https://doi.org/10.2196/53002 %U http://www.ncbi.nlm.nih.gov/pubmed/38241064 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 12 %N %P e48625 %T Developing a Comprehensive List of Criteria to Evaluate the Characteristics and Quality of eHealth Smartphone Apps: Systematic Review %A Ribaut,Janette %A DeVito Dabbs,Annette %A Dobbels,Fabienne %A Teynor,Alexandra %A Mess,Elisabeth Veronica %A Hoffmann,Theresa %A De Geest,Sabina %+ Institute of Nursing Science, Department Public Health, University of Basel, Bernoullistrasse 28, Basel, 4056, Switzerland, 41 61 207 09 16, sabina.degeest@unibas.ch %K telemedicine %K smartphone %K mobile apps %K program evaluation %K decision-making %K systematic review %K mobile phone %D 2024 %7 15.1.2024 %9 Review %J JMIR Mhealth Uhealth %G English %X Background: The field of eHealth is growing rapidly and chaotically. Health care professionals need guidance on reviewing and assessing health-related smartphone apps to propose appropriate ones to their patients. However, to date, no framework or evaluation tool fulfills this purpose. Objective: Before developing a tool to help health care professionals assess and recommend apps to their patients, we aimed to create an overview of published criteria to describe and evaluate health apps. Methods: We conducted a systematic review to identify existing criteria for eHealth smartphone app evaluation. Relevant databases and trial registers were queried for articles. Articles were included that (1) described tools, guidelines, dimensions, or criteria to evaluate apps, (2) were available in full text, and (3) were written in English, French, German, Italian, Portuguese, or Spanish. We proposed a conceptual framework for app evaluation based on the dimensions reported in the selected articles. This was revised iteratively in discussion rounds with international stakeholders. The conceptual framework was used to synthesize the reported evaluation criteria. The list of criteria was discussed and refined by the research team. Results: Screening of 1258 articles yielded 128 (10.17%) that met the inclusion criteria. Of these 128 articles, 30 (23.4%) reported the use of self-developed criteria and described their development processes incompletely. Although 43 evaluation instruments were used only once, 6 were used in multiple studies. Most articles (83/128, 64.8%) did not report following theoretical guidelines; those that did noted 37 theoretical frameworks. On the basis of the selected articles, we proposed a conceptual framework to explore 6 app evaluation dimensions: context, stakeholder involvement, features and requirements, development processes, implementation, and evaluation. After standardizing the definitions, we identified 205 distinct criteria. Through consensus, the research team relabeled 12 of these and added 11 more—mainly related to ethical, legal, and social aspects—resulting in 216 evaluation criteria. No criteria had to be moved between dimensions. Conclusions: This study provides a comprehensive overview of criteria currently used in clinical practice to describe and evaluate apps. This is necessary as no reviewed criteria sets were inclusive, and none included consistent definitions and terminology. Although the resulting overview is impractical for use in clinical practice in its current form, it confirms the need to craft it into a purpose-built, theory-driven tool. Therefore, in a subsequent step, based on our current criteria set, we plan to construct an app evaluation tool with 2 parts: a short section (including 1-3 questions/dimension) to quickly disqualify clearly unsuitable apps and a longer one to investigate more likely candidates in closer detail. We will use a Delphi consensus-building process and develop a user manual to prepare for this undertaking. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42021227064; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021227064 %M 38224477 %R 10.2196/48625 %U https://mhealth.jmir.org/2024/1/e48625 %U https://doi.org/10.2196/48625 %U http://www.ncbi.nlm.nih.gov/pubmed/38224477 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 12 %N %P e46501 %T Design and Implementation of an Inpatient Fall Risk Management Information System %A Wang,Ying %A Jiang,Mengyao %A He,Mei %A Du,Meijie %+ School of Management, Wuhan University of Technology, 122 Luoshi Road, Hongshan District, Wuhan, 430070, China, 86 027 83662317, wangying_tjh@hotmail.com %K fall %K hospital information system %K patient safety %K quality improvement %K management %K implementation %D 2024 %7 2.1.2024 %9 Implementation Report %J JMIR Med Inform %G English %X Background: Falls had been identified as one of the nursing-sensitive indicators for nursing care in hospitals. With technological progress, health information systems make it possible for health care professionals to manage patient care better. However, there is a dearth of research on health information systems used to manage inpatient falls. Objective: This study aimed to design and implement a novel hospital-based fall risk management information system (FRMIS) to prevent inpatient falls and improve nursing quality. Methods: This implementation was conducted at a large academic medical center in central China. We established a nurse-led multidisciplinary fall prevention team in January 2016. The hospital’s fall risk management problems were summarized by interviewing fall-related stakeholders, observing fall prevention workflow and post–fall care process, and investigating patients' satisfaction. The FRMIS was developed using an iterative design process, involving collaboration among health care professionals, software developers, and system architects. We used process indicators and outcome indicators to evaluate the implementation effect. Results: The FRMIS includes a fall risk assessment platform, a fall risk warning platform, a fall preventive strategies platform, fall incident reporting, and a tracking improvement platform. Since the implementation of the FRMIS, the inpatient fall rate was significantly lower than that before implementation (P<.05). In addition, the percentage of major fall-related injuries was significantly lower than that before implementation. The implementation rate of fall-related process indicators and the reporting rate of high risk of falls were significantly different before and after system implementation (P<.05). Conclusions: The FRMIS provides support to nursing staff in preventing falls among hospitalized patients while facilitating process control for nursing managers. %M 38165733 %R 10.2196/46501 %U https://medinform.jmir.org/2024/1/e46501 %U https://doi.org/10.2196/46501 %U http://www.ncbi.nlm.nih.gov/pubmed/38165733 %0 Journal Article %@ 2562-0959 %I JMIR Publications %V 6 %N %P e48981 %T The Effect of Remote Digital Services on Health Care Inequalities Among People Under Long-Term Dermatology Follow-Up: Cross-Sectional Questionnaire Study %A Ramjee,Serena %A Mohamedthani,Hanen %A Patel,Aditya Umeshkumar %A Goiriz,Rebeca %A Harwood,Catherine A %A Osborne,Richard H %A Cheng,Christina %A Hasan,Zeeshaan-ul %+ Barts and the London School of Medicine and Dentistry, Queen Mary University London, Garrod Building, Turner St, London, E1 2AD, United Kingdom, 44 02078822239, serena.ramjee1@nhs.net %K dermatology %K health literacy %K digital health literacy %K digital literacy %K skin %K chronic %K cluster analysis %K innovation %K eHealth literacy %K dermatologists %K telehealth %K dermatologist %K telemedicine %K remote care %K service %K services %K quality improvement %D 2023 %7 8.12.2023 %9 Original Paper %J JMIR Dermatol %G English %X Background: Given the expansion of remote digital dermatology services from the National Health Service, particularly during the COVID-19 pandemic, there is a need for methods that identify patients at risk of digital exclusion to guide equitable representation in service co-design processes and tailor remote services to the needs of their patient population. Objective: This quality improvement project aims to inform the redesign of remote services to optimally support the ongoing needs of patients with chronic skin diseases, ensuring that the services are tailored to patients’ digital health literacy requirements. Methods: We profiled the digital health literacy of 123 people with chronic skin conditions who require long-term surveillance in 2 specialist clinics (London, United Kingdom) using the Multidimensional Readiness and Enablement Index for Health Technology (READHY) questionnaire alongside the Optimizing Health Literacy and Access (Ophelia) process for hierarchical cluster analysis. Results: The cluster analysis of READHY dimensions in responding participants (n=116) revealed 7 groups with distinct digital and health literacy characteristics. High READHY scores in groups 1 (n=22, 19%) and 2 (n=20, 17.2%) represent those who are confident with managing their health and using technology, whereas the lower-scoring groups, 6 (n=4, 3.4%) and 7 (n=12, 10.3%), depended on traditional services. Groups 3 (n=27, 23.3%), 4 (n=23, 19.8%), and 5 (n=8, 6.9%) had varying digital skills, access, and engagement, highlighting a population that may benefit from a co-designed dermatology service. Conclusions: By identifying patient groups with distinguishable patterns of digital access and health literacy, our method demonstrates that 63.8% (n=74) of people attending specialist clinics in our center require support in order to optimize remote follow-up or need an alternative approach. Future efforts should streamline the READHY question profile to improve its practicality and use focus groups to elicit strategies for engaging patients with digital services. %M 38064259 %R 10.2196/48981 %U https://derma.jmir.org/2023/1/e48981 %U https://doi.org/10.2196/48981 %U http://www.ncbi.nlm.nih.gov/pubmed/38064259 %0 Journal Article %@ 2562-0959 %I JMIR Publications %V 6 %N %P e43821 %T The Reporting and Methodological Quality of Systematic Reviews Underpinning Clinical Practice Guidelines Focused on the Management of Cutaneous Melanoma: Cross-Sectional Analysis %A Khalid,Mahnoor %A Sutterfield,Bethany %A Minley,Kirstien %A Ottwell,Ryan %A Abercrombie,McKenna %A Heath,Christopher %A Torgerson,Trevor %A Hartwell,Micah %A Vassar,Matt %+ Office of Medical Student Research, Oklahoma State University Center for Health Sciences, 1111 W 17th St, Tulsa, OK, 74107, United States, 1 (918) 853 9938, mahnoor.khalid@okstate.edu %K clinical practice guidelines %K clinical %K cutaneous melanoma %K decision making %K evidence %K management %K melanoma %K practice guideline %K review %K systematic review %D 2023 %7 7.12.2023 %9 Original Paper %J JMIR Dermatol %G English %X Background: Clinical practice guidelines (CPGs) inform evidence-based decision-making in the clinical setting; however, systematic reviews (SRs) that inform these CPGs may vary in terms of reporting and methodological quality, which affects confidence in summary effect estimates. Objective: Our objective was to appraise the methodological and reporting quality of the SRs used in CPGs for cutaneous melanoma and evaluate differences in these outcomes between Cochrane and non-Cochrane reviews. Methods: We conducted a cross-sectional analysis by searching PubMed for cutaneous melanoma guidelines published between January 1, 2015, and May 21, 2021. Next, we extracted SRs composing these guidelines and appraised their reporting and methodological rigor using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and AMSTAR (A Measurement Tool to Assess Systematic Reviews) checklists. Lastly, we compared these outcomes between Cochrane and non-Cochrane SRs. All screening and data extraction occurred in a masked, duplicate fashion. Results: Of the SRs appraised, the mean completion rate was 66.5% (SD 12.29%) for the PRISMA checklist and 44.5% (SD 21.05%) for AMSTAR. The majority of SRs (19/50, 53%) were of critically low methodological quality, with no SRs being appraised as high quality. There was a statistically significant association (P<.001) between AMSTAR and PRISMA checklists. Cochrane SRs had higher PRISMA mean completion rates and higher methodological quality than non-Cochrane SRs. Conclusions: SRs supporting CPGs focused on the management of cutaneous melanoma vary in reporting and methodological quality, with the majority of SRs being of low quality. Increasing adherence to PRISMA and AMSTAR checklists will likely increase the quality of SRs, thereby increasing the level of evidence supporting cutaneous melanoma CPGs. %M 38060306 %R 10.2196/43821 %U https://derma.jmir.org/2023/1/e43821 %U https://doi.org/10.2196/43821 %U http://www.ncbi.nlm.nih.gov/pubmed/38060306 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e44530 %T The Use of Medical Crowdfunding to Mitigate the Personal Costs of Serious Chronic Illness: Scoping Review %A Killela,Mary %A Biddell,Caitlin %A Keim-Malpass,Jessica %A Schwartz,Todd A %A Soto,Sandra %A Williams,Jessica %A Santacroce,Sheila %+ School of Nursing, University of North Carolina at Chapel Hill, 120 N Medical Dr, Chapel Hill, NC, 27599, United States, 1 919 843 8566, mkillela@email.unc.edu %K COVID-19 %K chronic illness %K costs %K financial %K stress %K appraisal %K coping %K crowdfunding %K social network %K social support %K caregiver %K systematic scoping review %K medical crowdfunding %K social network %K coping behavior %D 2023 %7 4.12.2023 %9 Review %J J Med Internet Res %G English %X Background: Persons diagnosed with serious chronic illnesses and their caretakers experience multiple types of financial costs that strain their income and generate financial distress. Many turn to medical crowdfunding (MCF) to mitigate the harms of these costs on their health and quality of life. Objective: This scoping review aims to summarize the research on MCF for persons diagnosed with serious chronic illness regarding study designs and methods; the responsible conduct of research practices; and study foci as they relate to stress, stress appraisals, and the coping processes. Methods: This review was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. Eligible studies were conducted in countries designated as high income by the World Bank and focused on beneficiaries diagnosed with serious chronic illness. The findings of the included studies were summarized as they related to the key concepts in a conceptual framework derived from an established stress, appraisal, and coping framework and a conceptual model of financial toxicity in pediatric oncology. Results: Overall, 26 studies were eligible for inclusion in the review. The main findings included a lack of integration of qualitative and quantitative approaches and the inconsistent reporting of the responsible conduct of research practices. The included studies focused on financial stressors that contributed to financial burden, such as out-of-pocket payments of medical bills, basic living expenses, medical travel expenses, and lost income owing to illness-related work disruptions. Few studies addressed stress appraisals as threatening or the adequacy of available financial resources. When mentioned, appraisals related to the global financial struggle during the COVID-19 pandemic or the capacity of social network members to donate funds. The consequences of MCF included the receipt of 3 forms of social support (tangible, informational, and emotional), privacy loss, embarrassment, and the propagation of scientifically unsupported information. Studies found that friends and family tended to manage MCF campaigns. Although most of the studies (21/26, 81%) focused on monetary outcomes, a few (5/26, 19%) concentrated on peoples’ experiences with MCF. Conclusions: The identified methodological gaps highlight the need for more robust and reproducible approaches to using the copious data available on public MCF platforms. The integration of quantitative and qualitative methods will allow for nuanced explorations of the MCF experience. A more consistent elaboration of strategies to promote the responsible conduct of research is warranted to minimize risk to populations that are vulnerable and express concerns regarding the loss of privacy. Finally, an examination of the unanticipated consequences of MCF is critical for the development of future interventions to optimize existing supports while providing needed supports, financial and nonfinancial, that are lacking. %M 38048149 %R 10.2196/44530 %U https://www.jmir.org/2023/1/e44530 %U https://doi.org/10.2196/44530 %U http://www.ncbi.nlm.nih.gov/pubmed/38048149 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e45128 %T User-Guided Enhancements to a Technology-Facilitated Resilience Program to Address Opioid Risks Following Traumatic Injury in Youth: Qualitative Interview Study %A Adams,Zachary W %A Marriott,Brigid R %A Karra,Swathi %A Linhart-Musikant,Elizabeth %A Raymond,Jodi L %A Fischer,Lydia J %A Bixler,Kristina A %A Bell,Teresa M %A Bryan,Eric A %A Hulvershorn,Leslie A %+ Department of Psychiatry, Indiana University School of Medicine, 410 West 10th Street, Indianapolis, IN, 46202, United States, 1 3172780591, zwadams@iu.edu %K access-to-care %K addiction %K adolescent %K behavior %K health disorder %K opioid use disorder %K opioid %K personalized care %K telehealth %K telemedicine %K trauma %K user %K youth %D 2023 %7 30.11.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Youth with traumatic injury experience elevated risk for behavioral health disorders, yet posthospital monitoring of patients’ behavioral health is rare. The Telehealth Resilience and Recovery Program (TRRP), a technology-facilitated and stepped access-to-care program initiated in hospitals and designed to be integrated seamlessly into trauma center operations, is a program that can potentially address this treatment gap. However, the TRRP was originally developed to address this gap for mental health recovery but not substance use. Given the high rates of substance and opioid use disorders among youth with traumatic injury, there is a need to monitor substance use and related symptoms alongside other mental health concerns. Objective: This study aimed to use an iterative, user-guided approach to inform substance use adaptations to TRRP content and procedures. Methods: We conducted individual semistructured interviews with adolescents (aged 12-17 years) and young adults (aged 18-25 years) who were recently discharged from trauma centers (n=20) and health care providers from two level 1 trauma centers (n=15). Interviews inquired about reactions to and recommendations for expanding TRRP content, features, and functionality; factors related to TRRP implementation and acceptability; and current strategies for monitoring patients’ postinjury physical and emotional recovery and opioid and substance use. Interview responses were transcribed and analyzed using thematic analysis to guide new TRRP substance use content and procedures. Results: Themes identified in interviews included gaps in care, task automation, user personalization, privacy concerns, and in-person preferences. Based on these results, a multimedia, web-based mobile education app was developed that included 8 discrete interactive education modules and 6 videos on opioid use disorder, and TRRP procedures were adapted to target opioid and other substance use disorder risk. Substance use adaptations included the development of a set of SMS text messaging–delivered questions that monitor both mental health symptoms and substance use and related symptoms (eg, pain and sleep) and the identification of validated mental health and substance use screening tools to monitor patients’ behavioral health in the months after discharge. Conclusions: Patients and health care providers found the TRRP and its expansion to address substance use acceptable. This iterative, user-guided approach yielded novel content and procedures that will be evaluated in a future trial. %M 38032728 %R 10.2196/45128 %U https://formative.jmir.org/2023/1/e45128 %U https://doi.org/10.2196/45128 %U http://www.ncbi.nlm.nih.gov/pubmed/38032728 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e45968 %T Co-design of a Mobile App for Engaging Breast Cancer Patients in Reporting Health Experiences: Qualitative Case Study %A Taramasco,Carla %A Rimassa,Carla %A Noël,René %A Bravo Storm,María Loreto %A Sánchez,César %+ Instituto de Tecnologías para la Innovación en Salud y Bienestar, Facultad de Ingeniería, Universidad Andrés Bello, Quillota 980, Viña del Mar, 2531015, Chile, 56 322507000, carla.taramasco@unab.cl %K cancer %K registration systems %K patient-reported outcome measures %K patient-reported experience measures %K software analysis and design %K cancer patient report %K adverse event reporting %K quality of life %K eHealth %K mHealth %K mobile health %D 2023 %7 27.11.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: The World Health Organization recommends incorporating patient-reported experience measures and patient-reported outcome measures to ensure care processes. New technologies, such as mobile apps, could help report and monitor patients’ adverse effects and doubts during treatment. However, engaging patients in the daily use of mobile apps is a challenge that must be addressed in accordance with the needs of people. Objective: We present a qualitative case study documenting the process of identifying the information needs of breast cancer patients and health care professionals during the treatment process in a Chilean cancer institution. The study aims to identify patients’ information requirements for integration into a mobile app that accompanies patients throughout their treatment while also providing features for reporting adverse symptoms. Methods: We conducted focus groups with breast cancer patients who were undergoing chemotherapy (n=3) or who completed chemotherapy between 3 months and 1 year (n=1). We also surveyed health care professionals (n=9) who were involved in patient care and who belonged to the oncology committee of the cancer center where the study took place. Content analysis was applied to the responses to categorize the information needs and the means to satisfy them. A user interface was designed according to the findings of the focus groups and was assessed by 3 trained information system and user interaction design experts from 2 countries, using heuristic evaluation guidelines for mobile apps. Results: Patients’ information needs were classified into 4 areas: an overview of the disease, information on treatment and day-to-day affairs, assistance on the normality and abnormality of symptoms during treatment, and symptoms relevant to report. Health care professionals required patients to be provided with information on the administrative and financial process. We noted that the active involvement of the following 4 main actors is required to satisfy the information needs: patients, caregivers, social network moderators, and health professionals. Seven usability guidelines were extracted from the heuristic evaluation recommendations. Conclusions: A mobile app that seeks to accompany breast cancer patients to report symptoms requires the involvement of multiple participants to handle the reports and day-to-day information needs. User interfaces must be designed with consideration of the patient’s social conventions and the emotional load of the disease information. %M 38010791 %R 10.2196/45968 %U https://www.jmir.org/2023/1/e45968 %U https://doi.org/10.2196/45968 %U http://www.ncbi.nlm.nih.gov/pubmed/38010791 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e47505 %T Innovation Process and Industrial System of US Food and Drug Administration–Approved Software as a Medical Device: Review and Content Analysis %A Yu,Jiakan %A Zhang,Jiajie %A Sengoku,Shintaro %+ Department of Innovation Science, School of Environment and Society, Tokyo Institute of Technology, Tokyo Campus Innovation Center 9th Floor Room 908N, 3-3-6 Shibaura, Minato-ku, Tokyo, 108-0023, Japan, 81 03 3454 8907, sengoku.s.aa@m.titech.ac.jp %K digital health %K digital therapeutics %K software as a medical device %K innovation process %K artificial intelligence %D 2023 %7 24.11.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: There has been a surge in academic and business interest in software as a medical device (SaMD). SaMD enables medical professionals to streamline existing medical practices and make innovative medical processes such as digital therapeutics a reality. Furthermore, SaMD is a billion-dollar market. However, SaMD is not clearly understood as a technological change and emerging industry. Objective: This study aims to review the landscape of SaMD in response to increasing interest in SaMD within health systems and regulation. The objectives of the study are to (1) clarify the innovation process of SaMD, (2) identify the prevailing typology of such innovation, and (3) elucidate the underlying mechanisms driving the SaMD innovation process. Methods: We collected product information on 581 US Food and Drug Administration–approved SaMDs from the OpenFDA website and 268 company profiles of the corresponding manufacturers from Crunchbase, Bloomberg, PichBook.com, and other company websites. In addition to assessing the metadata of SaMD, we used correspondence and business process analysis to assess the distribution of intended use and how SaMDs interact with other devices in the medical process. Results: The current SaMD industry is highly concentrated in medical image processing and radiological analysis. Incumbents in the medical device industry currently lead the market and focus on incremental innovation, whereas new entrants, particularly startups, produce more disruptive innovation. We found that hardware medical device functions as a complementary asset for SaMD, whereas how SaMD interacts with the complementary asset differs according to its intended use. Based on these findings, we propose a regime map that illustrates the SaMD innovation process. Conclusions: SaMD, as an industry, is nascent and dominated by incremental innovation. The innovation process of the present SaMD industry is shaped by data accessibility, which is key to building disruptive innovation. %M 37999948 %R 10.2196/47505 %U https://www.jmir.org/2023/1/e47505 %U https://doi.org/10.2196/47505 %U http://www.ncbi.nlm.nih.gov/pubmed/37999948 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 10 %N %P e47718 %T Developing an Audit and Feedback Dashboard for Family Physicians: User-Centered Design Process %A Shuldiner,Jennifer %A Kiran,Tara %A Agarwal,Payal %A Daneshvarfard,Maryam %A Eldridge,Kirsten %A Kim,Susie %A Greiver,Michelle %A Jokhio,Iffat %A Ivers,Noah %+ Women's College Hospital, 76 Grenville, Toronto, ON, M5S 1B2, Canada, 1 6474720232, jennifer.shuldiner@wchospital.ca %K audit and feedback %K primary care %K design %K user-centered %K design %K audit %K feedback %K development %K dashboard %K family physician %K clinical performance %K implementation %K users %K primary care %K care %D 2023 %7 9.11.2023 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Audit and feedback (A&F), the summary and provision of clinical performance data, is a common quality improvement strategy. Successful design and implementation of A&F—or any quality improvement strategy—should incorporate evidence-informed best practices as well as context-specific end user input. Objective: We used A&F theory and user-centered design to inform the development of a web-based primary care A&F dashboard. We describe the design process and how it influenced the design of the dashboard. Methods: Our design process included 3 phases: prototype development based on A&F theory and input from clinical improvement leaders; workshop with family physician quality improvement leaders to develop personas (ie, fictional users that represent an archetype character representative of our key users) and application of those personas to design decisions; and user-centered interviews with family physicians to learn about the physician’s reactions to the revised dashboard. Results: The team applied A&F best practices to the dashboard prototype. Personas were used to identify target groups with challenges and behaviors as a tool for informed design decision-making. Our workshop produced 3 user personas, Dr Skeptic, Frazzled Physician, and Eager Implementer, representing common users based on the team’s experience of A&F. Interviews were conducted to further validate findings from the persona workshop and found that (1) physicians were interested in how they compare with peers; however, if performance was above average, they were not motivated to improve even if gaps compared to other standards in their care remained; (2) burnout levels were high as physicians are trying to catch up on missed care during the pandemic and are therefore less motivated to act on the data; and (3) additional desired features included integration within the electronic medical record, and more up-to-date and accurate data. Conclusions: We found that carefully incorporating data from user interviews helped operationalize generic best practices for A&F to achieve an acceptable dashboard that could meet the needs and goals of physicians. We demonstrate such a design process in this paper. A&F dashboards should address physicians’ data skepticism, present data in a way that spurs action, and support physicians to have the time and capacity to engage in quality improvement work; the steps we followed may help those responsible for quality improvement strategy implementation achieve these aims. %M 37943586 %R 10.2196/47718 %U https://humanfactors.jmir.org/2023/1/e47718 %U https://doi.org/10.2196/47718 %U http://www.ncbi.nlm.nih.gov/pubmed/37943586 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 12 %N %P e49842 %T Applying AI and Guidelines to Assist Medical Students in Recognizing Patients With Heart Failure: Protocol for a Randomized Trial %A Joo,Hyeon %A Mathis,Michael R %A Tam,Marty %A James,Cornelius %A Han,Peijin %A Mangrulkar,Rajesh S %A Friedman,Charles P %A Vydiswaran,VG Vinod %+ Department of Learning Health Sciences, University of Michigan, 1111 East Catherine Street, Ann Arbor, MI, 48109, United States, 1 7349361644, thejoo@umich.edu %K medical education %K clinical decision support systems %K artificial intelligence %K machine learning %K heart failure %K evidence-based medicine %K guidelines %K digital health interventions %D 2023 %7 24.10.2023 %9 Protocol %J JMIR Res Protoc %G English %X Background: The integration of artificial intelligence (AI) into clinical practice is transforming both clinical practice and medical education. AI-based systems aim to improve the efficacy of clinical tasks, enhancing diagnostic accuracy and tailoring treatment delivery. As it becomes increasingly prevalent in health care for high-quality patient care, it is critical for health care providers to use the systems responsibly to mitigate bias, ensure effective outcomes, and provide safe clinical practices. In this study, the clinical task is the identification of heart failure (HF) prior to surgery with the intention of enhancing clinical decision-making skills. HF is a common and severe disease, but detection remains challenging due to its subtle manifestation, often concurrent with other medical conditions, and the absence of a simple and effective diagnostic test. While advanced HF algorithms have been developed, the use of these AI-based systems to enhance clinical decision-making in medical education remains understudied. Objective: This research protocol is to demonstrate our study design, systematic procedures for selecting surgical cases from electronic health records, and interventions. The primary objective of this study is to measure the effectiveness of interventions aimed at improving HF recognition before surgery, the second objective is to evaluate the impact of inaccurate AI recommendations, and the third objective is to explore the relationship between the inclination to accept AI recommendations and their accuracy. Methods: Our study used a 3 × 2 factorial design (intervention type × order of prepost sets) for this randomized trial with medical students. The student participants are asked to complete a 30-minute e-learning module that includes key information about the intervention and a 5-question quiz, and a 60-minute review of 20 surgical cases to determine the presence of HF. To mitigate selection bias in the pre- and posttests, we adopted a feature-based systematic sampling procedure. From a pool of 703 expert-reviewed surgical cases, 20 were selected based on features such as case complexity, model performance, and positive and negative labels. This study comprises three interventions: (1) a direct AI-based recommendation with a predicted HF score, (2) an indirect AI-based recommendation gauged through the area under the curve metric, and (3) an HF guideline-based intervention. Results: As of July 2023, 62 of the enrolled medical students have fulfilled this study’s participation, including the completion of a short quiz and the review of 20 surgical cases. The subject enrollment commenced in August 2022 and will end in December 2023, with the goal of recruiting 75 medical students in years 3 and 4 with clinical experience. Conclusions: We demonstrated a study protocol for the randomized trial, measuring the effectiveness of interventions using AI and HF guidelines among medical students to enhance HF recognition in preoperative care with electronic health record data. International Registered Report Identifier (IRRID): DERR1-10.2196/49842 %M 37874618 %R 10.2196/49842 %U https://www.researchprotocols.org/2023/1/e49842 %U https://doi.org/10.2196/49842 %U http://www.ncbi.nlm.nih.gov/pubmed/37874618 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e43765 %T Patient and Health Care Provider Perspectives on Patient Access to Test Results via Web Portals: Scoping Review %A Petrovskaya,Olga %A Karpman,Albina %A Schilling,Joanna %A Singh,Simran %A Wegren,Larissa %A Caine,Vera %A Kusi-Appiah,Elizabeth %A Geen,Willow %+ School of Nursing, University of Victoria, PO Box 1700 STN CSC, Victoria, BC, V8W 2Y2, Canada, 1 250 472 4607, olgap@uvic.ca %K patient portal %K web portal %K MyChart %K electronic health records %K personal health records %K patient access to records %K laboratory tests %K radiology reports %K diagnostic imaging %K laboratory test results %K result release %K embargo %K the Cures Act %D 2023 %7 19.10.2023 %9 Review %J J Med Internet Res %G English %X Background: A frequently used feature of electronic patient portals is the viewing of test results. Research on patient portals is abundant and offers evidence to help portal implementers make policy and practice decisions. In contrast, no comparable comprehensive summary of research addresses the direct release of and patient access to test results. Objective: This scoping review aims to analyze and synthesize published research focused on patient and health care provider perspectives on the direct release of laboratory, imaging, and radiology results to patients via web portals. Methods: PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed. Searches were conducted in CINAHL, MEDLINE, and other databases. Citations were screened in Covidence using the inclusion and exclusion criteria. Primary studies that focused on patient and health care provider perspectives on patient access to laboratory and imaging results via web portals were included. An updated search was conducted up to August 2023. Our review included 27 articles—20 examining patient views, 3 examining provider views, and 4 examining both patient and provider views. Data extraction and inductive data analysis were informed by sensitizing concepts from sociomaterial perspectives, and 15 themes were generated. Results: Patient perspectives (24 papers) were synthesized using nine themes: (1) patterns of use and patient characteristics; (2) emotional response when viewing the results and uncertainty about their implications; (3) understanding test results; (4) preferences for mode and timing of result release; (5). information seeking and patients’ actions motivated by viewing results via a portal; (6) contemplating changes in behavior and managing own health; (7) benefits of accessing test results via a portal; (8) limitations of accessing test results via a portal; and (9) suggestions for portal improvement. Health care provider perspectives (7 papers) were synthetized into six themes: (1) providers’ view of benefits of patient access to results via the portal; (2) effects on health care provider workload; (3) concerns about patient anxiety; (4) timing of result release into the patient portal; (5) the method of result release into the patient portal: manual versus automatic release; and (6) the effects of hospital health information technology system on patient quality outcomes. Conclusions: The timing of the release of test results emerged as a particularly important topic. In some countries, the policy context may motivate immediate release of most tests directly into patient portals. However, our findings aim to make policy makers, health administrators, and other stakeholders aware of factors to consider when making decisions about the timing of result release. This review is sensitive to the characteristics of patient populations and portal technology and can inform result release framework policies. The findings are timely, as patient portals have become more common internationally. %M 37856174 %R 10.2196/43765 %U https://www.jmir.org/2023/1/e43765 %U https://doi.org/10.2196/43765 %U http://www.ncbi.nlm.nih.gov/pubmed/37856174 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 11 %N %P e48256 %T Implementing Clinical Information Systems in Sub-Saharan Africa: Report and Lessons Learned From the MatLook Project in Cameroon %A Bediang,Georges %+ Faculty of Medicine and Biomedical Sciences, Université de Yaoundé, PO Box 1364, Yaoundé, Cameroon, 237 699588574, bediang@yahoo.com %K implementation report %K challenges %K success factors %K Sub-Saharan Africa %K Cameroon %K healthcare %K health care %K clinical information %K information management %K clinical information systems %K hospital information systems %K data governance %D 2023 %7 18.10.2023 %9 Implementation Report %J JMIR Med Inform %G English %X Background: Yaoundé Central Hospital (YCH), located in the capital of Cameroon, is one of the leading referral hospitals in Cameroon. The hospital has several departments, including the Department of Gynecology-Obstetrics (hereinafter referred to as “the Maternity”). This clinical department has faced numerous problems with clinical information management, including the lack of high-quality and reliable clinical information, lack of access to this information, and poor use of this information. Objective: We aim to improve the management of clinical information generated at the Maternity at YCH and to describe the challenges, success factors, and lessons learned during its implementation and use. Methods: Based on an open-source hospital information system (HIS), this intervention implemented a clinical information system (CIS) at the Maternity at YCH and was carried out using the HERMES model—the first part aimed to cover outpatient consultations, billing, and cash management of the Maternity. Geneva University Hospitals supported this project, and several outcomes were measured at the end. The following outcomes were assessed: project management, technical and organizational aspects, leadership, change management, user training, and system use. Implementation (Results): The first part of the project was completed, and the CIS was deployed in the Maternity at YCH. The main technical activities were adapting the open-source HIS to manage outpatient consultations and develop integrated billing and cash management software. In addition to technical aspects, we implemented several other activities. They consisted of the implementation of appropriate project governance or management, improvement of the organizational processes at the Maternity, promotion of the local digital health leadership and performance of change management, and implementation of the training and support of users. Despite barriers encountered during the project, the 6-month evaluation showed that the CIS was effectively used during the first 6 months. Conclusions: Implementation of the HIS or CIS is feasible in a resource-limited setting such as Cameroon. The CIS was implemented based on good practices at the Maternity at YCH. This project had successes but also many challenges. Beyond project management and technical and financial aspects, the other main problems of implementing health information systems or HISs in Africa lie in digital health leadership, governance, and change management. This digital health leadership, governance, and change management should prioritize data as a tool for improving productivity and managing health institutions, and promote a data culture among health professionals to support a change in mindset and the acquisition of information management skills. Moreover, in countries with a highly centralized political system like ours, a high-level strategic and political anchor for such projects is often necessary to guarantee their success. %M 37851502 %R 10.2196/48256 %U https://medinform.jmir.org/2023/1/e48256 %U https://doi.org/10.2196/48256 %U http://www.ncbi.nlm.nih.gov/pubmed/37851502 %0 Journal Article %@ 2561-6722 %I JMIR Publications %V 6 %N %P e47663 %T Health Care Professionals’ Experiences and Views of eHealth in Pediatric Care: Qualitative Interview Study Applying a Theoretical Framework for Implementation %A Castor,Charlotte %A Lindkvist,Rose-Marie %A Hallström,Inger Kristensson %A Holmberg,Robert %+ Department of Health Sciences, Lund University, Box 117, Sölvegatan 19, Lund, 22100, Sweden, 46 703668523, charlotte.castor@med.lu.se %K communication %K digital %K experiences %K eHealth %K health care professionals %K implementation %K NASSS %K pediatric care %D 2023 %7 18.10.2023 %9 Original Paper %J JMIR Pediatr Parent %G English %X Background: The development and evaluation of eHealth interventions in clinical care should be accompanied by a thorough assessment of their implementation. The NASSS (Non-adoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies) framework was designed to facilitate the implementation and scale-up of health technology programs, providing an option for analyzing the progression of these initiatives as they are implemented in real-time. Considering health care provider perspectives within the framework for implementation offers valuable insights into the early identification of barriers and facilitators in the implementation of potentially effective eHealth innovations. Nevertheless, there is a dearth of studies on eHealth interventions that encompass longer time frames and delve into the complexities of scaling up and sustaining such interventions within real-world health care environments. Objective: This study aims to investigate the perspectives and insights of health care professionals (HCPs) regarding the implementation of an eHealth intervention in pediatric health care while applying the NASSS framework to theorize and evaluate the conditions influencing the implementation of eHealth solutions. Methods: Semistructured interviews were performed with health care providers, including both staff and management personnel, within a university pediatric hospital (N=10). The data collection process occurred concurrently with a clinical trial focused on developing and assessing an eHealth app for self-management in pediatric care following hospital discharge. Using an abductive approach, the interviews were initially analyzed qualitatively and subsequently mapped onto the 7 domains of the NASSS framework to identify factors influencing implementation, encompassing facilitators, barriers, and varying levels of complexity. Results: In the realm of pediatric care, the family was identified as the primary unit of care, and patient heterogeneity was a prominent feature. The implementation of eHealth tools, while deemed usable and flexible, was also seen as a delicate balance between safety and adaptability, highlighting challenges related to health care integration. Child participation and secrecy, especially for adolescents, contributed to the complexity of using eHealth. HCPs had high eHealth literacy, and thus challenges concerning adoption were related to work adaptations and the risk of “app overload.” The readiness for implementation was experienced as induced through the research study and the pandemic situation. However, to move from research to implementation in clinical practice, organizational challenges identified a need to update the concept of care and ensure activity measurements. In a wider context, HCPs raised concerns related to regulatory requirements for documentation, public procurement, and data safety. Implementation became more complex due to a lack of overview in a large organization. Conclusions: Important perspectives for implementation were considerations of regulatory requirements, as well as the need for a shared vision of eHealth and the establishment of eHealth-related work as part of regular health care. Key contextual factors that support reach and impact are communication channels between different levels at the hospital and a need for paths and procedures compatible with legal, technological, and security concerns. Further research should focus on how eHealth interventions are perceived by children, adolescents, their parents, and other stakeholders. Trial Registration: ClinicalTrials.gov NCT04150120; https://clinicaltrials.gov/ct2/show/NCT04150120 %M 37851500 %R 10.2196/47663 %U https://pediatrics.jmir.org/2023/1/e47663 %U https://doi.org/10.2196/47663 %U http://www.ncbi.nlm.nih.gov/pubmed/37851500 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 11 %N %P e49995 %T Comparison of Diagnostic and Triage Accuracy of Ada Health and WebMD Symptom Checkers, ChatGPT, and Physicians for Patients in an Emergency Department: Clinical Data Analysis Study %A Fraser,Hamish %A Crossland,Daven %A Bacher,Ian %A Ranney,Megan %A Madsen,Tracy %A Hilliard,Ross %+ Brown Center for Biomedical Informatics, The Warren Alpert Medical School of Brown University, 233 Richmond Street, Providence, RI, 02912, United States, 1 401863 1815, hamish_fraser@brown.edu %K diagnosis %K triage %K symptom checker %K emergency patient %K ChatGPT %K LLM %K diagnose %K self-diagnose %K self-diagnosis %K app %K application %K language model %K accuracy %K ChatGPT-3.5 %K ChatGPT-4.0 %K emergency %K machine learning %D 2023 %7 3.10.2023 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Diagnosis is a core component of effective health care, but misdiagnosis is common and can put patients at risk. Diagnostic decision support systems can play a role in improving diagnosis by physicians and other health care workers. Symptom checkers (SCs) have been designed to improve diagnosis and triage (ie, which level of care to seek) by patients. Objective: The aim of this study was to evaluate the performance of the new large language model ChatGPT (versions 3.5 and 4.0), the widely used WebMD SC, and an SC developed by Ada Health in the diagnosis and triage of patients with urgent or emergent clinical problems compared with the final emergency department (ED) diagnoses and physician reviews. Methods: We used previously collected, deidentified, self-report data from 40 patients presenting to an ED for care who used the Ada SC to record their symptoms prior to seeing the ED physician. Deidentified data were entered into ChatGPT versions 3.5 and 4.0 and WebMD by a research assistant blinded to diagnoses and triage. Diagnoses from all 4 systems were compared with the previously abstracted final diagnoses in the ED as well as with diagnoses and triage recommendations from three independent board-certified ED physicians who had blindly reviewed the self-report clinical data from Ada. Diagnostic accuracy was calculated as the proportion of the diagnoses from ChatGPT, Ada SC, WebMD SC, and the independent physicians that matched at least one ED diagnosis (stratified as top 1 or top 3). Triage accuracy was calculated as the number of recommendations from ChatGPT, WebMD, or Ada that agreed with at least 2 of the independent physicians or were rated “unsafe” or “too cautious.” Results: Overall, 30 and 37 cases had sufficient data for diagnostic and triage analysis, respectively. The rate of top-1 diagnosis matches for Ada, ChatGPT 3.5, ChatGPT 4.0, and WebMD was 9 (30%), 12 (40%), 10 (33%), and 12 (40%), respectively, with a mean rate of 47% for the physicians. The rate of top-3 diagnostic matches for Ada, ChatGPT 3.5, ChatGPT 4.0, and WebMD was 19 (63%), 19 (63%), 15 (50%), and 17 (57%), respectively, with a mean rate of 69% for physicians. The distribution of triage results for Ada was 62% (n=23) agree, 14% unsafe (n=5), and 24% (n=9) too cautious; that for ChatGPT 3.5 was 59% (n=22) agree, 41% (n=15) unsafe, and 0% (n=0) too cautious; that for ChatGPT 4.0 was 76% (n=28) agree, 22% (n=8) unsafe, and 3% (n=1) too cautious; and that for WebMD was 70% (n=26) agree, 19% (n=7) unsafe, and 11% (n=4) too cautious. The unsafe triage rate for ChatGPT 3.5 (41%) was significantly higher (P=.009) than that of Ada (14%). Conclusions: ChatGPT 3.5 had high diagnostic accuracy but a high unsafe triage rate. ChatGPT 4.0 had the poorest diagnostic accuracy, but a lower unsafe triage rate and the highest triage agreement with the physicians. The Ada and WebMD SCs performed better overall than ChatGPT. Unsupervised patient use of ChatGPT for diagnosis and triage is not recommended without improvements to triage accuracy and extensive clinical evaluation. %M 37788063 %R 10.2196/49995 %U https://mhealth.jmir.org/2023/1/e49995 %U https://doi.org/10.2196/49995 %U http://www.ncbi.nlm.nih.gov/pubmed/37788063 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 12 %N %P e41409 %T Outsourcing the Management of Reusable Medical Devices in a Chain-Wide Care Setting: Mixed Methods Feasibility Study %A Noort,Bart A C %A Buijs,Paul %A Roemeling,Oskar %+ Department of Operations, Faculty of Economics and Business, University of Groningen, Nettelbosje 2, Groningen, 9747 AE, Netherlands, 31 631986866, a.c.noort@rug.nl %K health care logistics %K outsourcing %K web ordering portal %K medical devices %K feasibility study %K device management %D 2023 %7 19.9.2023 %9 Original Paper %J Interact J Med Res %G English %X Background: Managing reusable medical devices incurs substantial health care costs and complexity, particularly in integrated care settings. This complexity hampers care quality, safety, and costs. Studying logistical innovations within integrated care can provide insights to medical devices use among staff effectively. Objective: This study aimed to establish the feasibility of a logistical intervention through outsourcing and a web portal. The goal was to provide insights into users’ acceptability of the intervention, on whether the intervention was successfully implemented, and on the intervention’s preliminary efficacy, thus benefiting practitioners and researchers. Methods: This paper presents a mixed methods feasibility study at a large chain-wide health care provider in the Netherlands. The intervention entailed outsourcing noncritical reusable medical devices and introducing a web portal for device management. A questionnaire gauged perceived ordering and delivery times, satisfaction with the ordering and delivery process, compliance with safety and hygiene certification, and effects on the care delivery process. Qualitative data in the form of observations, documentation, and interviews were used to identify implementing challenges. Using on-site stocktaking and data from information systems, we analyzed the utilization, costs, and rental time of medical devices before and after the intervention for wheelchairs and anti–pressure ulcer mattresses. Results: Looking at the acceptability of the intervention, a high user satisfaction with the ordering and delivery process was reported (rated on a 5-point Likert scale). With respect to preliminary efficacy, we noted a reduction in the utilization of wheelchairs (on average, 1106, SD 106 fewer utilization d/mo), and a halted increase in the utilization of anti–pressure ulcer mattresses. In addition, nurses who used the web portal reported shorter ordering times for wheelchairs (−2.7 min) and anti–pressure ulcer mattresses (−3.1 min), as well as shorter delivery times for wheelchairs (−0.5 d). Moreover, an increase in device certification was reported (average score of 1.9, SD 1.0), indicating higher levels of safety and hygiene standards. In theory, these improvements should translate into better outcomes in terms of costs and the quality of care. However, we were unable to establish a reduction in total care costs or a reduced rental time per device. Furthermore, respondents did not identify improvements in safety or the quality of care. Although implementation challenges related to the diverse supply base and complexities with different care financers were observed, the overall implementation of the intervention was considered successful. Conclusions: This study confirms the feasibility of our intervention, in terms of acceptability, implementation success, and preliminary efficacy. The integrated management of medical devices should enable a reduction in costs, required devices, and material waste, as well as higher quality care. However, several challenges remain related to the implementation of such interventions. %M 37725420 %R 10.2196/41409 %U https://www.i-jmr.org/2023/1/e41409 %U https://doi.org/10.2196/41409 %U http://www.ncbi.nlm.nih.gov/pubmed/37725420 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e44759 %T The Current Status of the Use of Internet Hospitals for Outpatients With Pain: Retrospective Study %A Sang,Ling %A Song,Li %+ Department of Pain Management, West China Hospital, Sichuan University, No 37 Guoxue Xiang, Wuhou District, Chengdu, 610041, China, 86 18980601501, song_li76@163.com %K internet hospital %K internet + %K pain management %K online visit %K outpatient %K pain %D 2023 %7 11.9.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: The national “Internet +” policies and the emergence of internet hospitals have created a new direction for the management of pain outside of the hospital. Nevertheless, there are no consolidated studies conducted by pain physicians on the current state of internet hospital–based online medical services used by patients with pain outside of a hospital setting. Objective: In this retrospective study, we aimed to examine the status of the use of internet hospitals by patients who experience pain. Moreover, we identified the factors that influenced patients' decisions to make an online visit through the internet hospital. Methods: Detailed information was collected online and offline from outpatients with pain at the information technology center of West China Hospital of Sichuan University from February 2020 to April 2022. Binary logistic regression analysis was conducted to identify the determinants that influenced patients' decisions to make an online visit to the internet hospital. Results: Over a 2-year period, 85,266 pain-related clinic visits were recorded. Ultimately, 39,260 patients were enrolled for the analysis, with 12.9% (5088/39,260) having online visits. Both online and offline clinics had a greater number of visits by women than men. The average age of patients attending the online clinic was 46.85 (SD 16.56) years, whereas the average age of patients attending the offline clinic was 51.48 (SD 16.12) years. The majority of online clinic visitors (3059/5088, 60.1%) were employed, and one of the most common occupations was farming (721/5088, 14.2%). In addition, 51.8% (2635/5088) of patients who participated in the online clinics lived outside the hospital vicinity. Young (odds ratio [OR] 1.35, 95% CI 1.01-1.81; P=.045) and middle-aged (OR 1.98, 95% CI 1.81-2.16; P<.001) patients, employed patients (OR 1.11, 95% CI 1.04-1.18; P=.002), nonlocal patients (OR 1.57, 95% CI 1.48-1.67; P<.001), and the ordinary staff (OR 1.19, 95%CI 1.01-1.39; P=.03) were more likely to have the intention to choose online visits through the internet hospitals. Conclusions: Internet hospitals are flourishing as a more efficient and promising method of pain management and follow-up for patients with pain outside the hospital. People with pain who are young, working, and not in the vicinity of hospitals are more likely to visit internet hospitals. %M 37695652 %R 10.2196/44759 %U https://www.jmir.org/2023/1/e44759 %U https://doi.org/10.2196/44759 %U http://www.ncbi.nlm.nih.gov/pubmed/37695652 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e47335 %T Barriers and Enablers for Implementation of an Artificial Intelligence–Based Decision Support Tool to Reduce the Risk of Readmission of Patients With Heart Failure: Stakeholder Interviews %A Nair,Monika %A Andersson,Jonas %A Nygren,Jens M %A Lundgren,Lina E %+ School of Business, Innovation and Sustainability, Halmstad University, Kristian IV:s väg 3, Halmstad, 30118, Sweden, 46 707227544, lina.lundgren@hh.se %K implementation %K AI systems %K health care %K interviews %K artificial Intelligence %K AI %K decision support tool %K readmission %K prediction %K heart failure %K digital tool %D 2023 %7 23.8.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Artificial intelligence (AI) applications in health care are expected to provide value for health care organizations, professionals, and patients. However, the implementation of such systems should be carefully planned and organized in order to ensure quality, safety, and acceptance. The gathered view of different stakeholders is a great source of information to understand the barriers and enablers for implementation in a specific context. Objective: This study aimed to understand the context and stakeholder perspectives related to the future implementation of a clinical decision support system for predicting readmissions of patients with heart failure. The study was part of a larger project involving model development, interface design, and implementation planning of the system. Methods: Interviews were held with 12 stakeholders from the regional and municipal health care organizations to gather their views on the potential effects implementation of such a decision support system could have as well as barriers and enablers for implementation. Data were analyzed based on the categories defined in the nonadoption, abandonment, scale-up, spread, sustainability (NASSS) framework. Results: Stakeholders had in general a positive attitude and curiosity toward AI-based decision support systems, and mentioned several barriers and enablers based on the experiences of previous implementations of information technology systems. Central aspects to consider for the proposed clinical decision support system were design aspects, access to information throughout the care process, and integration into the clinical workflow. The implementation of such a system could lead to a number of effects related to both clinical outcomes as well as resource allocation, which are all important to address in the planning of implementation. Stakeholders saw, however, value in several aspects of implementing such system, emphasizing the increased quality of life for those patients who can avoid being hospitalized. Conclusions: Several ideas were put forward on how the proposed AI system would potentially affect and provide value for patients, professionals, and the organization, and implementation aspects were important parts of that. A successful system can help clinicians to prioritize the need for different types of treatments but also be used for planning purposes within the hospital. However, the system needs not only technological and clinical precision but also a carefully planned implementation process. Such a process should take into consideration the aspects related to all the categories in the NASSS framework. This study further highlighted the importance to study stakeholder needs early in the process of development, design, and implementation of decision support systems, as the data revealed new information on the potential use of the system and the placement of the application in the care process. %M 37610799 %R 10.2196/47335 %U https://formative.jmir.org/2023/1/e47335 %U https://doi.org/10.2196/47335 %U http://www.ncbi.nlm.nih.gov/pubmed/37610799 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 12 %N %P e48155 %T Clinical Integration of Digital Patient-Reported Outcome Measures in Primary Health Care for Chronic Disease Management: Protocol for a Systematic Review %A Sasseville,Maxime %A Supper,Wilfried %A Gartner,Jean-Baptiste %A Layani,Géraldine %A Amil,Samira %A Sheffield,Peter %A Gagnon,Marie-Pierre %A Hudon,Catherine %A Lambert,Sylvie %A Attisso,Eugène %A Bureau Lagarde,Victoria %A Breton,Mylaine %A Poitras,Marie-Eve %A Pluye,Pierre %A Roux-Levy,Pierre-Henri %A Plaisimond,James %A Bergeron,Frédéric %A Ashcroft,Rachelle %A Wong,Sabrina %A Groulx,Antoine %A Beaudet,Nicolas %A Paquette,Jean-Sébastien %A D'Anjou,Natasha %A Langlois,Sylviane %A LeBlanc,Annie %+ Université Laval, 1050, rue de la Médecine, Québec, QC, G1V 0A6, Canada, 1 418 656 2131, maxime.sasseville@fsi.ulaval.ca %K systematic review %K patient-reported outcome measure %K primary healthcare %K health care %K implementation science %D 2023 %7 18.8.2023 %9 Protocol %J JMIR Res Protoc %G English %X Background: Health measurement guides policies and health care decisions are necessary to describe and attain the quintuple aim of improving patient experience, population health, care team well-being, health care costs, and equity. In the primary care setting, patient-reported outcome measurement allows outcome comparisons within and across settings and helps improve the clinical management of patients. However, these digital patient-reported outcome measures (PROMs) are still not adapted to the clinical context of primary health care, which is an indication of the complexity of integrating these tools in this context. We must then gather evidence of their impact on chronic disease management in primary health care and understand the characteristics of effective implementation. Objective: We will conduct a systematic review to identify and assess the impact of electronic PROMs (ePROMs) implementation in primary health care for chronic disease management. Our specific objectives are to (1) determine the impact of ePROMs in primary health care for chronic disease management and (2) compare and contrast characteristics of effective ePROMs’ implementation strategies. Methods: We will conduct a systematic review of the literature in accordance with the guidelines of the Cochrane Methods Group and in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for its reporting. A specific search strategy was developed for relevant databases to identify studies. Two reviewers will independently apply the inclusion criteria using full texts and will extract the data. We will use a 2-phase sequential mixed methods synthesis design by conducting a qualitative synthesis first, and use its results to perform a quantitative synthesis. Results: This study was initiated in June 2022 by assembling the research team and the knowledge transfer committee. The preliminary search strategy will be developed and completed in September 2022. The main search strategy, data collection, study selection, and application of inclusion criteria were completed between October and December 2022. Conclusions: Results from this review will help support implementation efforts to accelerate innovations and digital adoption for primary health care and will be relevant for improving clinical management of chronic diseases and health care services and policies. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42022333513; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=333513 International Registered Report Identifier (IRRID): DERR1-10.2196/48155 %M 37594780 %R 10.2196/48155 %U https://www.researchprotocols.org/2023/1/e48155 %U https://doi.org/10.2196/48155 %U http://www.ncbi.nlm.nih.gov/pubmed/37594780 %0 Journal Article %@ 2369-2529 %I JMIR Publications %V 10 %N %P e41359 %T Methodologies for Evaluating the Usability of Rehabilitation Technologies Aimed at Supporting Shared Decision-Making: Scoping Review %A Alhasani,Rehab %A George,Nicole %A Radman,Dennis %A Auger,Claudine %A Ahmed,Sara %+ School of Physical and Occupation Therapy, Faculty of Medicine, McGill University, 845 Sherbrooke Street West, Montreal, QC, H3A 0G4, Canada, 1 514 398 4400 ext 00531, sara.ahmed@mcgill.ca %K usability %K technology %K rehabilitation %K shared decision-making %K mobile phone %D 2023 %7 15.8.2023 %9 Review %J JMIR Rehabil Assist Technol %G English %X Background: The field of rehabilitation has seen a recent rise in technologies to support shared decision-making (SDM). Usability testing during the design process of SDM technologies is needed to optimize adoption and realize potential benefits. There is variability in how usability is defined and measured. Given the complexity of usability, a thorough examination of the methodologies used to measure usability to develop the SDM technologies used in rehabilitation care is needed. Objective: This scoping review aims to answer the following research questions: which methods and measures have been used to produce knowledge about the usability of rehabilitation technologies aimed at supporting SDM at the different phases of development and implementation? Which parameters of usability have been measured and reported? Methods: This review followed the Arksey and O’Malley framework. An electronic search was performed in the Ovid MEDLINE, Embase, CINAHL, and PsycINFO databases from January 2005 up to November 2020. In total, 2 independent reviewers screened all retrieved titles, abstracts, and full texts according to the inclusion criteria and extracted the data. The International Organization for Standardization framework was used to define the scope of usability (effectiveness, efficiency, and satisfaction). The characteristics of the studies were outlined in a descriptive summary. Findings were categorized based on usability parameters, technology interventions, and measures of usability. Results: A total of 38 articles were included. The most common SDM technologies were web-based aids (15/33, 46%). The usability of SDM technologies was assessed during development, preimplementation, or implementation, using 14 different methods. The most frequent methods were questionnaires (24/38, 63%) and semistructured interviews (16/38, 42%). Satisfaction (27/38, 71%) was the most common usability parameter mapped to types of SDM technologies and usability evaluation methods. User-centered design (9/15, 60%) was the most frequently used technology design framework. Conclusions: The results from this scoping review highlight the importance and the complexity of usability evaluation. Although various methods and measures were shown to be used to evaluate the usability of technologies to support SDM in rehabilitation, very few evaluations used in the included studies were found to adequately span the selected usability domains. This review identified gaps in usability evaluation, as most studies (24/38, 63%) relied solely on questionnaires rather than multiple methods, and most questionnaires simply focused on the usability parameter of satisfaction. The consideration of end users (such as patients and clinicians) is of particular importance for the development of technologies to support SDM, as the process of SDM itself aims to improve patient-centered care and integrate both patient and clinician voices into their rehabilitation care. %M 37581911 %R 10.2196/41359 %U https://rehab.jmir.org/2023/1/e41359 %U https://doi.org/10.2196/41359 %U http://www.ncbi.nlm.nih.gov/pubmed/37581911 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e39525 %T Patients’ Experiences Using a Mobile Health App for Self-Care of Heart Failure in a Real-World Setting: Qualitative Analysis %A Madujibeya,Ifeanyi %A Lennie,Terry A %A Pelzel,Jamie %A Moser,Debra K %+ Research and Interventions for Cardiovascular Health Heart Program, College of Nursing, University of Kentucky, 751 Rose Street, Lexington, KY, 40536, United States, 1 8593340561, ima232@uky.edu %K heart failure %K patients’ experiences %K experience %K satisfaction %K facilitator %K mobile health apps %K mobile app %K health app %K app feature %K mobile health %K cardiology %K cardiovascular %K patient care %K self-management %K patient %K heart %K mHealth %K self-care %K medication %K performance %K feedback %K personalized %D 2023 %7 15.8.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: Publicly available patient-focused mobile health (mHealth) apps are being increasingly integrated into routine heart failure (HF)–related self-care. However, there is a dearth of research on patients’ experiences using mHealth apps for self-care in real-world settings. Objective: The purpose of this study was to explore patients’ experiences using a commercially available mHealth app, OnTrack to Health, for HF self-care in a real-world setting. Methods: Patient satisfaction, measured with a 5-point Likert scale, and an open-ended survey were used to gather data from 23 patients with HF who were provided the OnTrack to Health app as a part of routine HF management. A content analysis of patients’ responses was conducted with the qualitative software Atlas.ti (version 8; ATLAS.ti Scientific Software Development GmbH). Results: Patients (median age 64, IQR 57-71 years; 17/23, 74% male) used OnTrack to Health for a median 164 (IQR 51-640) days before the survey. All patients reported excellent experiences related to app use and would recommend the app to other patients with HF. Five themes emerged from the responses to the open-ended questions: (1) features that enhanced self-care of HF (medication tracker, graphic performance feedback and automated alerts, secured messaging features, and HF self-care education); (2) perceived benefits (provided assurance of safety, improved HF self-care, and decreased hospitalization rates); (3) challenges with using apps for self-care (giving up previous self-care strategies); (4) facilitators (perceived ease of use and availability of technical support); and (5) suggested improvements (streamlining data entry, integration of apps with an electronic medical record, and personalization of app features). Conclusions: Patients were satisfied with using OnTrack to Health for self-care. They perceived the features of the app as valuable tools for improving self-care ability and decreasing hospitalization rates. The development of apps in collaboration with end users is essential to ensure high-quality patient experiences related to app use for self-care. %M 37581912 %R 10.2196/39525 %U https://formative.jmir.org/2023/1/e39525 %U https://doi.org/10.2196/39525 %U http://www.ncbi.nlm.nih.gov/pubmed/37581912 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 12 %N %P e48801 %T Using Presurgical Biopsychosocial Features to Develop an Advanced Clinical Decision-Making Support Tool for Predicting Recovery Trajectories in Patients Undergoing Total Knee Arthroplasty: Protocol for a Prospective Observational Study %A Ribbons,Karen %A Johnson,Sarah %A Ditton,Elizabeth %A Wills,Adrian %A Mason,Gillian %A Flynn,Traci %A Cochrane,Jodie %A Pollack,Michael %A Walker,Frederick Rohan %A Nilsson,Michael %+ Centre for Rehab Innovations, University of Newcastle, Kookaburra Circuit, New Lambton Heights, 2305, Australia, 61 240420758, karen.ribbons@newcastle.edu.au %K biopsychosocial %K total knee arthroplasty %K prospective %K recovery trajectories %K patient-reported outcomes %K predictive clinical decision tool %K clinical decision support %K knee arthroplasty %K rehabilitation %K psychosocial %K patient-reported outcome %K quality of life %K patient recruitment %K presurgery %K patient stratification %D 2023 %7 9.8.2023 %9 Protocol %J JMIR Res Protoc %G English %X Background: Following total knee arthroplasty (TKA), 10% to 20% of patients report dissatisfaction with procedural outcomes. There is growing recognition that postsurgical satisfaction is shaped not only by the quality of surgery but also by psychological and social factors. Surprisingly, information on the psychological and social determinants of surgical outcomes is rarely collected before surgery. A comprehensive collection of biopsychosocial information could assist clinicians in making recommendations in relation to rehabilitation, particularly if there is robust evidence to support the ability of presurgical constructs to predict postsurgical outcomes. Clinical decision support tools can help identify factors influencing patient outcomes and support the provision of interventions or services that can be tailored to meet individuals’ needs. However, despite their potential clinical benefit, the application of such tools remains limited. Objective: This study aims to develop a clinical decision tool that will assist with patient stratification and more precisely targeted clinical decision-making regarding prehabilitation and rehabilitation for TKA, based on the identified individual biopsychosocial needs. Methods: In this prospective observational study, all participants provided written or electronic consent before study commencement. Patient-completed questionnaires captured information related to a broad range of biopsychosocial parameters during the month preceding TKA. These included demographic factors (sex, age, and rurality), psychological factors (mood status, pain catastrophizing, resilience, and committed action), quality of life, social support, lifestyle factors, and knee symptoms. Physical measures assessing mobility, balance, and functional lower body strength were performed via video calls with patients in their home. Information related to preexisting health issues and concomitant medications was derived from hospital medical records. Patient recovery outcomes were assessed 3 months after the surgical procedure and included quality of life, patient-reported knee symptoms, satisfaction with the surgical procedure, and mood status. Machine learning data analysis techniques will be applied to determine which presurgery parameters have the strongest power for predicting patient recovery following total knee replacement. On the basis of these analyses, a predictive model will be developed. Predictive models will undergo internal validation, and Bayesian analysis will be applied to provide additional metrics regarding prediction accuracy. Results: Patient recruitment and data collection commenced in November 2019 and was completed in June 2022. A total of 1050 patients who underwent TKA were enrolled in this study. Conclusions: Our findings will facilitate the development of the first comprehensive biopsychosocial prediction tool, which has the potential to objectively predict a patient’s individual recovery outcomes following TKA once selected by an orthopedic surgeon to undergo TKA. If successful, the tool could also inform the evolution rehabilitation services, such that factors in addition to physical performance can be addressed and have the potential to further enhance patient recovery and satisfaction. International Registered Report Identifier (IRRID): DERR1-10.2196/48801 %M 37556181 %R 10.2196/48801 %U https://www.researchprotocols.org/2023/1/e48801 %U https://doi.org/10.2196/48801 %U http://www.ncbi.nlm.nih.gov/pubmed/37556181 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e46421 %T Effects of Excluding Those Who Report Having “Syndomitis” or “Chekalism” on Data Quality: Longitudinal Health Survey of a Sample From Amazon’s Mechanical Turk %A Hays,Ron D %A Qureshi,Nabeel %A Herman,Patricia M %A Rodriguez,Anthony %A Kapteyn,Arie %A Edelen,Maria Orlando %+ Division of General Internal Medicine and Health Services Research, Department of Medicine, University of California, 1100 Glendon Avenue Suite 800, Los Angeles, CA, 90024, United States, 1 310 794 2294, drhays@ucla.edu %K misrepresentation %K survey %K data quality %K MTurk %K Amazon Mechanical Turk %D 2023 %7 4.8.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Researchers have implemented multiple approaches to increase data quality from existing web-based panels such as Amazon’s Mechanical Turk (MTurk). Objective: This study extends prior work by examining improvements in data quality and effects on mean estimates of health status by excluding respondents who endorse 1 or both of 2 fake health conditions (“Syndomitis” and “Chekalism”). Methods: Survey data were collected in 2021 at baseline and 3 months later from MTurk study participants, aged 18 years or older, with an internet protocol address in the United States, and who had completed a minimum of 500 previous MTurk “human intelligence tasks.” We included questions about demographic characteristics, health conditions (including the 2 fake conditions), and the Patient Reported Outcomes Measurement Information System (PROMIS)-29+2 (version 2.1) preference–based score survey. The 3-month follow-up survey was only administered to those who reported having back pain and did not endorse a fake condition at baseline. Results: In total, 15% (996/6832) of the sample endorsed at least 1 of the 2 fake conditions at baseline. Those who endorsed a fake condition at baseline were more likely to identify as male, non-White, younger, report more health conditions, and take longer to complete the survey than those who did not endorse a fake condition. They also had substantially lower internal consistency reliability on the PROMIS-29+2 scales than those who did not endorse a fake condition: physical function (0.69 vs 0.89), pain interference (0.80 vs 0.94), fatigue (0.80 vs 0.92), depression (0.78 vs 0.92), anxiety (0.78 vs 0.90), sleep disturbance (−0.27 vs 0.84), ability to participate in social roles and activities (0.77 vs 0.92), and cognitive function (0.65 vs 0.77). The lack of reliability of the sleep disturbance scale for those endorsing a fake condition was because it includes both positively and negatively worded items. Those who reported a fake condition reported significantly worse self-reported health scores (except for sleep disturbance) than those who did not endorse a fake condition. Excluding those who endorsed a fake condition improved the overall mean PROMIS-29+2 (version 2.1) T-scores by 1-2 points and the PROMIS preference–based score by 0.04. Although they did not endorse a fake condition at baseline, 6% (n=59) of them endorsed at least 1 of them on the 3-month survey and they had lower PROMIS-29+2 score internal consistency reliability and worse mean scores on the 3-month survey than those who did not report having a fake condition. Based on these results, we estimate that 25% (1708/6832) of the MTurk respondents provided careless or dishonest responses. Conclusions: This study provides evidence that asking about fake health conditions can help to screen out respondents who may be dishonest or careless. We recommend this approach be used routinely in samples of members of MTurk. %M 37540543 %R 10.2196/46421 %U https://www.jmir.org/2023/1/e46421 %U https://doi.org/10.2196/46421 %U http://www.ncbi.nlm.nih.gov/pubmed/37540543 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e42649 %T Involving Health Professionals in the Development of Quality and Safety Dashboards: Qualitative Study %A van de Baan,Frank Christian %A Lambregts,Stijn %A Bergman,Esther %A Most,Jasper %A Westra,Daan %+ Department of Health Services Research, Care and Public Health Research Institute, Maastricht University, Duboisdomein 30, Maastricht, 6229GT, Netherlands, 31 043 38 81 553, f.vandebaan@maastrichtuniversity.nl %K quality improvement %K dashboard %K user involvement %K innovation %K health care provider %K health care professional %K feedback %K opinion %K perspective %K qualitative %K constant comparative method %D 2023 %7 12.6.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Dashboards are an important tool for hospitals to improve quality and safety performance. However, implementing quality and safety dashboards often does not increase performance due to a lack of use by health professionals. Including health professionals in the development process of quality and safety dashboards can improve their use in practice. Yet, it remains unclear how a development process involving health professionals can be executed successfully. Objective: The aim of this study is twofold: (1) to delineate how a process whereby health professionals are included in the development of quality and safety dashboards can be facilitated and (2) to identify the factors that are important to consider in order to make that process successful. Methods: We conducted a qualitative, in-depth exploratory case study in which we analyzed 150 pages of internal documents and interviewed 13 staff members regarding the development of quality and safety dashboards within 2 care pathways of a hospital that has experience in such development. The data were analyzed inductively using the constant comparative method. Results: We found that the development of quality and safety dashboards in collaboration with health professionals was facilitated through a five-stage process: (1) familiarizing participants with dashboards and the development process; (2) brainstorming about potential indicators to be included in the dashboard; (3) prioritizing, defining, and selecting indicators to be included in the dashboard; (4) examining how the indicators can be visualized; and (5) implementing the dashboard and following up on its use. To enhance the success of the process, 3 factors were deemed important. The first is to create and maintain broad involvement, ensuring that various professions are represented and take ownership of the dashboard. Here, potential barriers include gaining engagement from peers not directly involved in the process and maintaining involvement after the initial implementation of the dashboard. Second, unburdening, whereby quality and safety staff facilitate a structured process that has little additional burden for professionals. For this, time management and a lack of collaboration with departments responsible for delivering the data might be an issue. Lastly, focusing on relevance for health professionals, which refers to the inclusion of indicators with value for health professionals. For this factor, a lack of consensus on how indicators should be defined and registered might be a barrier. Conclusions: Health care organizations seeking to develop quality and safety dashboards in collaboration with health professionals can use a 5-stage process. To enhance the success of the process, organizations are advised to focus on 3 key factors. For each of the key factors, potential barriers should be taken into account. Engaging in this process and attaining the key factors could increase the likelihood that the dashboards are used in practice. %M 37307058 %R 10.2196/42649 %U https://www.jmir.org/2023/1/e42649 %U https://doi.org/10.2196/42649 %U http://www.ncbi.nlm.nih.gov/pubmed/37307058 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e47659 %T The Effects of Online Access to General Practice Medical Records Perceived by Patients: Longitudinal Survey Study %A Thielmann,Rosa R L C %A Hoving,Ciska %A Cals,Jochen W L %A Crutzen,Rik %+ School for Public Health and Primary Care, Faculty of Health, Medicine and Life Sciences, Maastricht University, Debyeplein 1, Maastricht, 6226 HA, Netherlands, 31 38 82423, r.thielmann@maastrichtuniversity.nl %K electronic health records %K personal health records %K medical records %K patient access to records %K patient portals %K patient participation %K informed decision-making %K patient empowerment %D 2023 %7 2.6.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Patient online access to medical records is assumed to facilitate patient empowerment and advance patient-centered health care. However, to date, the actual effects of online access to medical records perceived by patients and other outcomes are insufficiently empirically tested. Objective: This study aimed to investigate the effects of online access to medical records on patient empowerment, informed decision-making, and the patient-provider relationship perceived by patients. Methods: A nationwide, 2-wave, longitudinal survey study was conducted among Dutch adults (N=2402). Linear regression analyses were performed. In model 1, the perceived effects of online access to medical records (measured at T1 [first measurement; July 2021]) on 16 outcomes (measured at T2 [second measurement; January 2022]), which were associated with the use of online access to general practice medical records in previous research, were investigated. Model 2 included sociodemographic factors and patient characteristics as confounders. Results: Users indicated more strongly than nonusers that online access to medical records would increase their participation in health care, improve the relationship with their general practitioner, and support informed decision-making. These results were robust when adjusted for the influence of confounders. Effect sizes were very small, with unstandardized regression coefficients (B) ranging between −0.39 and 0.28. Higher digital and health literacy were associated with higher ratings of almost all effects. Conclusions: Online access to medical records has the potential to empower patients and foster informed decision-making among patients. The effects in this study were small but might grow over time. Other factors, such as the attitude of general practitioners toward online access to medical records, might moderate these effects. The results indicate that the potential benefits of online access to medical records might be unevenly distributed. We suggest future exploration of the conditions under which online access to medical records can improve health care system functioning and efficiency without increasing health inequality. %M 37266981 %R 10.2196/47659 %U https://www.jmir.org/2023/1/e47659 %U https://doi.org/10.2196/47659 %U http://www.ncbi.nlm.nih.gov/pubmed/37266981 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e45654 %T A Smart System for Remote Monitoring of Patients in Palliative Care (HumanITcare Platform): Mixed Methods Study %A Castillo Padrós,Manuel Ramón %A Pastor,Nuria %A Altarriba Paracolls,Júlia %A Mosquera Peña,Marcelino %A Pergolizzi,Denise %A Salvador Vergès,Àngels %+ Innohealth Academy, C/Magi Casanovas 11, Barcelona, 08870, Spain, 34 630887995, angels.salvador@innohealth.academy %K palliative care %K advanced illness %K remote monitoring %K eHealth %K telemedicine %K mHealth %D 2023 %7 31.5.2023 %9 Viewpoint %J JMIR Form Res %G English %X Background: Due to the complexities of advanced illnesses and their treatments, it can be difficult for patients in palliative care to maintain their quality of life. Telemedicine interventions in chronic disease management engage patients in their care, provide continuous follow-up by their health care providers, identify symptoms earlier, and allow a quick response to illness-related decline. Objective: We aimed to detail and reflect on the design of an app and evaluate its feasibility to monitor the clinical situation of patients with advanced illnesses. Methods: This study used a mixed methods design using qualitative methods to inform app development and design and quantitative methods for data collection and analysis of patient evaluations. Palliative care units in 2 Spanish university hospitals (Nuestra Señora de la Candelaria in Santa Cruz de Tenerife and University Hospital Complex of Ferrol in A Coruña) carried out a literature review, designed the study protocol, and obtained approval from the Ethics Committee from June to December 2020. In addition, focus group meetings were held, and the design and technical development of the app were elaborated on and subsequently presented in the participating palliative care units. From January to March 2021, the app was made public on the App Store and Play Store, and a pilot study with patients was carried out in April to September 2021. Results: Six focus group meetings were held that included doctors, nurses, app developers, technology consultants, and sponsors. In addition, the technology consultants presented their results 3 times in the participating palliative care units to obtain feedback. After the app’s final design, it was possible to publish it on the usual servers and begin its evaluation in patients (n=60, median age 72 years). Sixty percent (n=36) of the participants were women and 40% (n=24) were men. The most prevalent advanced pathology was cancer (n=46, 76%), followed by other diseases (n=7, 12%) and amyotrophic lateral sclerosis (n=5, 8%). Seventy percent (n=42) of the patients were already in follow-up prior to the start of the study, while 30% (n=18) were included at the start of their follow-up. The information in the app was collected and entered by relatives or caregivers in 60% (n=36) of the cases. The median follow-up was 52 (IQR 14-104) days. In all, 69% (n=41) had a follow-up >30 days (10 were deceased and 9 were missing data). The use of the different sections of the app ranged from 37% (n=22) for the glycemic record to 90% (n=54) for the constipation scale). Patients and caregivers were delighted with its ease of use and usefulness. Conclusions: Incorporating an intelligent remote patient monitoring system in clinical practice for patients in palliative care can improve access to health services and provide more information to professionals. %M 37256664 %R 10.2196/45654 %U https://formative.jmir.org/2023/1/e45654 %U https://doi.org/10.2196/45654 %U http://www.ncbi.nlm.nih.gov/pubmed/37256664 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e43518 %T Factors Influencing Admission Decisions in Skilled Nursing Facilities: Retrospective Quantitative Study %A Strickland,Caroline %A Chi,Nancy %A Ditz,Laura %A Gomez,Luisa %A Wagner,Brittin %A Wang,Stanley %A Lizotte,Daniel J %+ Department of Computer Science, University of Western Ontario, 1151 Richmond St, London, ON, N6A 3K7, Canada, 1 519 661 2111, cstrick4@uwo.ca %K decision-making %K skilled nursing facility %K patient admission %K decision %K nursing %K clinical %K database %K health informatics %K diagnosis %K modeling %K connection %K patient %D 2023 %7 17.5.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Occupancy rates within skilled nursing facilities (SNFs) in the United States have reached a record low. Understanding drivers of occupancy, including admission decisions, is critical for assessing the recovery of the long-term care sector as a whole. We provide the first comprehensive analysis of financial, clinical, and operational factors that impact whether a patient referral to an SNF is accepted or denied, using a large health informatics database. Objective: Our key objectives were to describe the distribution of referrals sent to SNFs in terms of key referral- and facility-level features; analyze key financial, clinical, and operational variables and their relationship to admission decisions; and identify the key potential reasons behind referral decisions in the context of learning health systems. Methods: We extracted and cleaned referral data from 627 SNFs from January 2020 to March 2022, including information on SNF daily operations (occupancy and nursing hours), referral-level factors (insurance type and primary diagnosis), and facility-level factors (overall 5-star rating and urban versus rural status). We computed descriptive statistics and applied regression modeling to identify and describe the relationships between these factors and referral decisions, considering them individually and controlling for other factors to understand their impact on the decision-making process. Results: When analyzing daily operation values, no significant relationship between SNF occupancy or nursing hours and referral acceptance was observed (P>.05). By analyzing referral-level factors, we found that the primary diagnosis category and insurance type of the patient were significantly related to referral acceptance (P<.05). Referrals with primary diagnoses within the category “Diseases of the Musculoskeletal System” are least often denied whereas those with diagnoses within the “Mental Illness” category are most often denied (compared with other diagnosis categories). Furthermore, private insurance holders are least often denied whereas “medicaid” holders are most often denied (compared with other insurance types). When analyzing facility-level factors, we found that the overall 5-star rating and urban versus rural status of an SNF are significantly related to referral acceptance (P<.05). We found a positive but nonmonotonic relationship between the 5-star rating and referral acceptance rates, with the highest acceptance rates found among 5-star facilities. In addition, we found that SNFs in urban areas have lower acceptance rates than their rural counterparts. Conclusions: While many factors may influence a referral acceptance, care challenges associated with individual diagnoses and financial challenges associated with different remuneration types were found to be the strongest drivers. Understanding these drivers is essential in being more intentional in the process of accepting or denying referrals. We have interpreted our results using an adaptive leadership framework and suggested how SNFs can be more purposeful with their decisions while striving to achieve appropriate occupancy levels in ways that meet their goals and patients’ needs. %M 37195755 %R 10.2196/43518 %U https://www.jmir.org/2023/1/e43518 %U https://doi.org/10.2196/43518 %U http://www.ncbi.nlm.nih.gov/pubmed/37195755 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 11 %N %P e44455 %T An Electronic Dashboard to Improve Dosing of Hydroxychloroquine Within the Veterans Health Care System: Time Series Analysis %A Montgomery,Anna %A Tarasovsky,Gary %A Izadi,Zara %A Shiboski,Stephen %A Whooley,Mary A %A Dana,Jo %A Ehiorobo,Iziegbe %A Barton,Jennifer %A Bennett,Lori %A Chung,Lorinda %A Reiter,Kimberly %A Wahl,Elizabeth %A Subash,Meera %A Schmajuk,Gabriela %+ University of California San Francisco, 4150 Clement St, San Francisco, CA, 94121, United States, 1 415 221 4810, Gabriela.schmajuk@ucsf.edu %K medical informatics %K patient safety %K health IT %K hydroxychloroquine %K dashboard %K Veterans Health Administration %K audit and feedback %K electronic health record %D 2023 %7 12.5.2023 %9 Original Paper %J JMIR Med Inform %G English %X Background: Hydroxychloroquine (HCQ) is commonly used for patients with autoimmune conditions. Long-term use of HCQ can cause retinal toxicity, but this risk can be reduced if high doses are avoided. Objective: We developed and piloted an electronic health record–based dashboard to improve the safe prescribing of HCQ within the Veterans Health Administration (VHA). We observed pilot facilities over a 1-year period to determine whether they were able to improve the proportion of patients receiving inappropriate doses of HCQ. Methods: Patients receiving HCQ were identified from the VHA corporate data warehouse. Using PowerBI (Microsoft Corp), we constructed a dashboard to display patient identifiers and the most recent HCQ dose and weight (flagged if ≥5.2 mg/kg/day). Six VHA pilot facilities were enlisted to test the dashboard and invited to participate in monthly webinars. We performed an interrupted time series analysis using synthetic controls to assess changes in the proportion of patients receiving HCQ ≥5.2 mg/kg/day between October 2020 and November 2021. Results: At the start of the study period, we identified 18,525 total users of HCQ nationwide at 128 facilities in the VHA, including 1365 patients at the 6 pilot facilities. Nationwide, at baseline, 19.8% (3671/18,525) of patients were receiving high doses of HCQ. We observed significant improvements in the proportion of HCQ prescribed at doses ≥5.2 mg/kg/day among pilot facilities after the dashboard was deployed (–0.06; 95% CI –0.08 to –0.04). The difference in the postintervention linear trend for pilot versus synthetic controls was also significant (–0.06; 95% CI –0.08 to –0.05). Conclusions: The use of an electronic health record–based dashboard reduced the proportion of patients receiving higher than recommended doses of HCQ and significantly improved performance at 6 VHA facilities. National roll-out of the dashboard will enable further improvements in the safe prescribing of HCQ. %M 37171858 %R 10.2196/44455 %U https://medinform.jmir.org/2023/1/e44455 %U https://doi.org/10.2196/44455 %U http://www.ncbi.nlm.nih.gov/pubmed/37171858 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 10 %N %P e43960 %T Performance of a Web-Based Reference Database With Natural Language Searching Capabilities: Usability Evaluation of DynaMed and Micromedex With Watson %A Rui,Angela %A Garabedian,Pamela M %A Marceau,Marlika %A Syrowatka,Ania %A Volk,Lynn A %A Edrees,Heba H %A Seger,Diane L %A Amato,Mary G %A Cambre,Jacob %A Dulgarian,Sevan %A Newmark,Lisa P %A Nanji,Karen C %A Schultz,Petra %A Jackson,Gretchen Purcell %A Rozenblum,Ronen %A Bates,David W %+ Division of General Internal Medicine, Brigham and Women's Hospital, 75 Francis St, Boston, MA, 02115, United States, 1 978 397 0082, arui@partners.org %K medication safety %K patient safety %K usability %K searching behavior %K efficiency %K quality of care %K web-based databases %K point-of-care information %K POCI %K point-of-care tools %K artificial intelligence %K machine learning %K clinical decision support %K natural language processing %D 2023 %7 17.4.2023 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Evidence-based point-of-care information (POCI) tools can facilitate patient safety and care by helping clinicians to answer disease state and drug information questions in less time and with less effort. However, these tools may also be visually challenging to navigate or lack the comprehensiveness needed to sufficiently address a medical issue. Objective: This study aimed to collect clinicians’ feedback and directly observe their use of the combined POCI tool DynaMed and Micromedex with Watson, now known as DynaMedex. EBSCO partnered with IBM Watson Health, now known as Merative, to develop the combined tool as a resource for clinicians. We aimed to identify areas for refinement based on participant feedback and examine participant perceptions to inform further development. Methods: Participants (N=43) within varying clinical roles and specialties were recruited from Brigham and Women’s Hospital and Massachusetts General Hospital in Boston, Massachusetts, United States, between August 10, 2021, and December 16, 2021, to take part in usability sessions aimed at evaluating the efficiency and effectiveness of, as well as satisfaction with, the DynaMed and Micromedex with Watson tool. Usability testing methods, including think aloud and observations of user behavior, were used to identify challenges regarding the combined tool. Data collection included measurements of time on task; task ease; satisfaction with the answer; posttest feedback on likes, dislikes, and perceived reliability of the tool; and interest in recommending the tool to a colleague. Results: On a 7-point Likert scale, pharmacists rated ease (mean 5.98, SD 1.38) and satisfaction (mean 6.31, SD 1.34) with the combined POCI tool higher than the physicians, nurse practitioner, and physician’s assistants (ease: mean 5.57, SD 1.64, and satisfaction: mean 5.82, SD 1.60). Pharmacists spent longer (mean 2 minutes, 26 seconds, SD 1 minute, 41 seconds) on average finding an answer to their question than the physicians, nurse practitioner, and physician’s assistants (mean 1 minute, 40 seconds, SD 1 minute, 23 seconds). Conclusions: Overall, the tool performed well, but this usability evaluation identified multiple opportunities for improvement that would help inexperienced users. %M 37067858 %R 10.2196/43960 %U https://humanfactors.jmir.org/2023/1/e43960 %U https://doi.org/10.2196/43960 %U http://www.ncbi.nlm.nih.gov/pubmed/37067858 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 7 %N %P e41223 %T Novel Note Templates to Enhance Signal and Reduce Noise in Medical Documentation: Prospective Improvement Study %A Feldman,Jonah %A Goodman,Adam %A Hochman,Katherine %A Chakravartty,Eesha %A Austrian,Jonathan %A Iturrate,Eduardo %A Bosworth,Brian %A Saxena,Archana %A Moussa,Marwa %A Chenouda,Dina %A Volpicelli,Frank %A Adler,Nicole %A Weisstuch,Joseph %A Testa,Paul %+ Department of Medicine, NYU Langone Health, 550 1st avenue, New York, NY, 10016, United States, 1 (212) 263 5800, eesha.chakravartty@nyulangone.org %K medical informatics %K decision support %K hospital data %K clinical documentation %K clinical informatics %D 2023 %7 12.4.2023 %9 Original Paper %J JMIR Form Res %G English %X Background: The introduction of electronic workflows has allowed for the flow of raw uncontextualized clinical data into medical documentation. As a result, many electronic notes have become replete of “noise” and deplete clinically significant “signals.” There is an urgent need to develop and implement innovative approaches in electronic clinical documentation that improve note quality and reduce unnecessary bloating. Objective: This study aims to describe the development and impact of a novel set of templates designed to change the flow of information in medical documentation. Methods: This is a multihospital nonrandomized prospective improvement study conducted on the inpatient general internal medicine service across 3 hospital campuses at the New York University Langone Health System. A group of physician leaders representing each campus met biweekly for 6 months. The output of these meetings included (1) a conceptualization of the note bloat problem as a dysfunction in information flow, (2) a set of guiding principles for organizational documentation improvement, (3) the design and build of novel electronic templates that reduced the flow of extraneous information into provider notes by providing link outs to best practice data visualizations, and (4) a documentation improvement curriculum for inpatient medicine providers. Prior to go-live, pragmatic usability testing was performed with the new progress note template, and the overall user experience was measured using the System Usability Scale (SUS). Primary outcome measures after go-live include template utilization rate and note length in characters. Results: In usability testing among 22 medicine providers, the new progress note template averaged a usability score of 90.6 out of 100 on the SUS. A total of 77% (17/22) of providers strongly agreed that the new template was easy to use, and 64% (14/22) strongly agreed that they would like to use the template frequently. In the 3 months after template implementation, general internal medicine providers wrote 67% (51,431/76,647) of all inpatient notes with the new templates. During this period, the organization saw a 46% (2768/6191), 47% (3505/7819), and 32% (3427/11,226) reduction in note length for general medicine progress notes, consults, and history and physical notes, respectively, when compared to a baseline measurement period prior to interventions. Conclusions: A bundled intervention that included the deployment of novel templates for inpatient general medicine providers significantly reduced average note length on the clinical service. Templates designed to reduce the flow of extraneous information into provider notes performed well during usability testing, and these templates were rapidly adopted across all hospital campuses. Further research is needed to assess the impact of novel templates on note quality, provider efficiency, and patient outcomes. %M 36821760 %R 10.2196/41223 %U https://formative.jmir.org/2023/1/e41223 %U https://doi.org/10.2196/41223 %U http://www.ncbi.nlm.nih.gov/pubmed/36821760 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 11 %N %P e40312 %T Assessment and Improvement of Drug Data Structuredness From Electronic Health Records: Algorithm Development and Validation %A Reinecke,Ines %A Siebel,Joscha %A Fuhrmann,Saskia %A Fischer,Andreas %A Sedlmayr,Martin %A Weidner,Jens %A Bathelt,Franziska %+ Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, Fetscherstraße 74, Dresden, 01307, Germany, 49 35145887 ext 12975, ines.reinecke@uniklinikum-dresden.de %K secondary usage %K Observational Medical Outcomes Partnership %K OMOP %K drug data %K data quality %K Anatomical Therapeutic Chemical %K ATC %K RxNorm %K interoperability %D 2023 %7 25.1.2023 %9 Original Paper %J JMIR Med Inform %G English %X Background: Digitization offers a multitude of opportunities to gain insights into current diagnostics and therapies from retrospective data. In this context, real-world data and their accessibility are of increasing importance to support unbiased and reliable research on big data. However, routinely collected data are not readily usable for research owing to the unstructured nature of health care systems and a lack of interoperability between these systems. This challenge is evident in drug data. Objective: This study aimed to present an approach that identifies and increases the structuredness of drug data while ensuring standardization according to Anatomical Therapeutic Chemical (ATC) classification. Methods: Our approach was based on available drug prescriptions and a drug catalog and consisted of 4 steps. First, we performed an initial analysis of the structuredness of local drug data to define a point of comparison for the effectiveness of the overall approach. Second, we applied 3 algorithms to unstructured data that translated text into ATC codes based on string comparisons in terms of ingredients and product names and performed similarity comparisons based on Levenshtein distance. Third, we validated the results of the 3 algorithms with expert knowledge based on the 1000 most frequently used prescription texts. Fourth, we performed a final validation to determine the increased degree of structuredness. Results: Initially, 47.73% (n=843,980) of 1,768,153 drug prescriptions were classified as structured. With the application of the 3 algorithms, we were able to increase the degree of structuredness to 85.18% (n=1,506,059) based on the 1000 most frequent medication prescriptions. In this regard, the combination of algorithms 1, 2, and 3 resulted in a correctness level of 100% (with 57,264 ATC codes identified), algorithms 1 and 3 resulted in 99.6% (with 152,404 codes identified), and algorithms 1 and 2 resulted in 95.9% (with 39,472 codes identified). Conclusions: As shown in the first analysis steps of our approach, the availability of a product catalog to select during the documentation process is not sufficient to generate structured data. Our 4-step approach reduces the problems and reliably increases the structuredness automatically. Similarity matching shows promising results, particularly for entries with no connection to a product catalog. However, further enhancement of the correctness of such a similarity matching algorithm needs to be investigated in future work. %M 36696159 %R 10.2196/40312 %U https://medinform.jmir.org/2023/1/e40312 %U https://doi.org/10.2196/40312 %U http://www.ncbi.nlm.nih.gov/pubmed/36696159 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 11 %N 12 %P e39672 %T Behavioral Skills Training for Teaching Safety Skills to Mental Health Clinicians: Protocol for a Pragmatic Randomized Control Trial %A Lin,Elizabeth %A Malhas,Mais %A Bratsalis,Emmanuel %A Thomson,Kendra %A Boateng,Rhonda %A Hargreaves,Fabienne %A Baig,Heba %A Benadict,Mary Benisha %A Busch,Louis %+ Department of Education, Centre for Addiction and Mental Health, B1- 2nd floor, Room 2338, 1025 Queen Street West, Toronto, ON, M6J 1H1, Canada, 1 416 535 8501 ext 34102, elizabethbetty.lin@camh.ca %K workplace safety %K violence %K mental health %K medical education %K protocol %K occupational health %K occupational safety %K behavioral analysis %K randomized controlled trial %K RCT %K pragmatic %K training %K safety %K self protection %D 2022 %7 14.12.2022 %9 Protocol %J JMIR Res Protoc %G English %X Background: Workplace violence is an increasingly significant topic, particularly for staff working in mental health settings. The Centre for Addiction and Mental Health (CAMH), Canada’s largest mental health hospital, considers workplace safety a high priority and consequently has mandated staff safety training. For clinical staff, key components of this training are self-protection and team-control skills, which are a last resort when an individual is at an imminent risk of harm to self or others and other interventions are ineffective (eg, verbal de-escalation). For the past 20 years, CAMH’s training-as-usual (TAU) has been based on a 3D approach (description, demonstration, and doing), but without any competency-based assessment. Recent staff reports indicate that the acquisition and retention of these skills may be problematic and that staff are not always confident in their ability to effectively address workplace violence. The current literature lacks studies that evaluate how staff are trained to acquire these physical skills and consequently provides no recommendations or best practice guidelines. To address these gaps described by the staff and in the literature, we have used an evidence-based approach from the field of applied behavior analysis known as behavioral skills training (BST), which requires trainees to actively execute targeted skills through instruction, modeling, practice, and feedback loop. As part of this method, competency checklists of skills are used with direct observation to determine successful mastery. Objective: Our objectives are to evaluate the effectiveness of BST versus TAU in terms of staff confidence; their competence in self-protection and team-control physical skills; their level of mastery (predefined as 80% competence) in these skills; and their confidence, competency, and mastery at 1 month posttraining. Methods: We are using a pragmatic randomized controlled trial design. New staff registering for their mandatory safety training are randomly assigned to sessions which are, in turn, randomly assigned to either the BST or TAU conditions. Attendees are informed and consented into the study at the beginning of training. Differences between those consenting and those not consenting in terms of role and department are tracked to flag potential biases. Results: This study was internally funded and commenced in January 2021 after receiving ethics approval. As of May 2022, data collection is complete; half of the baseline, posttraining, and 1-month videotapes have been rated, and three-fourths of the interrater reliability checks have been completed. The analysis is expected to begin in late summer 2022 with results submitted for publication by fall 2022. Conclusions: The findings from this study are expected to contribute to both the medical education literature as well as to the field of applied behavioral analysis where randomized controlled trial designs are rare. More practically, the results are also expected to inform the continuing development of our institutional staff safety training program. International Registered Report Identifier (IRRID): DERR1-10.2196/39672 %M 36515979 %R 10.2196/39672 %U https://www.researchprotocols.org/2022/12/e39672 %U https://doi.org/10.2196/39672 %U http://www.ncbi.nlm.nih.gov/pubmed/36515979 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 12 %P e37239 %T A Framework for Modeling and Interpreting Patient Subgroups Applied to Hospital Readmission: Visual Analytical Approach %A Bhavnani,Suresh K %A Zhang,Weibin %A Visweswaran,Shyam %A Raji,Mukaila %A Kuo,Yong-Fang %+ School of Public and Population Health, University of Texas Medical Branch, Institute for Translational Sciences, 301 University Blvd., Galveston, TX, 77555-0129, United States, 1 (409) 772 1928, subhavna@utmb.edu %K visual analytics %K Bipartite Network analysis %K hospital readmission %K precision medicine %K modeling %K Medicare %D 2022 %7 7.12.2022 %9 Original Paper %J JMIR Med Inform %G English %X Background: A primary goal of precision medicine is to identify patient subgroups and infer their underlying disease processes with the aim of designing targeted interventions. Although several studies have identified patient subgroups, there is a considerable gap between the identification of patient subgroups and their modeling and interpretation for clinical applications. Objective: This study aimed to develop and evaluate a novel analytical framework for modeling and interpreting patient subgroups (MIPS) using a 3-step modeling approach: visual analytical modeling to automatically identify patient subgroups and their co-occurring comorbidities and determine their statistical significance and clinical interpretability; classification modeling to classify patients into subgroups and measure its accuracy; and prediction modeling to predict a patient’s risk of an adverse outcome and compare its accuracy with and without patient subgroup information. Methods: The MIPS framework was developed using bipartite networks to identify patient subgroups based on frequently co-occurring high-risk comorbidities, multinomial logistic regression to classify patients into subgroups, and hierarchical logistic regression to predict the risk of an adverse outcome using subgroup membership compared with standard logistic regression without subgroup membership. The MIPS framework was evaluated for 3 hospital readmission conditions: chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), and total hip arthroplasty/total knee arthroplasty (THA/TKA) (COPD: n=29,016; CHF: n=51,550; THA/TKA: n=16,498). For each condition, we extracted cases defined as patients readmitted within 30 days of hospital discharge. Controls were defined as patients not readmitted within 90 days of discharge, matched by age, sex, race, and Medicaid eligibility. Results: In each condition, the visual analytical model identified patient subgroups that were statistically significant (Q=0.17, 0.17, 0.31; P<.001, <.001, <.05), significantly replicated (Rand Index=0.92, 0.94, 0.89; P<.001, <.001, <.01), and clinically meaningful to clinicians. In each condition, the classification model had high accuracy in classifying patients into subgroups (mean accuracy=99.6%, 99.34%, 99.86%). In 2 conditions (COPD and THA/TKA), the hierarchical prediction model had a small but statistically significant improvement in discriminating between readmitted and not readmitted patients as measured by net reclassification improvement (0.059, 0.11) but not as measured by the C-statistic or integrated discrimination improvement. Conclusions: Although the visual analytical models identified statistically and clinically significant patient subgroups, the results pinpoint the need to analyze subgroups at different levels of granularity for improving the interpretability of intra- and intercluster associations. The high accuracy of the classification models reflects the strong separation of patient subgroups, despite the size and density of the data sets. Finally, the small improvement in predictive accuracy suggests that comorbidities alone were not strong predictors of hospital readmission, and the need for more sophisticated subgroup modeling methods. Such advances could improve the interpretability and predictive accuracy of patient subgroup models for reducing the risk of hospital readmission, and beyond. %M 35537203 %R 10.2196/37239 %U https://medinform.jmir.org/2022/12/e37239 %U https://doi.org/10.2196/37239 %U http://www.ncbi.nlm.nih.gov/pubmed/35537203 %0 Journal Article %@ 2561-9128 %I JMIR Publications %V 5 %N 1 %P e40209 %T Experiences of Health Care Professionals Working Extra Weekends to Reduce COVID-19–Related Surgical Backlog: Cross-sectional Study %A Matava,Clyde %A So,Jeannette P %A Hossain,Alomgir %A Kelley,Simon %+ Department of Anesthesia and Pain Medicine, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, M5G 1X8, Canada, 1 416 813 7445, clyde.matava@sickkids.ca %K staff %K wait-list %K surgery %K health care delivery %K patient safety %K quality improvement %K patient satisfaction %K COVID-19 %K practice redesign %K burnout %K preoperative %K pediatric %K perioperative %K surgery %K surgical staff %K surgeon %K healthcare %K health care %K staff perception %K workforce %K stress %K work %K occupational health %K occupational safety %K perception %K workload %K nurse %K nursing %K anesthesiologist %K health care provider %K health care professional %K cross-sectional %K online survey %D 2022 %7 6.12.2022 %9 Original Paper %J JMIR Perioper Med %G English %X Background: During the quiescent periods of the COVID-19 pandemic in 2020, we implemented a weekend-scheduled pediatric surgery program to reduce COVID-19–related backlogs. Over 100 staff members from anesthesiologists to nurses, surgeons, and administrative and supporting personnel signed up to work extra weekends as part of a novel weekend elective pediatric surgery program to reduce COVID-19–related backlog: Operating Room Ramp-Up After COVID-19 Lockdown Ends-Extra Lists (ORRACLE-Xtra). Objective: In this study, we sought to evaluate staff perceptions and their level of satisfaction and experiences with working extra scheduled weekend elective surgical cases at the end of the 3-month pilot phase of ORRACLE-Xtra and identify key factors for participation. Methods: Following the pilot of ORRACLE-Xtra, all perioperative staff who worked at least 1 weekend list were invited to complete an online survey that was developed and tested prior to distribution. The survey collected information on the impact of working weekends on well-being, overall satisfaction, and likelihood of and preferences for working future weekend lists. Logistic regression was used to estimate the association of well-being with satisfaction and willingness to work future weekend lists. Results: A total of 82 out of 118 eligible staff responded to the survey for a response rate of 69%. Staff worked a median of 2 weekend lists (IQR 1-9). Of 82 staff members, 65 (79%) were satisfied or very satisfied with working the extra weekend elective lists, with surgeons and surgical trainees reporting the highest levels of satisfaction. Most respondents (72/82, 88%) would continue working weekend lists. A sense of accomplishment was associated with satisfaction with working on the weekend (odds ratio [OR] 19.97, 95% CI 1.79-222.63; P=.02) and willingness to participate in future weekend lists (OR 17.74, 95% CI 1.50-200.70; P=.02). Many (56/82, 68%) were willing to work weekend lists that included longer, more complex cases, which was associated with a sense of community (OR 0.12, 95% CI 0.02-0.63; P=.01). Conclusions: Staff participating in the first 3 months of the ORRACLE-Xtra program reported satisfaction with working weekends and a willingness to continue with the program, including doing longer, more complex cases. Institutions planning on implementing COVID-19 surgical backlog work may benefit from gathering key information from their staff. %M 36423322 %R 10.2196/40209 %U https://periop.jmir.org/2022/1/e40209 %U https://doi.org/10.2196/40209 %U http://www.ncbi.nlm.nih.gov/pubmed/36423322 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 11 %P e38483 %T Managing Critical Patient-Reported Outcome Measures in Oncology Settings: System Development and Retrospective Study %A Strachna,Olga %A Asan,Onur %A Stetson,Peter D %+ School of Systems and Enterprises, Stevens Institute of Technology, 1 Castle Terrace, Hoboken, NJ, 07030, United States, 1 201 216 5514, oasan@stevens.edu %K patient-reported outcome measures %K delivery of health care %K self-report %K quality of care %K neoplasms %K surveys and questionnaires %K clinical decision support systems %D 2022 %7 3.11.2022 %9 Original Paper %J JMIR Med Inform %G English %X Background: Remote monitoring programs based on the collection of patient-reported outcome (PRO) data are being increasingly adopted in oncology practices. Although PROs are a great source of patient data, the management of critical PRO data is not discussed in detail in the literature. Objective: This first-of-its-kind study aimed to design, describe, and evaluate a closed-loop alerting and communication system focused on managing PRO-related alerts in cancer care. Methods: We designed and developed a novel solution using an agile software development methodology by incrementally building new capabilities. We evaluated these new features using participatory design and the Fit between Individuals, Task, and Technology framework. Results: A total of 8 questionnaires were implemented using alerting features, resulting in an alert rate of 7.82% (36,838/470,841) with 13.28% (10,965/82,544) of the patients triggering at least one alert. Alerts were reviewed by 501 staff members spanning across 191 care teams. All the alerts were reviewed with a median response time of 1 hour (SD 185 hours) during standard business hours. The most severe (red) alerts were documented 56.83% (2592/4561) of the time, whereas unlabeled alerts were documented 27.68% (1298/4689) of the time, signaling clinician concordance with the alert thresholds. Conclusions: A PRO-based alert and communication system has some initial benefits in reviewing clinically meaningful PRO data in a reasonable amount of time. We have discussed key system design considerations, workflow integration, and the mitigation of potential impact on the burden of care teams. The introduction of a PRO-based alert and communication system provides a reliable mechanism for care teams to review and respond to patient symptoms quickly. The system was standardized across many different oncology settings, demonstrating system flexibility. Future studies should focus on formally evaluating system usability through qualitative methods. %M 36326801 %R 10.2196/38483 %U https://medinform.jmir.org/2022/11/e38483 %U https://doi.org/10.2196/38483 %U http://www.ncbi.nlm.nih.gov/pubmed/36326801 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 11 %P e35709 %T The Application of Graph Theoretical Analysis to Complex Networks in Medical Malpractice in China: Qualitative Study %A Dong,Shengjie %A Shi,Chenshu %A Zeng,Wu %A Jia,Zhiying %A Dong,Minye %A Xiao,Yuyin %A Li,Guohong %+ School of Public Health, Shanghai Jiao Tong University, No.227 South Chongqing Road, Huangpu District, Shanghai, 200025, China, 86 21 63846590, guohongli@sjtu.edu.cn %K medical malpractice %K complex network %K scale-free network %K hub nodes %K patient safety management %K health systems %D 2022 %7 3.11.2022 %9 Original Paper %J JMIR Med Inform %G English %X Background: Studies have shown that hospitals or physicians with multiple malpractice claims are more likely to be involved in new claims. This finding indicates that medical malpractice may be clustered by institutions. Objective: We aimed to identify the underlying mechanisms of medical malpractice that, in the long term, may contribute to developing interventions to reduce future claims and patient harm. Methods: This study extracted the semantic network in 6610 medical litigation records (unstructured data) obtained from a public judicial database in China. They represented the most serious cases of malpractice in the country. The medical malpractice network of China was presented as a knowledge graph based on the complex network theory; it uses the International Classification of Patient Safety from the World Health Organization as a reference. Results: We found that the medical malpractice network of China was a scale-free network—the occurrence of medical malpractice in litigation cases was not random, but traceable. The results of the hub nodes revealed that orthopedics, obstetrics and gynecology, and the emergency department were the 3 most frequent specialties that incurred malpractice; inadequate informed consent work constituted the most errors. Nontechnical errors (eg, inadequate informed consent) showed a higher centrality than technical errors. Conclusions: Hospitals and medical boards could apply our approach to detect hub nodes that are likely to benefit from interventions; doing so could effectively control medical risks. %M 36326815 %R 10.2196/35709 %U https://medinform.jmir.org/2022/11/e35709 %U https://doi.org/10.2196/35709 %U http://www.ncbi.nlm.nih.gov/pubmed/36326815 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 10 %P e29920 %T RWD-Cockpit: Application for Quality Assessment of Real-world Data %A Babrak,Lmar Marie %A Smakaj,Erand %A Agac,Teyfik %A Asprion,Petra Maria %A Grimberg,Frank %A der Werf,Daan Van %A van Ginkel,Erwin Willem %A Tosoni,Deniz David %A Clay,Ieuan %A Degen,Markus %A Brodbeck,Dominique %A Natali,Eriberto Noel %A Schkommodau,Erik %A Miho,Enkelejda %+ University of Applied Sciences and Arts Northwestern Switzerland, School of Life Sciences, Hofackerstrasse 30, Muttenz, 4132, Switzerland, 41 0612285847, enkelejda.miho@fhnw.ch %K real-world data %K real-world evidence %K quality assessment %K application %K mobile phone %D 2022 %7 18.10.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Digital technologies are transforming the health care system. A large part of information is generated as real-world data (RWD). Data from electronic health records and digital biomarkers have the potential to reveal associations between the benefits and adverse events of medicines, establish new patient-stratification principles, expose unknown disease correlations, and inform on preventive measures. The impact for health care payers and providers, the biopharmaceutical industry, and governments is massive in terms of health outcomes, quality of care, and cost. However, a framework to assess the preliminary quality of RWD is missing, thus hindering the conduct of population-based observational studies to support regulatory decision-making and real-world evidence. Objective: To address the need to qualify RWD, we aimed to build a web application as a tool to translate characterization of some quality parameters of RWD into a metric and propose a standard framework for evaluating the quality of the RWD. Methods: The RWD-Cockpit systematically scores data sets based on proposed quality metrics and customizable variables chosen by the user. Sleep RWD generated de novo and publicly available data sets were used to validate the usability and applicability of the web application. The RWD quality score is based on the evaluation of 7 variables: manageability specifies access and publication status; complexity defines univariate, multivariate, and longitudinal data; sample size indicates the size of the sample or samples; privacy and liability stipulates privacy rules; accessibility specifies how the data set can be accessed and to what granularity; periodicity specifies how often the data set is updated; and standardization specifies whether the data set adheres to any specific technical or metadata standard. These variables are associated with several descriptors that define specific characteristics of the data set. Results: To address the need to qualify RWD, we built the RWD-Cockpit web application, which proposes a framework and applies a common standard for a preliminary evaluation of RWD quality across data sets—molecular, phenotypical, and social—and proposes a standard that can be further personalized by the community retaining an internal standard. Applied to 2 different case studies—de novo–generated sleep data and publicly available data sets—the RWD-Cockpit could identify and provide researchers with variables that might increase quality. Conclusions: The results from the application of the framework of RWD metrics implemented in the RWD-Cockpit application suggests that multiple data sets can be preliminarily evaluated in terms of quality using the proposed metrics. The output scores—quality identifiers—provide a first quality assessment for the use of RWD. Although extensive challenges remain to be addressed to set RWD quality standards, our proposal can serve as an initial blueprint for community efforts in the characterization of RWD quality for regulated settings. %M 35266872 %R 10.2196/29920 %U https://formative.jmir.org/2022/10/e29920 %U https://doi.org/10.2196/29920 %U http://www.ncbi.nlm.nih.gov/pubmed/35266872 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 9 %P e37283 %T The Value of Electronic Health Records Since the Health Information Technology for Economic and Clinical Health Act: Systematic Review %A Modi,Shikha %A Feldman,Sue S %+ Department of Political Science, Auburn University, 7074 Haley Center, Auburn, AL, 36849, United States, 1 2563355796, szs0308@auburn.edu %K electronic health records %K EHRs %K value %K financial outcomes %K clinical outcomes %K health informatics %K clinical informatics %D 2022 %7 27.9.2022 %9 Review %J JMIR Med Inform %G English %X Background: Electronic health records (EHRs) are the electronic records of patient health information created during ≥1 encounter in any health care setting. The Health Information Technology Act of 2009 has been a major driver of the adoption and implementation of EHRs in the United States. Given that the adoption of EHRs is a complex and expensive investment, a return on this investment is expected. Objective: This literature review aims to focus on how the value of EHRs as an intervention is defined in relation to the elaboration of value into 2 different value outcome categories, financial and clinical outcomes, and to understand how EHRs contribute to these 2 value outcome categories. Methods: This literature review was conducted using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). The initial search of key terms, EHRs, values, financial outcomes, and clinical outcomes in 3 different databases yielded 971 articles, of which, after removing 410 (42.2%) duplicates, 561 (57.8%) were incorporated in the title and abstract screening. During the title and abstract screening phase, articles were excluded from further review phases if they met any of the following criteria: not relevant to the outcomes of interest, not relevant to EHRs, nonempirical, and non–peer reviewed. After the application of the exclusion criteria, 80 studies remained for a full-text review. After evaluating the full text of the residual 80 studies, 26 (33%) studies were excluded as they did not address the impact of EHR adoption on the outcomes of interest. Furthermore, 4 additional studies were discovered through manual reference searches and were added to the total, resulting in 58 studies for analysis. A qualitative analysis tool, ATLAS.ti. (version 8.2), was used to categorize and code the final 58 studies. Results: The findings from the literature review indicated a combination of positive and negative impacts of EHRs on financial and clinical outcomes. Of the 58 studies surveyed for this review of the literature, 5 (9%) reported on the intersection of financial and clinical outcomes. To investigate this intersection further, the category “Value–Intersection of Financial and Clinical Outcomes” was generated. Approximately 80% (4/5) of these studies specified a positive association between EHR adoption and financial and clinical outcomes. Conclusions: This review of the literature reports on the individual and collective value of EHRs from a financial and clinical outcomes perspective. The collective perspective examined the intersection of financial and clinical outcomes, suggesting a reversal of the current understanding of how IT investments could generate improvements in productivity, and prompted a new question to be asked about whether an increase in productivity could potentially lead to more IT investments. %M 36166286 %R 10.2196/37283 %U https://medinform.jmir.org/2022/9/e37283 %U https://doi.org/10.2196/37283 %U http://www.ncbi.nlm.nih.gov/pubmed/36166286 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 8 %P e36199 %T Application of Artificial Intelligence in Shared Decision Making: Scoping Review %A Abbasgholizadeh Rahimi,Samira %A Cwintal,Michelle %A Huang,Yuhui %A Ghadiri,Pooria %A Grad,Roland %A Poenaru,Dan %A Gore,Genevieve %A Zomahoun,Hervé Tchala Vignon %A Légaré,France %A Pluye,Pierre %+ Department of Family Medicine, McGill University, 5858 Cote-des-Neiges Rd, Suite 300, Montreal, QC, H3S 1Z1, Canada, 1 (514)399 9218, samira.rahimi@mcgill.ca %K artificial intelligence %K machine learning %K shared decision making %K patient-centered care %K scoping review %D 2022 %7 9.8.2022 %9 Review %J JMIR Med Inform %G English %X Background: Artificial intelligence (AI) has shown promising results in various fields of medicine. It has the potential to facilitate shared decision making (SDM). However, there is no comprehensive mapping of how AI may be used for SDM. Objective: We aimed to identify and evaluate published studies that have tested or implemented AI to facilitate SDM. Methods: We performed a scoping review informed by the methodological framework proposed by Levac et al, modifications to the original Arksey and O'Malley framework of a scoping review, and the Joanna Briggs Institute scoping review framework. We reported our results based on the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) reporting guideline. At the identification stage, an information specialist performed a comprehensive search of 6 electronic databases from their inception to May 2021. The inclusion criteria were: all populations; all AI interventions that were used to facilitate SDM, and if the AI intervention was not used for the decision-making point in SDM, it was excluded; any outcome related to patients, health care providers, or health care systems; studies in any health care setting, only studies published in the English language, and all study types. Overall, 2 reviewers independently performed the study selection process and extracted data. Any disagreements were resolved by a third reviewer. A descriptive analysis was performed. Results: The search process yielded 1445 records. After removing duplicates, 894 documents were screened, and 6 peer-reviewed publications met our inclusion criteria. Overall, 2 of them were conducted in North America, 2 in Europe, 1 in Australia, and 1 in Asia. Most articles were published after 2017. Overall, 3 articles focused on primary care, and 3 articles focused on secondary care. All studies used machine learning methods. Moreover, 3 articles included health care providers in the validation stage of the AI intervention, and 1 article included both health care providers and patients in clinical validation, but none of the articles included health care providers or patients in the design and development of the AI intervention. All used AI to support SDM by providing clinical recommendations or predictions. Conclusions: Evidence of the use of AI in SDM is in its infancy. We found AI supporting SDM in similar ways across the included articles. We observed a lack of emphasis on patients’ values and preferences, as well as poor reporting of AI interventions, resulting in a lack of clarity about different aspects. Little effort was made to address the topics of explainability of AI interventions and to include end-users in the design and development of the interventions. Further efforts are required to strengthen and standardize the use of AI in different steps of SDM and to evaluate its impact on various decisions, populations, and settings. %M 35943793 %R 10.2196/36199 %U https://medinform.jmir.org/2022/8/e36199 %U https://doi.org/10.2196/36199 %U http://www.ncbi.nlm.nih.gov/pubmed/35943793 %0 Journal Article %@ 2563-6316 %I JMIR Publications %V 3 %N 3 %P e34263 %T Waiting Time and Patient Satisfaction in a Subspecialty Eye Hospital Using a Mobile Data Collection Kit: Pre-Post Quality Improvement Intervention %A Mbwogge,Mathew %A Astbury,Nicholas %A Nkumbe,Henry Ebong %A Bunce,Catey %A Bascaran,Covadonga %+ International Center for Eye Health, London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom, 44 07424409211, m.mbwoge@gmail.com %K waiting time %K waiting list %K patient satisfaction %K quality improvement %K clinical audit %K ophthalmology %K patient-centered care %D 2022 %7 9.8.2022 %9 Original Paper %J JMIRx Med %G English %X Background: Waiting time can considerably increase the cost to both the clinic and the patient and be a major predictor of the satisfaction of eye care users. Efficient management of waiting time remains as a challenge in hospitals. Waiting time management will become even more crucial in the postpandemic era. A key consideration when improving waiting time is the involvement of eye care users. This study aimed at improving patient waiting time and satisfaction through the use of Plan-Do-Study-Act (PDSA) quality improvement cycles. Objective: The objectives of this study were to determine the waiting time and patient satisfaction, measure the association between waiting time and patient satisfaction, and determine the effectiveness of the PDSA model in improving waiting time and satisfaction. Methods: This was a pre-post quality improvement study among patients aged 19 to 80 years, who are consulting with the Magrabi International Council of Ophthalmology Cameroon Eye Institute. We used PDSA cycles to conduct improvement audits of waiting time and satisfaction over 6 weeks. A data collection app known as Open Data Kit (Get ODK Inc) was used for real-time tracking of waiting, service, and idling times at each service point. Participants were also asked whether they were satisfied with the waiting time at the point of exit. Data from 51% (25/49) preintervention participants and 49% (24/49) postintervention participants were analyzed using Stata 14 at .05 significance level. An unpaired 2-tailed t test was used to assess the statistical significance of the observed differences in times before and after the intervention. Logistic regression was used to examine the association between satisfaction and waiting time. Results: In total, 49 participants were recruited with mean age of 49 (SD 15.7) years. The preintervention mean waiting, service, and idling times were 450 (SD 96.6), 112 (SD 47), and 338 (SD 98.1) minutes, respectively. There was no significant association between patient waiting time and satisfaction (odds ratio 1, 95% CI 0.99-1; P=.37; χ23=0.4). The use of PDSA led to 15% (66 minutes/450 minutes) improvement in waiting time (t47=2; P=.05) and nonsignificant increase in patient satisfaction from 32% (8/25) to 33% (8/24; z=0.1; P=.92). Conclusions: Use of PDSA led to a borderline statistically significant reduction of 66 minutes in waiting time over 6 weeks and an insignificant improvement in satisfaction, suggesting that quality improvement efforts at the clinic have to be made over a considerable period to be able to produce significant changes. The study provides a good basis for standardizing the cycle (consultation) time at the clinic. We recommend shortening the patient pathway and implementing other measures including a phasic appointment system, automated patient time monitoring, robust ticketing, patient pathway supervision, standard triaging, task shifting, physician consultation planning, patient education, and additional registration staff. %M 37725529 %R 10.2196/34263 %U https://med.jmirx.org/2022/3/e34263 %U https://doi.org/10.2196/34263 %U http://www.ncbi.nlm.nih.gov/pubmed/37725529 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 8 %P e39277 %T Optimization of a Quality Improvement Tool for Cancer Diagnosis in Primary Care: Qualitative Study %A Chima,Sophie %A Martinez-Gutierrez,Javiera %A Hunter,Barbara %A Manski-Nankervis,Jo-Anne %A Emery,Jon %+ Centre for Cancer Research, Victorian Comprehensive Cancer Centre, University of Melbourne, 305 Grattan St, Parkville, Melbourne, 3010, Australia, 61 410 798 352, s.chima@unimelb.edu.au %K cancer %K primary health care %K diagnosis %K quality improvement %K clinical decision support tool %K general practice %K pilot %K feasibility %K Clinical Performance Feedback Intervention Theory %D 2022 %7 4.8.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: The most common route to a diagnosis of cancer is through primary care. Delays in diagnosing cancer occur when an opportunity to make a timely diagnosis is missed and is evidenced by patients visiting the general practitioner (GP) on multiple occasions before referral to a specialist. Tools that minimize prolonged diagnostic intervals and reduce missed opportunities to investigate patients for cancer are therefore a priority. Objective: This study aims to explore the usefulness and feasibility of a novel quality improvement (QI) tool in which algorithms flag abnormal test results that may be indicative of undiagnosed cancer. This study allows for the optimization of the cancer recommendations before testing the efficacy in a randomized controlled trial. Methods: GPs, practice nurses, practice managers, and consumers were recruited to participate in individual interviews or focus groups. Participants were purposively sampled as part of a pilot and feasibility study, in which primary care practices were receiving recommendations relating to the follow-up of abnormal test results for prostate-specific antigen, thrombocytosis, and iron-deficiency anemia. The Clinical Performance Feedback Intervention Theory (CP-FIT) was applied to the analysis using a thematic approach. Results: A total of 17 interviews and 3 focus groups (n=18) were completed. Participant themes were mapped to CP-FIT across the constructs of context, recipient, and feedback variables. The key facilitators to use were alignment with workflow, recognized need, the perceived importance of the clinical topic, and the GPs’ perception that the recommendations were within their control. Barriers to use included competing priorities, usability and complexity of the recommendations, and knowledge of the clinical topic. There was consistency between consumer and practitioner perspectives, reporting language concerns associated with the word cancer, the need for more patient-facing resources, and time constraints of the consultation to address patients’ worries. Conclusions: There was a recognized need for the QI tool to support the diagnosis of cancer in primary care, but barriers were identified that hindered the usability and actionability of the recommendations in practice. In response, the tool has been refined and is currently being evaluated as part of a randomized controlled trial. Successful and effective implementation of this QI tool could support the detection of patients at risk of undiagnosed cancer in primary care and assist in preventing unnecessary delays. %M 35925656 %R 10.2196/39277 %U https://formative.jmir.org/2022/8/e39277 %U https://doi.org/10.2196/39277 %U http://www.ncbi.nlm.nih.gov/pubmed/35925656 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 8 %P e35726 %T Harnessing the Electronic Health Care Record to Optimize Patient Safety in Primary Care: Framework for Evaluating e–Safety-Netting Tools %A Black,Georgia Bell %A Bhuiya,Afsana %A Friedemann Smith,Claire %A Hirst,Yasemin %A Nicholson,Brian David %+ Department of Applied Health Research, University College London, 1-19 Torrington Place, London, WC1E 7HB, United Kingdom, 44 2031083157, g.black@ucl.ac.uk %K primary care %K patient safety %K electronic health record %K safety %K optimize %K framework %K evaluation %K tool %K diagnostic %K uncertainty %K management %K netting %K software %K criteria %D 2022 %7 1.8.2022 %9 Viewpoint %J JMIR Med Inform %G English %X The management of diagnostic uncertainty is part of every primary care physician’s role. e–Safety-netting tools help health care professionals to manage diagnostic uncertainty. Using software in addition to verbal or paper based safety-netting methods could make diagnostic delays and errors less likely. There are an increasing number of software products that have been identified as e–safety-netting tools, particularly since the start of the COVID-19 pandemic. e–Safety-netting tools can have a variety of functions, such as sending clinician alerts, facilitating administrative tasking, providing decision support, and sending reminder text messages to patients. However, these tools have not been evaluated by using robust research designs for patient safety interventions. We present an emergent framework of criteria for effective e–safety-netting tools that can be used to support the development of software. The framework is based on validated frameworks for electronic health record development and patient safety. There are currently no tools available that meet all of the criteria in the framework. We hope that the framework will stimulate clinical and public conversations about e–safety-netting tools. In the future, a validated framework would drive audits and improvements. We outline key areas for future research both in primary care and within integrated care systems. %M 35916722 %R 10.2196/35726 %U https://medinform.jmir.org/2022/8/e35726 %U https://doi.org/10.2196/35726 %U http://www.ncbi.nlm.nih.gov/pubmed/35916722 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 7 %P e34030 %T Wisdom of the Experts Versus Opinions of the Crowd in Hospital Quality Ratings: Analysis of Hospital Compare Star Ratings and Google Star Ratings %A Ramasubramanian,Hari %A Joshi,Satish %A Krishnan,Ranjani %+ Accounting Department, Frankfurt School of Finance and Management, 32-34 Adickesallee, Frankfurt am Main, 60320, Germany, 49 69154008823, h.ramasubramanian@fs.de %K hospital quality %K web-based rating %K online ratings %K Hospital Compare %K star ratings %D 2022 %7 26.7.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: Popular web-based portals provide free and convenient access to user-generated hospital quality reviews. The Centers for Medicare & Medicaid Services (CMS) also publishes Hospital Compare Star Ratings (HCSR), a comprehensive expert rating of US hospital quality that aggregates multiple measures of quality. CMS revised the HCSR methods in 2021. It is important to analyze the degree to which web-based ratings reflect expert measures of hospital quality because easily accessible, crowdsourced hospital ratings influence consumers’ hospital choices. Objective: This study aims to assess the association between web-based, Google hospital quality ratings that reflect the opinions of the crowd and HCSR representing the wisdom of the experts, as well as the changes in these associations following the 2021 revision of the CMS rating system. Methods: We extracted Google star ratings using the Application Programming Interface in June 2020. The HCSR data of April 2020 (before the revision of HCSR methodology) and April 2021 (after the revision of HCSR methodology) were obtained from the CMS Hospital Compare website. We also extracted scores for the individual components of hospital quality for each of the hospitals in our sample using the code provided by Hospital Compare. Fractional response models were used to estimate the association between Google star ratings and HCSR as well as individual components of quality (n=2619). Results: The Google star ratings are statistically associated with HCSR (P<.001) after controlling for hospital-level effects; however, they are not associated with clinical components of HCSR that require medical expertise for evaluation such as safety of care (P=.30) or readmission (P=.52). The revised CMS rating system ameliorates previous partial inconsistencies in the association between Google star ratings and quality component scores of HCSR. Conclusions: Crowdsourced Google star hospital ratings are informative regarding expert CMS overall hospital quality ratings and individual quality components that are easier for patients to evaluate. Improvements in hospital quality metrics that require expertise to assess, such as safety of care and readmission, may not lead to improved Google star ratings. Hospitals can benefit from using crowdsourced ratings as timely and easily available indicators of their quality performance while recognizing their limitations and biases. %M 35881418 %R 10.2196/34030 %U https://www.jmir.org/2022/7/e34030 %U https://doi.org/10.2196/34030 %U http://www.ncbi.nlm.nih.gov/pubmed/35881418 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 9 %N 2 %P e32174 %T Identifying Contextual Factors and Strategies for Practice Facilitation in Primary Care Quality Improvement Using an Informatics-Driven Model: Framework Development and Mixed Methods Case Study %A Ye,Jiancheng %A Woods,Donna %A Bannon,Jennifer %A Bilaver,Lucy %A Kricke,Gayle %A McHugh,Megan %A Kho,Abel %A Walunas,Theresa %+ Feinberg School of Medicine, Northwestern University, 633 N Saint Clair St, Chicago, IL, 60611, United States, 1 312 503 3690, jiancheng.ye@u.northwestern.edu %K quality improvement %K practice facilitation %K primary care %K mixed-methods %K practice facilitator %K informatics %K electronic health record %K implementation science %K implementation %K challenge %K strategy %K framework %K perspective %D 2022 %7 24.6.2022 %9 Original Paper %J JMIR Hum Factors %G English %X Background: The past decade has seen increasing opportunities and efforts to integrate quality improvement into health care. Practice facilitation is a proven strategy to support redesign and improvement in primary care practices that focuses on building organizational capacity for continuous improvement. Practice leadership, staff, and practice facilitators all play important roles in supporting quality improvement in primary care. However, little is known about their perspectives on the context, enablers, barriers, and strategies that impact quality improvement initiatives. Objective: This study aimed to develop a framework to enable assessment of contextual factors, challenges, and strategies that impact practice facilitation, clinical measure performance, and the implementation of quality improvement interventions. We also illustrated the application of the framework using a real-world case study. Methods: We developed the TITO (task, individual, technology, and organization) framework by conducting participatory stakeholder workshops and incorporating their perspectives to identify enablers and barriers to quality improvement and practice facilitation. We conducted a case study using a mixed methods approach to demonstrate the use of the framework and describe practice facilitation and factors that impact quality improvement in a primary care practice that participated in the Healthy Hearts in the Heartland study. Results: The proposed framework was used to organize and analyze different stakeholders’ perspectives and key factors based on framework domains. The case study showed that practice leaders, staff, and practice facilitators all influenced the success of the quality improvement program. However, these participants faced different challenges and used different strategies. The framework showed that barriers stemmed from patients’ social determinants of health, a lack of staff and time, and unsystematic facilitation resources, while enablers included practice culture, staff buy-in, implementation of effective practice facilitation strategies, practice capacity for change, and shared complementary resources from similar, ongoing programs. Conclusions: Our framework provided a useful and generalizable structure to guide and support assessment of future practice facilitation projects, quality improvement initiatives, and health care intervention implementation studies. The practice leader, staff, and practice facilitator all saw value in the quality improvement program and practice facilitation. Practice facilitators are key liaisons to help the quality improvement program; they help all stakeholders work toward a shared target and leverage tailored strategies. Taking advantage of resources from competing, yet complementary, programs as additional support may accelerate the effective achievement of quality improvement goals. Practice facilitation–supported quality improvement programs may be opportunities to assist primary care practices in achieving improved quality of care through focused and targeted efforts. The case study demonstrated how our framework can support a better understanding of contextual factors for practice facilitation, which could enable well-prepared and more successful quality improvement programs for primary care practices. Combining implementation science and informatics thinking, our TITO framework may facilitate interdisciplinary research in both fields. %M 35749211 %R 10.2196/32174 %U https://humanfactors.jmir.org/2022/2/e32174 %U https://doi.org/10.2196/32174 %U http://www.ncbi.nlm.nih.gov/pubmed/35749211 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 6 %P e34204 %T Quality Criteria for Real-world Data in Pharmaceutical Research and Health Care Decision-making: Austrian Expert Consensus %A Klimek,Peter %A Baltic,Dejan %A Brunner,Martin %A Degelsegger-Marquez,Alexander %A Garhöfer,Gerhard %A Gouya-Lechner,Ghazaleh %A Herzog,Arnold %A Jilma,Bernd %A Kähler,Stefan %A Mikl,Veronika %A Mraz,Bernhard %A Ostermann,Herwig %A Röhl,Claas %A Scharinger,Robert %A Stamm,Tanja %A Strassnig,Michael %A Wirthumer-Hoche,Christa %A Pleiner-Duxneuner,Johannes %+ Gesellschaft für Pharmazeutische Medizin, Engelhorngasse 3, Vienna, 1210, Austria, 43 1 40160 ext 36255, johannes.pleiner-duxneuner@roche.com %K real-world data %K real-world evidence %K data quality %K data quality criteria %K RWD quality recommendations %K pharmaceutical research %K health care decision-making %K quality criteria for RWD in health care %K Gesellschaft für Pharmazeutische Medizin %K GPMed %D 2022 %7 17.6.2022 %9 Viewpoint %J JMIR Med Inform %G English %X Real-world data (RWD) collected in routine health care processes and transformed to real-world evidence have become increasingly interesting within the research and medical communities to enhance medical research and support regulatory decision-making. Despite numerous European initiatives, there is still no cross-border consensus or guideline determining which qualities RWD must meet in order to be acceptable for decision-making within regulatory or routine clinical decision support. In the absence of guidelines defining the quality standards for RWD, an overview and first recommendations for quality criteria for RWD in pharmaceutical research and health care decision-making is needed in Austria. An Austrian multistakeholder expert group led by Gesellschaft für Pharmazeutische Medizin (Austrian Society for Pharmaceutical Medicine) met regularly; reviewed and discussed guidelines, frameworks, use cases, or viewpoints; and agreed unanimously on a set of quality criteria for RWD. This consensus statement was derived from the quality criteria for RWD to be used more effectively for medical research purposes beyond the registry-based studies discussed in the European Medicines Agency guideline for registry-based studies. This paper summarizes the recommendations for the quality criteria of RWD, which represents a minimum set of requirements. In order to future-proof registry-based studies, RWD should follow high-quality standards and be subjected to the quality assurance measures needed to underpin data quality. Furthermore, specific RWD quality aspects for individual use cases (eg, medical or pharmacoeconomic research), market authorization processes, or postmarket authorization phases have yet to be elaborated. %M 35713954 %R 10.2196/34204 %U https://medinform.jmir.org/2022/6/e34204 %U https://doi.org/10.2196/34204 %U http://www.ncbi.nlm.nih.gov/pubmed/35713954 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 11 %N 5 %P e30496 %T Impact of a Postintensive Care Unit Multidisciplinary Follow-up on the Quality of Life (SUIVI-REA): Protocol for a Multicenter Randomized Controlled Trial %A Friedman,Diane %A Grimaldi,Lamiae %A Cariou,Alain %A Aegerter,Philippe %A Gaudry,Stéphane %A Ben Salah,Abdel %A Oueslati,Haikel %A Megarbane,Bruno %A Meunier-Beillard,Nicolas %A Quenot,Jean-Pierre %A Schwebel,Carole %A Jacob,Laurent %A Robin Lagandré,Ségloène %A Kalfon,Pierre %A Sonneville,Romain %A Siami,Shidasp %A Mazeraud,Aurelien %A Sharshar,Tarek %+ GHU-Paris Psychiatrie & Neurosciences, Sainte-Anne Hospital, Université de Paris, 1, rue Cabanis, Paris, 75014, France, 33 0145658000, tsharshar@gmail.com %K critical illness %K Post-ICU syndrome %K Mortality %K cognitive impairments %K cognition %K quality of life %K patients %K intensive care %K post-traumatic %K post intensive care %D 2022 %7 9.5.2022 %9 Protocol %J JMIR Res Protoc %G English %X Background: Critically ill patients are at risk of developing a postintensive care syndrome (PICS), which is characterized by physical, psychological, and cognitive impairments and which dramatically impacts the patient’s quality of life (QoL). No intervention has been shown to improve QoL. We hypothesized that a medical, psychological, and social follow-up would improve QoL by mitigating the PICS. Objective: This multicenter, randomized controlled trial (SUIVI-REA) aims to compare a multidisciplinary follow-up with a standard postintensive care unit (ICU) follow-up. Methods: Patients were randomized to the control or intervention arm. In the intervention arm, multidisciplinary follow-up involved medical, psychological, and social evaluation at ICU discharge and at 3, 6, and 12 months thereafter. In the placebo group, patients were seen only at 12 months by the multidisciplinary team. Baseline characteristics at ICU discharge were collected for all patients. The primary outcome was QoL at 1 year, assessed using the Euro Quality of Life-5 dimensions (EQ5D). Secondary outcomes were mortality, cognitive, psychological, and functional status; social and professional reintegration; and the rate of rehospitalization and outpatient consultations at 1 year. Results: The study was funded by the Ministry of Health in June 2010. It was approved by the Ethics Committee on July 8, 2011. The first and last patient were randomized on December 20, 2012, and September 1, 2017, respectively. A total of 546 patients were enrolled across 11 ICUs. At present, data management is ongoing, and all parties involved in the trial remain blinded. Conclusions: The SUVI-REA multicenter randomized controlled trial aims to assess whether a post-ICU multidisciplinary follow-up improves QoL at 1 year. Trial Registration: Clinicaltrials.gov NCT01796509; https://clinicaltrials.gov/ct2/show/NCT01796509 International Registered Report Identifier (IRRID): DERR1-10.2196/30496 %M 35532996 %R 10.2196/30496 %U https://www.researchprotocols.org/2022/5/e30496 %U https://doi.org/10.2196/30496 %U http://www.ncbi.nlm.nih.gov/pubmed/35532996 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 5 %P e35061 %T Computerized Clinical Decision Support Systems for the Early Detection of Sepsis Among Pediatric, Neonatal, and Maternal Inpatients: Scoping Review %A Ackermann,Khalia %A Baker,Jannah %A Festa,Marino %A McMullan,Brendan %A Westbrook,Johanna %A Li,Ling %+ Centre for Health Systems and Safety Research, Australian Institute of Health Innovation, Level 6, 75 Talavera road, Macquarie University, 2109, Australia, 61 2 9850 2432, khalia.ackermann@mq.edu.au %K sepsis %K early detection of disease %K computerized clinical decision support %K patient safety %K electronic health records %K sepsis care pathway %D 2022 %7 6.5.2022 %9 Review %J JMIR Med Inform %G English %X Background: Sepsis is a severe condition associated with extensive morbidity and mortality worldwide. Pediatric, neonatal, and maternal patients represent a considerable proportion of the sepsis burden. Identifying sepsis cases as early as possible is a key pillar of sepsis management and has prompted the development of sepsis identification rules and algorithms that are embedded in computerized clinical decision support (CCDS) systems. Objective: This scoping review aimed to systematically describe studies reporting on the use and evaluation of CCDS systems for the early detection of pediatric, neonatal, and maternal inpatients at risk of sepsis. Methods: MEDLINE, Embase, CINAHL, Cochrane, Latin American and Caribbean Health Sciences Literature (LILACS), Scopus, Web of Science, OpenGrey, ClinicalTrials.gov, and ProQuest Dissertations and Theses Global (PQDT) were searched by using a search strategy that incorporated terms for sepsis, clinical decision support, and early detection. Title, abstract, and full-text screening was performed by 2 independent reviewers, who consulted a third reviewer as needed. One reviewer performed data charting with a sample of data. This was checked by a second reviewer and via discussions with the review team, as necessary. Results: A total of 33 studies were included in this review—13 (39%) pediatric studies, 18 (55%) neonatal studies, and 2 (6%) maternal studies. All studies were published after 2011, and 27 (82%) were published from 2017 onward. The most common outcome investigated in pediatric studies was the accuracy of sepsis identification (9/13, 69%). Pediatric CCDS systems used different combinations of 18 diverse clinical criteria to detect sepsis across the 13 identified studies. In neonatal studies, 78% (14/18) of the studies investigated the Kaiser Permanente early-onset sepsis risk calculator. All studies investigated sepsis treatment and management outcomes, with 83% (15/18) reporting on antibiotics-related outcomes. Usability and cost-related outcomes were each reported in only 2 (6%) of the 31 pediatric or neonatal studies. Both studies on maternal populations were short abstracts. Conclusions: This review found limited research investigating CCDS systems to support the early detection of sepsis among pediatric, neonatal, and maternal patients, despite the high burden of sepsis in these vulnerable populations. We have highlighted the need for a consensus definition for pediatric and neonatal sepsis and the study of usability and cost-related outcomes as critical areas for future research. International Registered Report Identifier (IRRID): RR2-10.2196/24899 %M 35522467 %R 10.2196/35061 %U https://medinform.jmir.org/2022/5/e35061 %U https://doi.org/10.2196/35061 %U http://www.ncbi.nlm.nih.gov/pubmed/35522467 %0 Journal Article %@ 2563-6316 %I JMIR Publications %V 3 %N 2 %P e22912 %T Using Structural Equation Modelling in Routine Clinical Data on Diabetes and Depression: Observational Cohort Study %A Ronaldson,Amy %A Freestone,Mark %A Zhang,Haoyuan %A Marsh,William %A Bhui,Kamaldeep %+ Wolfson Institute of Population Health, Queen Mary University of London, Centre for Psychiatry and Mental Health, Yvonne Carter Building, London, E1 2AB, United Kingdom, 44 02078822033 ext 2033, m.c.freestone@qmul.ac.uk %K depression %K diabetes %K electronic health records %K acute care %K PLS-SEM %K path analysis %K equation modelling %K accident %K emergency care %K emergency %K structural equation modelling %K clinical data %D 2022 %7 27.4.2022 %9 Original Paper %J JMIRx Med %G English %X Background: Large data sets comprising routine clinical data are becoming increasingly available for use in health research. These data sets contain many clinical variables that might not lend themselves to use in research. Structural equation modelling (SEM) is a statistical technique that might allow for the creation of “research-friendly” clinical constructs from these routine clinical variables and therefore could be an appropriate analytic method to apply more widely to routine clinical data. Objective: SEM was applied to a large data set of routine clinical data developed in East London to model well-established clinical associations. Depression is common among patients with type 2 diabetes, and is associated with poor diabetic control, increased diabetic complications, increased health service utilization, and increased health care costs. Evidence from trial data suggests that integrating psychological treatment into diabetes care can improve health status and reduce costs. Attempting to model these known associations using SEM will test the utility of this technique in routine clinical data sets. Methods: Data were cleaned extensively prior to analysis. SEM was used to investigate associations between depression, diabetic control, diabetic care, mental health treatment, and Accident & Emergency (A&E) use in patients with type 2 diabetes. The creation of the latent variables and the direction of association between latent variables in the model was based upon established clinical knowledge. Results: The results provided partial support for the application of SEM to routine clinical data. Overall, 19% (3106/16,353) of patients with type 2 diabetes had received a diagnosis of depression. In line with known clinical associations, depression was associated with worse diabetic control (β=.034, P<.001) and increased A&E use (β=.071, P<.001). However, contrary to expectation, worse diabetic control was associated with lower A&E use (β=–.055, P<.001) and receipt of mental health treatment did not impact upon diabetic control (P=.39). Receipt of diabetes care was associated with better diabetic control (β=–.072, P<.001), having depression (β=.018, P=.007), and receiving mental health treatment (β=.046, P<.001), which might suggest that comprehensive integrated care packages are being delivered in East London. Conclusions: Some established clinical associations were successfully modelled in a sample of patients with type 2 diabetes in a way that made clinical sense, providing partial evidence for the utility of SEM in routine clinical data. Several issues relating to data quality emerged. Data improvement would have likely enhanced the utility of SEM in this data set. %M 37725546 %R 10.2196/22912 %U https://med.jmirx.org/2022/2/e22912 %U https://doi.org/10.2196/22912 %U http://www.ncbi.nlm.nih.gov/pubmed/37725546 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 9 %N 2 %P e34704 %T A Web-Based Health Application to Translate Nutrition Therapy for Cardiovascular Risk Reduction in Primary Care (PortfolioDiet.app): Quality Improvement and Usability Testing Study %A Kavanagh,Meaghan E %A Chiavaroli,Laura %A Glenn,Andrea J %A Heijmans,Genevieve %A Grant,Shannan M %A Chow,Chi-Ming %A Josse,Robert G %A Malik,Vasanti S %A Watson,William %A Lofters,Aisha %A Holmes,Candice %A Rackal,Julia %A Srichaikul,Kristie %A Sherifali,Diana %A Snelgrove-Clarke,Erna %A Udell,Jacob A %A Juni,Peter %A Booth,Gillian L %A Farkouh,Michael E %A Leiter,Lawrence A %A Kendall,Cyril W C %A Jenkins,David J A %A Sievenpiper,John L %+ Department of Nutritional Sciences, Temerty Faculty of Medicine, University of Toronto, 5th floor, room 5334, Medical Sciences Building, 1 King's College Circle, Toronto, ON, M5S 1A8, Canada, 1 416 867 3732, john.sievenpiper@utoronto.ca %K portfolio diet %K dietary portfolio %K nutrition therapy %K dietary application %K eHealth %K usability testing %K quality improvement %K mobile phone %D 2022 %7 21.4.2022 %9 Original Paper %J JMIR Hum Factors %G English %X Background: The Portfolio Diet, or Dietary Portfolio, is a therapeutic dietary pattern that combines cholesterol-lowering foods to manage dyslipidemia for the prevention of cardiovascular disease. To translate the Portfolio Diet for primary care, we developed the PortfolioDiet.app as a patient and physician educational and engagement tool for PCs and smartphones. The PortfolioDiet.app is currently being used as an add-on therapy to the standard of care (usual care) for the prevention of cardiovascular disease in primary care. To enhance the adoption of this tool, it is important to ensure that the PortfolioDiet.app meets the needs of its target end users. Objective: The main objective of this project is to undertake user testing to inform modifications to the PortfolioDiet.app as part of ongoing engagement in quality improvement (QI). Methods: We undertook a 2-phase QI project from February 2021 to September 2021. We recruited users by convenience sampling. Users included patients, family physicians, and dietitians, as well as nutrition and medical students. For both phases, users were asked to use the PortfolioDiet.app daily for 7 days. In phase 1, a mixed-form questionnaire was administered to evaluate the users’ perceived acceptability, knowledge acquisition, and engagement with the PortfolioDiet.app. The questionnaire collected both quantitative and qualitative data, including 2 open-ended questions. The responses were used to inform modifications to the PortfolioDiet.app. In phase 2, the System Usability Scale was used to assess the usability of the updated PortfolioDiet.app, with a score higher than 70 being considered acceptable. Results: A total of 30 and 19 users were recruited for phase 1 and phase 2, respectively. In phase 1, the PortfolioDiet.app increased users’ perceived knowledge of the Portfolio Diet and influenced their perceived food choices. Limitations identified by users included challenges navigating to resources and profile settings, limited information on plant sterols, inaccuracies in points, timed-logout frustration, request for step-by-step pop-up windows, and request for a mobile app version; when looking at positive feedback, the recipe section was the most commonly praised feature. Between the project phases, 6 modifications were made to the PortfolioDiet.app to incorporate and address user feedback. At phase 2, the average System Usability Scale score was 85.39 (SD 11.47), with 100 being the best possible. Conclusions: By undertaking user testing of the PortfolioDiet.app, its limitations and strengths were able to be identified, informing modifications to the application, which resulted in a clinical tool that better meets users’ needs. The PortfolioDiet.app educates users on the Portfolio Diet and is considered acceptable by users. Although further refinements to the PortfolioDiet.app will continue to be made before its evaluation in a clinical trial, the result of this QI project is an improved clinical tool. %M 35451981 %R 10.2196/34704 %U https://humanfactors.jmir.org/2022/2/e34704 %U https://doi.org/10.2196/34704 %U http://www.ncbi.nlm.nih.gov/pubmed/35451981 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 4 %P e34274 %T Exploring Patient Multimorbidity and Complexity Using Health Insurance Claims Data: A Cluster Analysis Approach %A Nicolet,Anna %A Assouline,Dan %A Le Pogam,Marie-Annick %A Perraudin,Clémence %A Bagnoud,Christophe %A Wagner,Joël %A Marti,Joachim %A Peytremann-Bridevaux,Isabelle %+ Center for Primary Care and Public Health (Unisanté), University of Lausanne, Route de la Corniche, Lausanne, 1010, Switzerland, 41 21 314 23 4, anna.nicolet@unisante.ch %K multimorbidity %K pharmacy cost groups %K cluster analysis %K claims data %K patient complexity %K health claims %K informatics %D 2022 %7 4.4.2022 %9 Original Paper %J JMIR Med Inform %G English %X Background: Although the trend of progressing morbidity is widely recognized, there are numerous challenges when studying multimorbidity and patient complexity. For multimorbid or complex patients, prone to fragmented care and high health care use, novel estimation approaches need to be developed. Objective: This study aims to investigate the patient multimorbidity and complexity of Swiss residents aged ≥50 years using clustering methodology in claims data. Methods: We adopted a clustering methodology based on random forests and used 34 pharmacy-based cost groups as the only input feature for the procedure. To detect clusters, we applied hierarchical density-based spatial clustering of applications with noise. The reasonable hyperparameters were chosen based on various metrics embedded in the algorithms (out-of-bag misclassification error, normalized stress, and cluster persistence) and the clinical relevance of the obtained clusters. Results: Based on cluster analysis output for 18,732 individuals, we identified an outlier group and 7 clusters: individuals without diseases, patients with only hypertension-related diseases, patients with only mental diseases, complex high-cost high-need patients, slightly complex patients with inexpensive low-severity pharmacy-based cost groups, patients with 1 costly disease, and older high-risk patients. Conclusions: Our study demonstrated that cluster analysis based on pharmacy-based cost group information from claims-based data is feasible and highlights clinically relevant clusters. Such an approach allows expanding the understanding of multimorbidity beyond simple disease counts and can identify the population profiles with increased health care use and costs. This study may foster the development of integrated and coordinated care, which is high on the agenda in policy making, care planning, and delivery. %M 35377334 %R 10.2196/34274 %U https://medinform.jmir.org/2022/4/e34274 %U https://doi.org/10.2196/34274 %U http://www.ncbi.nlm.nih.gov/pubmed/35377334 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 9 %N 2 %P e26825 %T Proposal for Post Hoc Quality Control in Instrumented Motion Analysis Using Markerless Motion Capture: Development and Usability Study %A Röhling,Hanna Marie %A Althoff,Patrik %A Arsenova,Radina %A Drebinger,Daniel %A Gigengack,Norman %A Chorschew,Anna %A Kroneberg,Daniel %A Rönnefarth,Maria %A Ellermeyer,Tobias %A Rosenkranz,Sina Cathérine %A Heesen,Christoph %A Behnia,Behnoush %A Hirano,Shigeki %A Kuwabara,Satoshi %A Paul,Friedemann %A Brandt,Alexander Ulrich %A Schmitz-Hübsch,Tanja %+ Experimental and Clinical Research Center, a cooperation between the Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association and the Charité - Universitätsmedizin Berlin, Lindenberger Weg 80, Berlin, 13125, Germany, 49 30 450539718, hanna-marie.roehling@charite.de %K instrumented motion analysis %K markerless motion capture %K visual perceptive computing %K quality control %K quality reporting %K gait analysis %D 2022 %7 1.4.2022 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Instrumented assessment of motor symptoms has emerged as a promising extension to the clinical assessment of several movement disorders. The use of mobile and inexpensive technologies such as some markerless motion capture technologies is especially promising for large-scale application but has not transitioned into clinical routine to date. A crucial step on this path is to implement standardized, clinically applicable tools that identify and control for quality concerns. Objective: The main goal of this study comprises the development of a systematic quality control (QC) procedure for data collected with markerless motion capture technology and its experimental implementation to identify specific quality concerns and thereby rate the usability of recordings. Methods: We developed a post hoc QC pipeline that was evaluated using a large set of short motor task recordings of healthy controls (2010 recordings from 162 subjects) and people with multiple sclerosis (2682 recordings from 187 subjects). For each of these recordings, 2 raters independently applied the pipeline. They provided overall usability decisions and identified technical and performance-related quality concerns, which yielded respective proportions of their occurrence as a main result. Results: The approach developed here has proven user-friendly and applicable on a large scale. Raters’ decisions on recording usability were concordant in 71.5%-92.3% of cases, depending on the motor task. Furthermore, 39.6%-85.1% of recordings were concordantly rated as being of satisfactory quality whereas in 5.0%-26.3%, both raters agreed to discard the recording. Conclusions: We present a QC pipeline that seems feasible and useful for instant quality screening in the clinical setting. Results confirm the need of QC despite using standard test setups, testing protocols, and operator training for the employed system and by extension, for other task-based motor assessment technologies. Results of the QC process can be used to clean existing data sets, optimize quality assurance measures, as well as foster the development of automated QC approaches and therefore improve the overall reliability of kinematic data sets. %M 35363150 %R 10.2196/26825 %U https://humanfactors.jmir.org/2022/2/e26825 %U https://doi.org/10.2196/26825 %U http://www.ncbi.nlm.nih.gov/pubmed/35363150 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 3 %P e32994 %T Synthesizing Dimensions of Digital Maturity in Hospitals: Systematic Review %A Duncan,Rhona %A Eden,Rebekah %A Woods,Leanna %A Wong,Ides %A Sullivan,Clair %+ School of Information Systems, Queensland University of Technology, 2 George Street, Brisbane, 4000, Australia, 61 434237975, rg.eden@qut.edu.au %K digital maturity %K digital capability %K eHealth %K digital hospitals %K capability model %K maturity model %K literature review %K electronic medical records %D 2022 %7 30.3.2022 %9 Review %J J Med Internet Res %G English %X Background: Digital health in hospital settings is viewed as a panacea for achieving the “quadruple aim” of health care, yet the outcomes have been largely inconclusive. To optimize digital health outcomes, a strategic approach is necessary, requiring digital maturity assessments. However, current approaches to assessing digital maturity have been largely insufficient, with uncertainty surrounding the dimensions to assess. Objective: The aim of this study was to identify the current dimensions used to assess the digital maturity of hospitals. Methods: A systematic literature review was conducted of peer-reviewed literature (published before December 2020) investigating maturity models used to assess the digital maturity of hospitals. A total of 29 relevant articles were retrieved, representing 27 distinct maturity models. The articles were inductively analyzed, and the maturity model dimensions were extracted and consolidated into a maturity model framework. Results: The consolidated maturity model framework consisted of 7 dimensions: strategy; information technology capability; interoperability; governance and management; patient-centered care; people, skills, and behavior; and data analytics. These 7 dimensions can be evaluated based on 24 respective indicators. Conclusions: The maturity model framework developed for this study can be used to assess digital maturity and identify areas for improvement. %M 35353050 %R 10.2196/32994 %U https://www.jmir.org/2022/3/e32994 %U https://doi.org/10.2196/32994 %U http://www.ncbi.nlm.nih.gov/pubmed/35353050 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 3 %P e32933 %T Patient Perspectives of Inpatient Telemedicine During the COVID-19 Pandemic: Qualitative Assessment %A Vilendrer,Stacie %A Sackeyfio,Sarah %A Akinbami,Eliel %A Ghosh,Roy %A Luu,Jacklyn Ha %A Pathak,Divya %A Shimada,Masahiro %A Williamson,Emmanuelle Elise %A Shieh,Lisa %+ Division of Primary Care and Population Health, Stanford University School of Medicine, 1265 Welch Rd, Stanford, CA, 94305, United States, 1 952 913 8883, staciev@stanford.edu %K telemedicine %K inpatient %K patient experience %K COVID-19 %K infection control %K quality of health care %K communication %K hospital %K perspective %K qualitative %D 2022 %7 30.3.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Telemedicine has been adopted in the inpatient setting to facilitate clinical interactions between on-site clinicians and isolated hospitalized patients. Such remote interactions have the potential to reduce pathogen exposure and use of personal protective equipment but may also pose new safety concerns given prior evidence that isolated patients can receive suboptimal care. Formal evaluations of the use and practical acceptance of inpatient telemedicine among hospitalized patients are lacking. Objective: We aimed to evaluate the experience of patients hospitalized for COVID-19 with inpatient telemedicine introduced as an infection control measure during the pandemic. Methods: We conducted a qualitative evaluation in a COVID-19 designated non–intensive care hospital unit at a large academic health center (Stanford Health Care) from October 2020 through January 2021. Semistructured qualitative interviews focused on patient experience, impact on quality of care, communication, and mental health. Purposive sampling was used to recruit participants representing diversity across varying demographics until thematic saturation was reached. Interview transcripts were qualitatively analyzed using an inductive-deductive approach. Results: Interviews with 20 hospitalized patients suggested that nonemergency clinical care and bridging to in-person care comprised the majority of inpatient telemedicine use. Nurses were reported to enter the room and call on the tablet far more frequently than physicians, who typically entered the room at least daily. Patients reported broad acceptance of the technology, citing improved convenience and reduced anxiety, but preferred in-person care where possible. Quality of care was believed to be similar to in-person care with the exception of a few patients who wanted more frequent in-person examinations. Ongoing challenges included low audio volume, shifting tablet location, and inconsistent verbal introductions from the clinical team. Conclusions: Patient experiences with inpatient telemedicine were largely favorable. Although most patients expressed a preference for in-person care, telemedicine was acceptable given the circumstances associated with the COVID-19 pandemic. Improvements in technical and care team use may enhance acceptability. Further evaluation is needed to understand the impact of inpatient telemedicine and the optimal balance between in-person and virtual care in the hospital setting. %M 35147510 %R 10.2196/32933 %U https://formative.jmir.org/2022/3/e32933 %U https://doi.org/10.2196/32933 %U http://www.ncbi.nlm.nih.gov/pubmed/35147510 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 3 %P e26511 %T The Role of Health Kiosks: Scoping Review %A Maramba,Inocencio Daniel %A Jones,Ray %A Austin,Daniela %A Edwards,Katie %A Meinert,Edward %A Chatterjee,Arunangsu %+ Centre for Health Technology, University of Plymouth, Drake Circus, Plymouth, PL4 8AA, United Kingdom, 44 1752 587484, inocencio.maramba@plymouth.ac.uk %K kiosk %K health systems %K internet %K review %K online health information %K telemonitoring %K teleconsultation %K consultation %K telemedicine %K behavior %K promotion %K health service %K user experience %K barrier %K facilitator %K remote consultation %K mobile phone %D 2022 %7 29.3.2022 %9 Review %J JMIR Med Inform %G English %X Background: Health kiosks are publicly accessible computing devices that provide access to services, including health information provision, clinical measurement collection, patient self–check-in, telemonitoring, and teleconsultation. Although the increase in internet access and ownership of smart personal devices could make kiosks redundant, recent reports have predicted that the market will continue to grow. Objective: We seek to clarify the current and future roles of health kiosks by investigating the settings, roles, and clinical domains in which kiosks are used; whether usability evaluations of health kiosks are being reported, and if so, what methods are being used; and what the barriers and facilitators are for the deployment of kiosks. Methods: We conducted a scoping review using a bibliographic search of Google Scholar, PubMed, and Web of Science databases for studies and other publications between January 2009 and June 2020. Eligible papers described the implementation as primary studies, systematic reviews, or news and feature articles. Additional reports were obtained by manual searching and querying the key informants. For each article, we abstracted settings, purposes, health domains, whether the kiosk was opportunistic or integrated with a clinical pathway, and whether the kiosk included usability testing. We then summarized the data in frequency tables. Results: A total of 141 articles were included, of which 134 (95%) were primary studies, and 7 (5%) were reviews. Approximately 47% (63/134) of the primary studies described kiosks in secondary care settings. Other settings included community (32/134, 23.9%), primary care (24/134, 17.9%), and pharmacies (8/134, 6%). The most common roles of the health kiosks were providing health information (47/134, 35.1%), taking clinical measurements (28/134, 20.9%), screening (17/134, 12.7%), telehealth (11/134, 8.2%), and patient registration (8/134, 6.0%). The 5 most frequent health domains were multiple conditions (33/134, 24.6%), HIV (10/134, 7.5%), hypertension (10/134, 7.5%), pediatric injuries (7/134, 5.2%), health and well-being (6/134, 4.5%), and drug monitoring (6/134, 4.5%). Kiosks were integrated into the clinical pathway in 70.1% (94/134) of studies, opportunistic kiosks accounted for 23.9% (32/134) of studies, and in 6% (8/134) of studies, kiosks were used in both. Usability evaluations of kiosks were reported in 20.1% (27/134) of papers. Barriers (e.g., use of expensive proprietary software) and enablers (e.g., handling of on-demand consultations) of deploying health kiosks were identified. Conclusions: Health kiosks still play a vital role in the health care system, including collecting clinical measurements and providing access to web-based health services and information to those with little or no digital literacy skills and others without personal internet access. We identified research gaps, such as training needs for teleconsultations and scant reporting on usability evaluation methods. %M 35348457 %R 10.2196/26511 %U https://medinform.jmir.org/2022/3/e26511 %U https://doi.org/10.2196/26511 %U http://www.ncbi.nlm.nih.gov/pubmed/35348457 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 11 %N 3 %P e30454 %T A Quality Improvement Emergency Department Surge Management Platform (SurgeCon): Protocol for a Stepped Wedge Cluster Randomized Trial %A Mariathas,Hensley H %A Hurley,Oliver %A Anaraki,Nahid Rahimipour %A Young,Christina %A Patey,Christopher %A Norman,Paul %A Aubrey-Bassler,Kris %A Wang,Peizhong Peter %A Gadag,Veeresh %A Nguyen,Hai V %A Etchegary,Holly %A McCrate,Farah %A Knight,John C %A Asghari,Shabnam %+ Centre for Rural Health Studies, Faculty of Medicine, Memorial University of Newfoundland, 300 Prince Philip Drive, St. John's, NL, A1B3V6, Canada, 1 709 777 2142, shabnam.asghari@med.mun.ca %K SurgeCon %K emergency department %K stepped wedge design %K cluster randomized trials %K wait time %D 2022 %7 24.3.2022 %9 Protocol %J JMIR Res Protoc %G English %X Background: Despite many efforts, long wait times and overcrowding in emergency departments (EDs) have remained a significant health service issue in Canada. For several years, Canada has had one of the longest wait times among the Organisation for Economic Co-operation and Development countries. From a patient’s perspective, this challenge has been described as “patients wait in pain or discomfort for hours before being seen at EDs.” To overcome the challenge of increased wait times, we developed an innovative ED management platform called SurgeCon that was designed based on continuous quality improvement principles to maintain patient flow and mitigate the impact of patient surge on ED efficiency. The SurgeCon quality improvement intervention includes a protocol-driven software platform, restructures ED organization and workflow, and aims to establish a more patient-centric environment. We piloted SurgeCon at an ED in Carbonear, Newfoundland and Labrador, and found that there was a 32% reduction in ED wait times. Objective: The primary objective of this trial is to determine the effects of SurgeCon on ED performance by assessing its impact on length of stay, the time to a physician’s initial assessment, and the number of patients leaving the ED without being seen by a physician. The secondary objectives of this study are to evaluate SurgeCon’s effects on patient satisfaction and patient-reported experiences with ED wait times and its ability to create better-value care by reducing the per-patient cost of delivering ED services. Methods: The implementation of the intervention will be assessed using a comparative effectiveness-implementation hybrid design. This type of hybrid design is known to shorten the amount of time associated with transitioning interventions from being the focus of research to being used for practice and health care services. All EDs with 24/7 on-site physician support (category A hospitals) will be enrolled in a 31-month, pragmatic, stepped wedge cluster randomized trial. All clusters (hospitals) will start with a baseline period of usual care and will be randomized to determine the order and timing of transitioning to intervention care until all hospitals are using the intervention to manage and operationalize their EDs. Results: Data collection for this study is continuing. As of February 2022, a total of 570 randomly selected patients have participated in telephone interviews concerning patient-reported experiences and patient satisfaction with ED wait times. The first of the 4 EDs was randomly selected, and it is currently using SurgeCon’s eHealth platform and applying efficiency principles that have been learned through training since September 2021. The second randomly selected site will begin intervention implementation in winter 2022. Conclusions: By assessing the impact of SurgeCon on ED services, we hope to be able to improve wait times and create better-value ED care in this health care context. Trial Registration: ClinicalTrials.gov NCT04789902; https://clinicaltrials.gov/ct2/show/NCT04789902 International Registered Report Identifier (IRRID): DERR1-10.2196/30454 %M 35323121 %R 10.2196/30454 %U https://www.researchprotocols.org/2022/3/e30454 %U https://doi.org/10.2196/30454 %U http://www.ncbi.nlm.nih.gov/pubmed/35323121 %0 Journal Article %@ 2371-4379 %I JMIR Publications %V 7 %N 1 %P e23844 %T Small Practices, Big (QI) Dreams: Customizing Quality Improvement (QI) Efforts for Under-Resourced Primary Care Practices to Improve Diabetes Disparities %A Lim,Sahnah %A Islam,Nadia S %+ Department of Population Health, Grossman School of Medicine, New York University, 180 Madison Avenue 8-12, New York, NY, 10016, United States, 1 6465013485, sahnah.lim@nyulangone.org %K electronic health record %K quality improvement %K health equity %K clinical practice guidelines %K diabetes %D 2022 %7 18.3.2022 %9 Viewpoint %J JMIR Diabetes %G English %X Electronic health record quality improvement (QI) initiatives hold great promise in improving adoption of clinical practice guidelines, including those related to diabetes. QI initiatives implemented in under-resourced primary care settings that primarily serve racial/ethnic minority populations have potential to improve quality of care and ultimately improve diabetes disparities. The “Screen at 23” campaign was launched in 2011 to increase screening for prediabetes and diabetes at lower BMI thresholds (ie, 23 kg/m2) for Asian Americans, in line with the new guidelines put forth by the American Diabetes Association. Here, we describe the implementation of a customized electronic health record QI initiative in under-resourced practices that primarily serve low-income South Asian populations in New York City, designed to increase diabetes screening using updated BMI guidelines and in alignment with the “Screen at 23” campaign. The customization involved the implementation of an innovative, semi-manual alternate solution to automated clinical decision support system (CDSS) alerts in order to address the restrictions on customizing CDSS alerts in electronic health record platforms used in small practice settings. We also discuss challenges and strategies with this customized QI effort. Our experience suggests that multisector partnership engagement, user-centered approaches, and informal strategies for relationship building are even more critical in under-resourced, small practice settings. Relatively simple technological solutions can be greatly beneficial in enhancing small practice capacity to engage in larger-scale QI initiatives. Tailored, context-driven approaches for implementation of equity-focused QI initiatives such as the one we describe can increase adoption of clinical practice guidelines, improve diabetes-related outcomes, and improve health disparities among underserved populations.International Registered Report Identifier (IRRID): RR2-10.1186/s13063-019-3711-y %M 35302500 %R 10.2196/23844 %U https://diabetes.jmir.org/2022/1/e23844 %U https://doi.org/10.2196/23844 %U http://www.ncbi.nlm.nih.gov/pubmed/35302500 %0 Journal Article %@ 2561-9128 %I JMIR Publications %V 5 %N 1 %P e35584 %T A Canadian Weekend Elective Pediatric Surgery Program to Reduce the COVID-19–Related Backlog: Operating Room Ramp-Up After COVID-19 Lockdown Ends—Extra Lists (ORRACLE-Xtra) Implementation Study %A Matava,Clyde %A So,Jeannette %A Williams,RJ %A Kelley,Simon %A , %+ Department of Anesthesia and Pain Medicine, Hospital for Sick Children, 555 University Ave, Toronto, ON, M5G 1X8, Canada, 1 4168137445, clyde.matava@sickkids.ca %K waiting lists %K quality improvement %K patient satisfaction %K COVID-19 %K ambulatory surgery %K pandemics %K Canada %D 2022 %7 15.3.2022 %9 Original Paper %J JMIR Perioper Med %G English %X Background: The COVID-19 pandemic caused by the SARS-COV-2 virus has resulted in unprecedented challenges for the health care system. A decrease of surgical services led to substantial backlogs for time-sensitive scheduled pediatric patients. We designed and implemented a novel pilot weekend surgical quality improvement project called Operating Room Ramp-Up After COVID Lockdown Ends—Extra Lists (ORRACLE-Xtra). Objective: Our overall goals are to increase patient access to surgery (and reduce the wait list), improve operating room efficiencies, and optimize parent and staff experience. Methods: Using the DMAIC (define, measure, analyze, improve, control) framework, we implemented ORRACLE-Xtra in a tertiary care academic pediatric hospital during a quiescent period of the COVID-19 pandemic. We defined process and outcome measures based on provincial targets of out-of-window cases. Parental and staff satisfaction was tracked by surveys. Results: ORRACLE-Xtra led to 247 patients receiving surgery during the pilot period, resulting in a 5% decrease in the total number of patients on our wait list with Paediatric Canadian Access Targets for Surgery IV (147/247, 59.5%), with 38.1% (94/247) out-of-window of provincial targets. Most of the process and outcome measures were met or exceeded. Overall parental satisfaction was at 95.8% (110/121), with 79% (64/81) of staff reporting satisfaction with working weekends. Conclusions: Through the ORRACLE-Xtra pilot program, we have shown that hospitals impacted by COVID-19 can reduce the surgical backlog using innovative models of service delivery in a Canadian context. Sustained funding is critical to achieving more meaningful reductions in wait times for scheduled surgeries over the longer term and needs to be balanced with staff well-being. %M 34887242 %R 10.2196/35584 %U https://periop.jmir.org/2022/1/e35584 %U https://doi.org/10.2196/35584 %U http://www.ncbi.nlm.nih.gov/pubmed/34887242 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 3 %P e35104 %T Patient-Level Fall Risk Prediction Using the Observational Medical Outcomes Partnership’s Common Data Model: Pilot Feasibility Study %A Jung,Hyesil %A Yoo,Sooyoung %A Kim,Seok %A Heo,Eunjeong %A Kim,Borham %A Lee,Ho-Young %A Hwang,Hee %+ Office of eHealth Research and Business, Seoul National University Bundang Hospital, 172 Dolma-ro, Bundang-gu, Seongnam-si, 13620, Republic of Korea, 82 31 787 8980, yoosoo0@snubh.org %K common data model %K accidental falls %K Observational Medical Outcomes Partnership %K nursing records %K medical informatics %K health data %K electronic health record %K data model %K prediction model %K risk prediction %K fall risk %D 2022 %7 11.3.2022 %9 Original Paper %J JMIR Med Inform %G English %X Background: Falls in acute care settings threaten patients’ safety. Researchers have been developing fall risk prediction models and exploring risk factors to provide evidence-based fall prevention practices; however, such efforts are hindered by insufficient samples, limited covariates, and a lack of standardized methodologies that aid study replication. Objective: The objectives of this study were to (1) convert fall-related electronic health record data into the standardized Observational Medical Outcome Partnership's (OMOP) common data model format and (2) develop models that predict fall risk during 2 time periods. Methods: As a pilot feasibility test, we converted fall-related electronic health record data (nursing notes, fall risk assessment sheet, patient acuity assessment sheet, and clinical observation sheet) into standardized OMOP common data model format using an extraction, transformation, and load process. We developed fall risk prediction models for 2 time periods (within 7 days of admission and during the entire hospital stay) using 2 algorithms (least absolute shrinkage and selection operator logistic regression and random forest). Results: In total, 6277 nursing statements, 747,049,486 clinical observation sheet records, 1,554,775 fall risk scores, and 5,685,011 patient acuity scores were converted into OMOP common data model format. All our models (area under the receiver operating characteristic curve 0.692-0.726) performed better than the Hendrich II Fall Risk Model. Patient acuity score, fall history, age ≥60 years, movement disorder, and central nervous system agents were the most important predictors in the logistic regression models. Conclusions: To enhance model performance further, we are currently converting all nursing records into the OMOP common data model data format, which will then be included in the models. Thus, in the near future, the performance of fall risk prediction models could be improved through the application of abundant nursing records and external validation. %M 35275076 %R 10.2196/35104 %U https://medinform.jmir.org/2022/3/e35104 %U https://doi.org/10.2196/35104 %U http://www.ncbi.nlm.nih.gov/pubmed/35275076 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 3 %P e26577 %T Standards, Processes, and Tools Used to Evaluate the Quality of Health Information Systems: Systematic Literature Review %A Noël,René %A Taramasco,Carla %A Márquez,Gastón %+ Escuela de Ingeniería Informática, Universidad de Valparaíso, General Cruz 222, Valparaíso, 2340000, Chile, 56 32 250 3630, carla.taramasco@uv.cl %K health information systems %K quality %K standards %K processes %K metrics %K systematic literature review %D 2022 %7 8.3.2022 %9 Review %J J Med Internet Res %G English %X Background: Evaluating health information system (HIS) quality is strategically advantageous for improving the quality of patient care. Nevertheless, few systematic studies have reported what methods, such as standards, processes, and tools, were proposed to evaluate HIS quality. Objective: This study aimed to identify and discuss the existing literature that describes standards, processes, and tools used to evaluate HIS quality. Methods: We conducted a systematic literature review using review guidelines focused on software and systems. We examined seven electronic databases—Scopus, ACM (Association for Computing Machinery), ScienceDirect, Google Scholar, IEEE Xplore, Web of Science, and PubMed—to search for and select primary studies. Results: Out of 782 papers, we identified 17 (2.2%) primary studies. We found that most of the primary studies addressed quality evaluation from a management perspective. On the other hand, there was little explicit and pragmatic evidence on the processes and tools that allowed for the evaluation of HIS quality. Conclusions: To promote quality evaluation of HISs, it is necessary to define mechanisms and methods that operationalize the standards in HISs. Additionally, it is necessary to create metrics that measure the quality of the most critical components and processes of HISs. %M 35258469 %R 10.2196/26577 %U https://www.jmir.org/2022/3/e26577 %U https://doi.org/10.2196/26577 %U http://www.ncbi.nlm.nih.gov/pubmed/35258469 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 6 %N 3 %P e33488 %T Evaluation of a Web-Based Medication Reconciliation Application Within a Primary Care Setting: Cluster-Randomized Controlled Trial %A Gionfriddo,Michael R %A Hu,Yirui %A Maddineni,Bhumika %A Kern,Melissa %A Hayduk,Vanessa %A Kaledas,William R %A Elder,Nevan %A Border,Jeffrey %A Frusciante,Katie %A Kobylinski,Maria %A Wright,Eric A %+ Center for Pharmacy Innovation and Outcomes, Geisinger Health, 100 N Academy Ave Danville, Danville, PA, 17822, United States, 1 570 714 6633, ewright2@geisinger.edu %K medication %K reconciliation %K electronic health record %K information technology %K medication safety %K primary care %K EHR %K safety %K app %K randomized controlled trial %K drug %K interoperability %K information source %K mixed method %K effectiveness %K satisfaction %D 2022 %7 8.3.2022 %9 Original Paper %J JMIR Form Res %G English %X Background: Despite routine review of medication lists during patient encounters, patients’ medication lists are often incomplete and not reflective of actual medication use. Contributing to this situation is the challenge of reconciling medication information from existing health records, along with external locations (eg, pharmacies, other provider/hospital records, and care facilities) and patient-reported use. Advances in the interoperability and digital collection of information provides a foundation for integration of these once disparate information sources. Objective: We aim to evaluate the effectiveness of and satisfaction with an electronic health record (EHR)-integrated web-based medication reconciliation application, MedTrue (MT). Methods: We conducted a cluster-randomized controlled trial of MT in 6 primary care clinics within an integrated health care delivery system. Our primary outcome was medication list accuracy, as determined by a pharmacist-collected best-possible medication history (BPMH). Patient and staff perspectives were evaluated through surveys and semistructured interviews. Results: Overall, 224 patients were recruited and underwent a BPMH with the pharmacist (n=118 [52.7%] usual care [UC], n=106 [47.3%] MT). For our primary outcome of medication list accuracy, 8 (7.5%) patients in the MT arm and 9 (7.6%) in the UC arm had 0 discrepancies (odds ratio=1.01, 95% CI 0.38-2.72, P=.98). The most common discrepancy identified was patients reporting no longer taking a medication (UC mean 2.48 vs MT mean 2.58, P=.21). Patients found MT easy to use and on average would highly recommend MT (average net promoter score=8/10). Staff found MT beneficial but difficult to implement. Conclusions: The use of a web-based application integrated into the EHR which combines EHR, patient-reported data, and pharmacy-dispensed data did not improve medication list accuracy among a population of primary care patients compared to UC but was well received by patients. Future studies should address the limitations of the current application and assess whether improved implementation strategies would impact the effectiveness of the application. %M 35023836 %R 10.2196/33488 %U https://formative.jmir.org/2022/3/e33488 %U https://doi.org/10.2196/33488 %U http://www.ncbi.nlm.nih.gov/pubmed/35023836 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 3 %P e34098 %T An Innovative Telemedical Network to Improve Infectious Disease Management in Critically Ill Patients and Outpatients (TELnet@NRW): Stepped-Wedge Cluster Randomized Controlled Trial %A Marx,Gernot %A Greiner,Wolfgang %A Juhra,Christian %A Elkenkamp,Svenja %A Gensorowsky,Daniel %A Lemmen,Sebastian %A Englbrecht,Jan %A Dohmen,Sandra %A Gottschalk,Antje %A Haverkamp,Miriam %A Hempen,Annette %A Flügel-Bleienheuft,Christian %A Bause,Daniela %A Schulze-Steinen,Henna %A Rademacher,Susanne %A Kistermann,Jennifer %A Hoch,Stefan %A Beckmann,Hans-Juergen %A Lanckohr,Christian %A Lowitsch,Volker %A Peine,Arne %A Juzek-Kuepper,Fabian %A Benstoem,Carina %A Sperling,Kathrin %A Deisz,Robert %+ Department of Intensive Care Medicine and Intermediate Care, Medical Faculty RWTH Aachen, Pauwelsstr. 30, Aachen, 52074, Germany, 49 2418080444, gmarx@ukaachen.de %K telemedicine %K infectious disease medicine %K sepsis %K evidence-based medicine %K eHealth %D 2022 %7 2.3.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: Evidence-based infectious disease and intensive care management is more relevant than ever. Medical expertise in the two disciplines is often geographically limited to university institutions. In addition, the interconnection between inpatient and outpatient care is often insufficient (eg, no shared electronic health record and no digital transfer of patient findings). Objective: This study aims to establish and evaluate a telemedical inpatient-outpatient network based on expert teleconsultations to increase treatment quality in intensive care medicine and infectious diseases. Methods: We performed a multicenter, stepped-wedge cluster randomized trial (February 2017 to January 2020) to establish a telemedicine inpatient-outpatient network among university hospitals, hospitals, and outpatient physicians in North Rhine-Westphalia, Germany. Patients aged ≥18 years in the intensive care unit or consulting with a physician in the outpatient setting were eligible. We provided expert knowledge from intensivists and infectious disease specialists through advanced training courses and expert teleconsultations with 24/7/365 availability on demand respectively once per week to enhance treatment quality. The primary outcome was adherence to the 10 Choosing Wisely recommendations for infectious disease management. Guideline adherence was analyzed using binary logistic regression models. Results: Overall, 159,424 patients (10,585 inpatients and 148,839 outpatients) from 17 hospitals and 103 outpatient physicians were included. There was a significant increase in guideline adherence in the management of Staphylococcus aureus infections (odds ratio [OR] 4.00, 95% CI 1.83-9.20; P<.001) and in sepsis management in critically ill patients (OR 6.82, 95% CI 1.27-56.61; P=.04). There was a statistically nonsignificant decrease in sepsis-related mortality from 29% (19/66) in the control group to 23.8% (50/210) in the intervention group. Furthermore, the extension of treatment with prophylactic antibiotics after surgery was significantly less likely (OR 9.37, 95% CI 1.52-111.47; P=.04). Patients treated by outpatient physicians, who were regularly participating in expert teleconsultations, were also more likely to be treated according to guideline recommendations regarding antibiotic therapy for uncomplicated upper respiratory tract infections (OR 1.34, 95% CI 1.16-1.56; P<.001) and asymptomatic bacteriuria (OR 9.31, 95% CI 3.79-25.94; P<.001). For the other recommendations, we found no significant effects, or we had too few observations to generate models. The key limitations of our study include selection effects due to the applied on-site triage of patients as well as the limited possibilities to control for secular effects. Conclusions: Telemedicine facilitates a direct round-the-clock interaction over broad distances between intensivists or infectious disease experts and physicians who care for patients in hospitals without ready access to these experts. Expert teleconsultations increase guideline adherence and treatment quality in infectious disease and intensive care management, creating added value for critically ill patients. Trial Registration: ClinicalTrials.gov NCT03137589; https://clinicaltrials.gov/ct2/show/NCT03137589 %M 35103604 %R 10.2196/34098 %U https://www.jmir.org/2022/3/e34098 %U https://doi.org/10.2196/34098 %U http://www.ncbi.nlm.nih.gov/pubmed/35103604 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 9 %N 1 %P e33651 %T Usage and Usability of a National e-Library for Chemotherapy Regimens: Mixed Methods Study %A Fyhr,AnnSofie %A Persson,Johanna %A Ek,Åsa %+ Regional Cancer Centre South, Region Skåne, Medicon Village, Scheeletorget 1, Lund, SE-223 81, Sweden, 46 46 275 23 51, ann-sofie.fyhr@skane.se %K chemotherapy regimens %K user evaluation %K standardization %K patient safety %K chemotherapy %K safety %K usability %K e-library %K medication errors %D 2022 %7 17.2.2022 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Accurate information about chemotherapy drugs and regimens is needed to reduce chemotherapy errors. A national e-library, as a common knowledge source with standardized chemotherapy nomenclature and content, was developed. Since the information in the library is both complex and extensive, it is central that the users can use the resource as intended. Objective: The aim of this study was to evaluate the usage and usability of an extensive e-library for chemotherapy regimens developed to reduce medication errors, support the health care staff in their work, and increase patient safety. Methods: To obtain a comprehensive evaluation, a mixed methods study was performed for a broad view of the usage, including a compilation of subjective views of the users (web survey, spontaneous user feedback, and qualitative interviews), analysis of statistics from the website, and an expert evaluation of the usability of the webpage. Results: Statistics from the website show an average of just over 2500 visits and 870 unique visitors per month. Most visits took place Mondays to Fridays, but there were 5-10 visits per day on weekends. The web survey, with 292 answers, shows that the visitors were mainly physicians and nurses. Almost 80% (224/292) of respondents searched for regimens and 90% (264/292) found what they were looking for and were satisfied with their visit. The expert evaluation shows that the e-library follows many existing design principles, thus providing some useful improvement suggestions. A total of 86 emails were received in 2020 with user feedback, most of which were from nurses. The main part (78%, 67/86) contained a question, and the rest had discovered errors mainly in some regimen. The interviews reveal that most hospitals use a computerized physician order entry system, and they use the e-library in various ways, import XML files, transfer information, or use it as a reference. One hospital without a system uses the administration schedules from the library. Conclusions: The user evaluation indicates that the e-library is used in the intended manner and that the users can interact without problems. Users have different needs depending on their profession and their workplace, and these can be supported. The combination of methods applied ensures that the design and content comply with the users’ needs and serves as feedback for continuous design and learning. With a broad national usage, the e-library can become a source for organizational and national learning and a source for continuous improvement of cancer care in Sweden. %M 35175199 %R 10.2196/33651 %U https://humanfactors.jmir.org/2022/1/e33651 %U https://doi.org/10.2196/33651 %U http://www.ncbi.nlm.nih.gov/pubmed/35175199 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 2 %P e32373 %T Exploring Quality Differences in Telemedicine Between Hospital Outpatient Departments and Community Clinics: Cross-sectional Study %A Alhajri,Noora %A Simsekler,Mecit Can Emre %A Alfalasi,Buthaina %A Alhashmi,Mohamed %A Memon,Hamda %A Housser,Emma %A Abdi,Abdulhamid Mustafa %A Balalaa,Nahed %A Al Ali,Maryam %A Almaashari,Raghda %A Al Memari,Shammah %A Al Hosani,Farida %A Al Zaabi,Yousif %A Almazrouei,Shereena %A Alhashemi,Hamed %+ College of Medicine and Health Science, Khalifa University, Al-Saada Road, Zone 1, P O Box 11001, Abu Dhabi, United Arab Emirates, 971 552277490, nalhajri007@gmail.com %K COVID-19 %K patient satisfaction %K technology acceptance %K hospital %K community clinic %K video consultation %K audio consultation %K outpatient department %K OPD %K policy making %K UAE %D 2022 %7 15.2.2022 %9 Original Paper %J JMIR Med Inform %G English %X Background: Telemedicine is a care delivery modality that has the potential to broaden the reach and flexibility of health care services. In the United Arab Emirates, telemedicine services are mainly delivered through either integrated hospital outpatient department (OPDs) or community clinics. However, it is unknown if patients’ perceptions of, and satisfaction with, telemedicine services differ between these two types of health care systems during the COVID-19 pandemic. Objective: We aimed to explore the differences in patients’ perceptions of, and satisfaction with, telemedicine between hospital OPDs and community clinics during the COVID-19 pandemic. We also aimed to identify patient- or visit-related characteristics contributing to patient satisfaction with telemedicine. Methods: In this cross-sectional study that was conducted at Abu Dhabi health care centers, we invited outpatients aged 18 years or over, who completed a telemedicine visit during the COVID-19 pandemic, to participate in our study. Patients’ perceptions of, and satisfaction with, telemedicine regarding the two system types (ie, hospital OPDs and community clinics) were assessed using an online survey that was sent as a link through the SMS system. Regression models were used to describe the association between patient- and visit-related characteristics, as well as the perception of, and satisfaction with, telemedicine services. Results: A total of 515 patients participated in this survey. Patients’ satisfaction with telemedicine services was equally high among the settings, with no statistically significant difference between the two setting types (hospital OPDs: 253/343, 73.8%; community clinics: 114/172, 66.3%; P=.19). Video consultation was significantly associated with increased patient satisfaction (odds ratio [OR] 2.57, 95% CI 1.04-6.33; P=.04) and patients’ support of the transition to telemedicine use during and after the pandemic (OR 2.88, 95% CI 1.18-7.07; P=.02). Patients who used video consultations were more likely to report that telemedicine improved access to health care services (OR 3.06, 95% CI 1.71-8.03; P=.02), reduced waiting times and travel costs (OR 4.94, 95% CI 1.15-21.19; P=.03), addressed patients’ needs (OR 2.63, 95% CI 1.13-6.11; P=.03), and eased expression of patients’ medical concerns during the COVID-19 pandemic (OR 2.19, 95% CI 0.89-5.38; P=.09). Surprisingly, middle-aged patients were two times more likely to be satisfied with telemedicine services (OR 2.12, 95% CI 1.09-4.14; P=.03), as compared to any other age group in this study. Conclusions: These findings suggest that patient satisfaction was unaffected by the health system setting in which patients received the teleconsultations, whether they were at hospitals or community clinics. Video consultation was associated with increased patient satisfaction with telemedicine services. Efforts should be focused on strategic planning for enhanced telemedicine services, video consultation in particular, for both emergent circumstances, such as the COVID-19 pandemic, and day-to-day health care delivery. %M 34978281 %R 10.2196/32373 %U https://medinform.jmir.org/2022/2/e32373 %U https://doi.org/10.2196/32373 %U http://www.ncbi.nlm.nih.gov/pubmed/34978281 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 2 %P e32695 %T State-of-the-art Dashboards on Clinical Indicator Data to Support Reflection on Practice: Scoping Review %A Bucalon,Bernard %A Shaw,Tim %A Brown,Kerri %A Kay,Judy %+ Human Centred Technology Cluster, School of Computer Science, The University of Sydney, Level 3, Computer Science Building J12, 1 Cleveland St, Darlington, NSW 2008, Australia, 61 2 8627 0010, bernard.bucalon@sydney.edu.au %K practice analytics dashboards %K data visualization %K reflective practice %K professional learning %K mobile phone %D 2022 %7 14.2.2022 %9 Review %J JMIR Med Inform %G English %X Background: There is an increasing interest in using routinely collected eHealth data to support reflective practice and long-term professional learning. Studies have evaluated the impact of dashboards on clinician decision-making, task completion time, user satisfaction, and adherence to clinical guidelines. Objective: This scoping review aims to summarize the literature on dashboards based on patient administrative, medical, and surgical data for clinicians to support reflective practice. Methods: A scoping review was conducted using the Arksey and O’Malley framework. A search was conducted in 5 electronic databases (MEDLINE, Embase, Scopus, ACM Digital Library, and Web of Science) to identify studies that met the inclusion criteria. Study selection and characterization were performed by 2 independent reviewers (BB and CP). One reviewer extracted the data that were analyzed descriptively to map the available evidence. Results: A total of 18 dashboards from 8 countries were assessed. Purposes for the dashboards were designed for performance improvement (10/18, 56%), to support quality and safety initiatives (6/18, 33%), and management and operations (4/18, 22%). Data visualizations were primarily designed for team use (12/18, 67%) rather than individual clinicians (4/18, 22%). Evaluation methods varied among asking the clinicians directly (11/18, 61%), observing user behavior through clinical indicators and use log data (14/18, 78%), and usability testing (4/18, 22%). The studies reported high scores on standard usability questionnaires, favorable surveys, and interview feedback. Improvements to underlying clinical indicators were observed in 78% (7/9) of the studies, whereas 22% (2/9) of the studies reported no significant changes in performance. Conclusions: This scoping review maps the current literature landscape on dashboards based on routinely collected clinical indicator data. Although there were common data visualization techniques and clinical indicators used across studies, there was diversity in the design of the dashboards and their evaluation. There was a lack of detail regarding the design processes documented for reproducibility. We identified a lack of interface features to support clinicians in making sense of and reflecting on their personal performance data. %M 35156928 %R 10.2196/32695 %U https://medinform.jmir.org/2022/2/e32695 %U https://doi.org/10.2196/32695 %U http://www.ncbi.nlm.nih.gov/pubmed/35156928 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 9 %N 1 %P e27887 %T Enriching the Value of Patient Experience Feedback: Web-Based Dashboard Development Using Co-design and Heuristic Evaluation %A Khanbhai,Mustafa %A Symons,Joshua %A Flott,Kelsey %A Harrison-White,Stephanie %A Spofforth,Jamie %A Klaber,Robert %A Manton,David %A Darzi,Ara %A Mayer,Erik %+ Patient Safety Translational Research Centre, Imperial College London, National Institute for Health Research/Institute of Global Health Innovation, Queen Elizabeth the Queen Mother Wing, St Mary's Campus, London, W2 1NY, United Kingdom, 44 02033126428, m.khanbhai@imperial.ac.uk %K patient experience %K friends and family test %K quality dashboard %K co-design %K heuristic evaluation %K usability %D 2022 %7 3.2.2022 %9 Original Paper %J JMIR Hum Factors %G English %X Background: There is an abundance of patient experience data held within health care organizations, but stakeholders and staff are often unable to use the output in a meaningful and timely way to improve care delivery. Dashboards, which use visualized data to summarize key patient experience feedback, have the potential to address these issues. Objective: The aim of this study is to develop a patient experience dashboard with an emphasis on Friends and Family Test (FFT) reporting, as per the national policy drive. Methods: A 2-stage approach was used—participatory co-design involving 20 co-designers to develop a dashboard prototype, followed by iterative dashboard testing. Language analysis was performed on free-text patient experience data from the FFT, and the themes and sentiments generated were used to populate the dashboard with associated FFT metrics. Heuristic evaluation and usability testing were conducted to refine the dashboard and assess user satisfaction using the system usability score. Results: The qualitative analysis from the co-design process informed the development of the dashboard prototype with key dashboard requirements and a significant preference for bubble chart display. The heuristic evaluation revealed that most cumulative scores had no usability problems (18/20, 90%), had cosmetic problems only (7/20, 35%), or had minor usability problems (5/20, 25%). The mean System Usability Scale score was 89.7 (SD 7.9), suggesting an excellent rating. Conclusions: The growing capacity to collect and process patient experience data suggests that data visualization will be increasingly important in turning feedback into improvements to care. Through heuristic usability, we demonstrated that very large FFT data can be presented in a thematically driven, simple visual display without the loss of the nuances and still allow for the exploration of the original free-text comments. This study establishes guidance for optimizing the design of patient experience dashboards that health care providers find meaningful, which in turn drives patient-centered care. %M 35113022 %R 10.2196/27887 %U https://humanfactors.jmir.org/2022/1/e27887 %U https://doi.org/10.2196/27887 %U http://www.ncbi.nlm.nih.gov/pubmed/35113022 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 2 %P e31184 %T Continuous Glucose Monitoring With Low-Carbohydrate Nutritional Coaching to Improve Type 2 Diabetes Control: Randomized Quality Improvement Program %A Griauzde,Dina H %A Ling,Grace %A Wray,Daniel %A DeJonckheere,Melissa %A Mizokami Stout,Kara %A Saslow,Laura R %A Fenske,Jill %A Serlin,David %A Stonebraker,Spring %A Nisha,Tabassum %A Barry,Colton %A Pop-Busui,Rodica %A Sen,Ananda %A Richardson,Caroline R %+ VA Ann Arbor Healthcare System, 2215 Fuller Rd, Ann Arbor, MI, 48105, United States, 1 603 860 1066, dhafez@med.umich.edu %K type 2 diabetes mellitus %K continuous glucose monitoring %K low-carbohydrate counseling %D 2022 %7 2.2.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: Type 2 diabetes mellitus (T2DM) is a leading cause of morbidity and mortality globally, with adverse health consequences largely related to hyperglycemia. Despite clinical practice guideline recommendations, effective pharmacotherapy, and interventions to support patients and providers, up to 60% of patients diagnosed with T2DM are estimated to have hemoglobin A1c (HbA1c) levels above the recommended targets owing to multilevel barriers hindering optimal glycemic control. Objective: The aim of this study is to compare changes in HbA1c levels among patients with suboptimally controlled T2DM who were offered the opportunity to use an intermittently viewed continuous glucose monitor and receive personalized low-carbohydrate nutrition counseling (<100 g/day) versus those who received usual care (UC). Methods: This was a 12-month, pragmatic, randomized quality improvement program. All adult patients with T2DM who received primary care at a university-affiliated primary care clinic (N=1584) were randomized to either the UC or the enhanced care (EC) group. Within each program arm, we identified individuals with HbA1c >7.5% (58 mmol/mol) who were medically eligible for tighter glycemic control, and we defined these subgroups as UC–high risk (UC-HR) or EC-HR. UC-HR participants (n=197) received routine primary care. EC-HR participants (n=185) were invited to use an intermittently viewed continuous glucose monitor and receive low-carbohydrate nutrition counseling. The primary outcome was mean change in HbA1c levels from baseline to 12 months using an intention-to-treat difference-in-differences analysis comparing EC-HR with UC-HR groups. We conducted follow-up semistructured interviews to understand EC-HR participant experiences with the intervention. Results: HbA1c decreased by 0.41% (4.5 mmol/mol; P=.04) more from baseline to 12 months among participants in the EC-HR group than among those in UC-HR; however, only 61 (32.9%) of 185 EC-HR participants engaged in the program. Among the EC-HR participants who wore continuous glucose monitors (61/185, 32.9%), HbA1c was 1.1% lower at 12 months compared with baseline (P<.001). Interviews revealed themes related to EC-HR participants’ program engagement and continuous glucose monitor use. Conclusions: Among patients with suboptimally controlled T2DM, a combined approach that includes continuous glucose monitoring and low-carbohydrate nutrition counseling can improve glycemic control compared with the standard of care. %M 35107429 %R 10.2196/31184 %U https://www.jmir.org/2022/2/e31184 %U https://doi.org/10.2196/31184 %U http://www.ncbi.nlm.nih.gov/pubmed/35107429 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 9 %N 1 %P e23833 %T An Information Directory App InHouse Call for Streamlining Communication to Optimize Efficiency and Patient Care in a Hospital: Pilot Mixed Methods Design and Utility Study %A Schilling,George %A Villarosa,Leonardo %+ Vidant Medical Center, 2100 Statonsburg Rd, Greenville, NC, 27834, United States, 1 252 847 4441, georgeschilling@gmail.com %K InHouse Call %K communication %K hospital directory %K healthcare %K health care %K health informatics %K mHealth %K mobile app %K digital health %K patient records %K electronic health %D 2022 %7 27.1.2022 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Communication failures disrupt physician workflow, lead to poor patient outcomes, and are associated with significant economic burden. To increase efficiency when contacting a team member in a hospital, we have designed an information directory app, InHouse Call. Objective: This study aimed to describe the design of InHouse Call, objectively compare the usefulness of the app versus that of traditional methods (operator or pocket cards, etc), and determine its subjective usefulness through user surveys and a net promoter score (NPS). Methods: This pilot study utilizing before-after trials was carried out at a tertiary academic hospital and involved 20 clinicians, including physiatrists, hospitalists, internal medicine and family medicine residents, and advanced practice providers/nurse practitioners/physician assistants. InHouse Call was designed to efficiently supply contact information to providers through a simple, user-friendly interface. The participants used InHouse Call in timed trials to contact a health care team member in the hospital via a telephone call. The effectiveness of InHouse Call in connecting the user with a contact in the hospital was measured through timed trials comparing the amount of time spent in attempting to make the connection using traditional methods versus the app. Usability was measured through exit surveys and NPS. Results: The average time spent connecting to the correct contact using traditional methods was 59.5 seconds, compared to 13.8 seconds when using InHouse Call. The degree of variance when using traditional methods was 1544.2, compared to 19.7 with InHouse Call. A call made using the traditional methods deviated from the mean by 39.3 seconds, compared to 4.4 seconds when using InHouse Call. InHouse Call achieved an NPS of 95. Conclusions: InHouse Call significantly reduced the average amount of time spent connecting with the correct contact as well as the variability to complete the task, thus proving to be the superior method of communication for health care providers. The app garnered a high NPS and positive subjective feedback. %M 35084350 %R 10.2196/23833 %U https://humanfactors.jmir.org/2022/1/e23833 %U https://doi.org/10.2196/23833 %U http://www.ncbi.nlm.nih.gov/pubmed/35084350 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 11 %N 1 %P e31123 %T Assessment of Glycemic Control at St. Luke’s Free Medical Clinic: Retrospective Chart Review %A Hopper,Wade %A Fox,Justin %A Dimucci-Ward,JuliSu %+ Department of Surgery, Edward Via College of Osteopathic Medicine - Carolinas, 350 Howard St, Spartanburg, SC, 29303, United States, 1 8643279800, whopper@carolinas.vcom.edu %K free clinic %K glycemic control %K underserved %K uninsured %K diabetes %K health care delivery %K treatment program %D 2022 %7 24.1.2022 %9 Original Paper %J Interact J Med Res %G English %X Background: A free clinic is a health care delivery model that provides primary care and pharmaceutical services exclusively to uninsured patients. With a multidisciplinary volunteer clinical staff, which includes physicians, social workers, dieticians, and osteopathic medical students, St. Luke’s Free Medical Clinic (SLFMC) cares for over 1700 patients annually in Spartanburg, South Carolina. Objective: This study aims to measure the change, over time, in patient hemoglobin A1c measurements at the SLFMC to quantify the success of the clinic’s diabetes treatment program. Methods: A prospective-retrospective chart review of patients (n=140) enrolled at the SLFMC between January 1, 2018, and January 1, 2021, was performed. Patients were stratified as having controlled (hemoglobin A1c<7.0, n=53) or uncontrolled (hemoglobin A1c≥7.0, n=87) diabetes relative to a therapeutic hemoglobin A1c target of 7.0, which is recommended by the American Diabetes Association. For both controlled and uncontrolled groups, baseline hemoglobin A1c values were compared to subsequent readings using a Wilcoxon matched-pairs signed rank test. Results from the SLFMC population were compared to the published literature on hemoglobin A1c from other free clinics. Results: Patients with uncontrolled diabetes experienced significant reductions in median hemoglobin A1c at both 6 months (P=.006) and 1 year (P=.002) from baseline. Patients with controlled diabetes showed no significant changes. Black and Hispanic patients with uncontrolled diabetes experienced a 1.0% mean improvement in hemoglobin A1c over the study window. The SLFMC’s wholly uninsured patient population showed a population rate of controlled diabetes (42%), which was similar to recent nationwide averages for adults with diabetes (51% to 56%), as reported by the National Health and Nutrition Examination Survey. The clinic’s Hispanic population (n=47) showed the greatest average improvement in hemoglobin A1c of any ethnic group from baseline. Additionally, 61% of the SLFMC’s Black population (n=33) achieved a hemoglobin A1c of <7.0 by the end of the study window, which surpassed the nationwide averages for glycemic control. Conclusions: We present free clinic hemoglobin A1c outcomes obtained through a retrospective chart review. Uninsured patients treated for diabetes at the SLFMC show a reduction in hemoglobin A1c, which is comparable to nationwide standards, although average hemoglobin A1c levels in this study were higher than nationwide averages. Black and Hispanic patients with uncontrolled diabetes showed a mean 1% improvement in hemoglobin A1c levels. These results represent some of the first in the literature emerging from a free clinic that is not affiliated with a major medical school. %M 35072636 %R 10.2196/31123 %U https://www.i-jmr.org/2022/1/e31123 %U https://doi.org/10.2196/31123 %U http://www.ncbi.nlm.nih.gov/pubmed/35072636 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 11 %N 1 %P e31365 %T A Nationwide Evaluation of the Prevalence of Human Papillomavirus in Brazil (POP-Brazil Study): Protocol for Data Quality Assurance and Control %A Horvath,Jaqueline Driemeyer Correia %A Bessel,Marina %A Kops,Natália Luiza %A Souza,Flávia Moreno Alves %A Pereira,Gerson Mendes %A Wendland,Eliana Marcia %+ Escritório de Projetos, Programa de Apoio ao Desenvolvimento Institucional do Sistema Único de Saúde, Hospital Moinhos de Vento, Rua Ramiro Barcelos 910, Porto Alegre, 90035-004, Brazil, 55 51 33143600, elianawend@gmail.com %K quality control %K quality assurance %K evidence-based medicine %K quality data %D 2022 %7 5.1.2022 %9 Protocol %J JMIR Res Protoc %G English %X Background: The credibility of a study and its internal and external validity depend crucially on the quality of the data produced. An in-depth knowledge of quality control processes is essential as large and integrative epidemiological studies are increasingly prioritized. Objective: This study aimed to describe the stages of quality control in the POP-Brazil study and to present an analysis of the quality indicators. Methods: Quality assurance and control were initiated with the planning of this nationwide, multicentric study and continued through the development of the project. All quality control protocol strategies, such as training, protocol implementation, audits, and inspection, were discussed one by one. We highlight the importance of conducting a pilot study that provides the researcher the opportunity to refine or modify the research methodology and validating the results through double data entry, test-retest, and analysis of nonresponse rates. Results: This cross-sectional, nationwide, multicentric study recruited 8628 sexually active young adults (16-25 years old) in 119 public health units between September 2016 and November 2017. The Human Research Ethics Committee of the Moinhos de Vento Hospital approved this project. Conclusions: Quality control processes are a continuum, not restricted to a single event, and are fundamental to the success of data integrity and the minimization of bias in epidemiological studies. The quality control steps described can be used as a guide to implement evidence-based, valid, reliable, and useful procedures in most observational studies to ensure data integrity. International Registered Report Identifier (IRRID): RR1-10.2196/31365 %M 34989680 %R 10.2196/31365 %U https://www.researchprotocols.org/2022/1/e31365 %U https://doi.org/10.2196/31365 %U http://www.ncbi.nlm.nih.gov/pubmed/34989680 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 11 %N 1 %P e32635 %T Reducing Delays in Diagnosing Primary Immunodeficiency Through the Development and Implementation of a Clinical Decision Support Tool: Protocol for a Quality Improvement Project %A Kumar,Bharat %A Zetumer,Samuel %A Swee,Melissa %A Endelman,Ellen L Keyser %A Suneja,Manish %A Davis,Benjamin %+ Division of Immunology, Department of Internal Medicine, University of Iowa Carver College of Medicine, 200 Hawkins Drive, Iowa City, IA, 52242, United States, 1 319 356 1711, bharat-kumar@uiowa.edu %K immunology %K clinical decision support %K diagnostic decision-making %D 2022 %7 4.1.2022 %9 Protocol %J JMIR Res Protoc %G English %X Background: Primary immunodeficiencies (PIs) are a set of heterogeneous chronic disorders characterized by immune dysfunction. They are diagnostically challenging because of their clinical heterogeneity, knowledge gaps among primary care physicians, and continuing shortages of clinically trained immunologists. As a result, patients with undiagnosed PIs are at increased risk for recurrent infections, cancers, and autoimmune diseases. Objective: The aim of this research is to develop and implement a clinical decision support (CDS) tool for the identification of underlying PIs. Methods: We will develop and implement a CDS tool for the identification of underlying PIs among patients who receive primary care through a health care provider at the University of Iowa Hospitals and Clinics. The CDS tool will function through an algorithm that is based on the Immune Deficiency Foundation’s 10 Warning Signs for Primary Immunodeficiency. Over the course of a year, we will use Lean Six Sigma principles and the Define, Measure, Analyze, Improve, and Control (DMAIC) framework to guide the project. The primary measure is the number of newly diagnosed PI patients per month. Secondary measures include the following: (1) the number of new patients identified by the CDS as being at high risk for PI, (2) the number of new PI cases in which immunoglobulin replacement or rotating antibiotics are started, (3) the cost of evaluation of each patient identified by the CDS tool as being at high risk for PIs, (4) the number of new consults not diagnosed with a PI, and (5) patient satisfaction with the process of referral to the Immunology Clinic. Results: This study was determined to not be Human Subjects Research by the Institutional Review Board at the University of Iowa. Data collection will begin in August 2021. Conclusions: The development and implementation of a CDS tool is a promising approach to identifying patients with underlying PI. This protocol assesses whether such an approach will be able to achieve its objective of reducing diagnostic delays. The disciplined approach, using Lean Six Sigma and the DMAIC framework, will guide implementation to maximize opportunities for a successful intervention that meets the study’s goals and objectives as well as to allow for replication and adaptation of these methods at other sites. International Registered Report Identifier (IRRID): PRR1-10.2196/32635 %M 34587114 %R 10.2196/32635 %U https://www.researchprotocols.org/2022/1/e32635 %U https://doi.org/10.2196/32635 %U http://www.ncbi.nlm.nih.gov/pubmed/34587114 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 12 %P e31042 %T Measuring and Improving Evidence-Based Patient Care Using a Web-Based Gamified Approach in Primary Care (QualityIQ): Randomized Controlled Trial %A Burgon,Trever %A Casebeer,Linda %A Aasen,Holly %A Valdenor,Czarlota %A Tamondong-Lachica,Diana %A de Belen,Enrico %A Paculdo,David %A Peabody,John %+ QURE Healthcare, 450 Pacific Ave, Suite 200, San Francisco, CA, 94133, United States, 1 4153213388 ext 101, jpeabody@qurehealthcare.com %K quality improvement %K physician engagement %K MIPS %K case simulation %K feedback %K value-based care %K care standardization %K simulation %K gamification %K medical education %K continuing education %K outcome %K serious game %K decision-support %D 2021 %7 23.12.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Unwarranted variability in clinical practice is a challenging problem in practice today, leading to poor outcomes for patients and low-value care for providers, payers, and patients. Objective: In this study, we introduced a novel tool, QualityIQ, and determined the extent to which it helps primary care physicians to align care decisions with the latest best practices included in the Merit-Based Incentive Payment System (MIPS). Methods: We developed the fully automated QualityIQ patient simulation platform with real-time evidence-based feedback and gamified peer benchmarking. Each case included workup, diagnosis, and management questions with explicit evidence-based scoring criteria. We recruited practicing primary care physicians across the United States into the study via the web and conducted a cross-sectional study of clinical decisions among a national sample of primary care physicians, randomized to continuing medical education (CME) and non-CME study arms. Physicians “cared” for 8 weekly cases that covered typical primary care scenarios. We measured participation rates, changes in quality scores (including MIPS scores), self-reported practice change, and physician satisfaction with the tool. The primary outcomes for this study were evidence-based care scores within each case, adherence to MIPS measures, and variation in clinical decision-making among the primary care providers caring for the same patient. Results: We found strong, scalable engagement with the tool, with 75% of participants (61 non-CME and 59 CME) completing at least 6 of 8 total cases. We saw significant improvement in evidence-based clinical decisions across multiple conditions, such as diabetes (+8.3%, P<.001) and osteoarthritis (+7.6%, P=.003) and with MIPS-related quality measures, such as diabetes eye examinations (+22%, P<.001), depression screening (+11%, P<.001), and asthma medications (+33%, P<.001). Although the CME availability did not increase enrollment in the study, participants who were offered CME credits were more likely to complete at least 6 of the 8 cases. Conclusions: Although CME availability did not prove to be important, the short, clinically detailed case simulations with real-time feedback and gamified peer benchmarking did lead to significant improvements in evidence-based care decisions among all practicing physicians. Trial Registration: ClinicalTrials.gov NCT03800901; https://clinicaltrials.gov/ct2/show/NCT03800901 %M 34941547 %R 10.2196/31042 %U https://www.jmir.org/2021/12/e31042 %U https://doi.org/10.2196/31042 %U http://www.ncbi.nlm.nih.gov/pubmed/34941547 %0 Journal Article %@ 2561-9128 %I JMIR Publications %V 4 %N 2 %P e26613 %T Management of Acute Appendicitis in Children During COVID-19 and Perspectives of Pediatric Surgeons From South Asia: Survey Study %A Hannan,Md Jafrul %A Parveen,Mosammat Kohinoor %A Hoque,Md Mozammel %A Chowdhury,Tanvir Kabir %A Hasan,Md Samiul %A Nandy,Alak %+ Department of Pediatric Surgery, South Point Hospital, Apt B3, House 72/A, Road 1, Panchlaish, Chittagong, 4100, Bangladesh, 880 1819345305, jafrulhannan@gmail.com %K COVID-19 %K gastrointestinal %K pediatric %K global surgery %D 2021 %7 21.12.2021 %9 Original Paper %J JMIR Perioper Med %G English %X Background: Nonoperative treatment (NOT) of pediatric appendicitis as opposed to surgery elicits great debate and is potentially influenced by physician preferences. Owing to the effects of the COVID-19 pandemic on health care, the practice of NOT has generally increased by necessity and may, in a post–COVID-19 world, change surgeons’ perceptions of NOT. Objective: The aim of this study was to determine whether the use of NOT has increased in South Asia and whether these levels of practice would be sustained after the pandemic subsides. Methods: A survey was conducted among pediatric surgeons regarding their position, institute, and country; the number of appendicitis cases they managed; and their mode of treatment between identical time periods in 2019 and 2020 (April 1 to August 31). The survey also directly posed the question as to whether they would continue with the COVID-19–imposed level of NOT after the effect of the pandemic diminishes. Results: A total of 134 responses were collected out of 200 (67.0%). A significant increase in the practice of NOT was observed for the entire cohort, although no effect was observed when grouped by country or institute. When grouped by position, senior physicians increased the practice of NOT the most, while junior physicians reported the least change. The data suggest that only professors would be inclined to maintain the COVID-19–level of NOT practice after the pandemic. Conclusions: Increased practice of NOT during the COVID-19 pandemic was observed in South Asia, particularly by senior surgeons. Only professors appeared inclined to consider maintaining this increased level of practice in the post–COVID-19 world. %M 34818209 %R 10.2196/26613 %U https://periop.jmir.org/2021/2/e26613 %U https://doi.org/10.2196/26613 %U http://www.ncbi.nlm.nih.gov/pubmed/34818209 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 12 %P e25899 %T Use of the McIsaac Score to Predict Group A Streptococcal Pharyngitis in Outpatient Nurse Phone Triage and Electronic Visits Compared With In-Person Visits: Retrospective Observational Study %A Pecina,Jennifer L %A Nigon,Leah M %A Penza,Kristine S %A Murray,Martha A %A Kronebusch,Beckie J %A Miller,Nathaniel E %A Jensen,Teresa B %+ Department of Family Medicine, Mayo Clinic, 200 1st street SW, Rochester, MN, United States, 1 507 284 2511, pecina.jennifer@mayo.edu %K strep pharygitis %K e-visit %K electronic visit %K telemedicine %K telecare %K virtual visit %K McIssac score %K nurse phone triage %K scoring system %K sore throat %K group A streptococcus %K telehealth %K nurse %K phone %K triage %D 2021 %7 20.12.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: The McIsaac criteria are a validated scoring system used to determine the likelihood of an acute sore throat being caused by group A streptococcus (GAS) to stratify patients who need strep testing. Objective: We aim to compare McIsaac criteria obtained during face-to-face (f2f) and non-f2f encounters. Methods: This retrospective study compared the percentage of positive GAS tests by McIsaac score for scores calculated during nurse protocol phone encounters, e-visits (electronic visits), and in person f2f clinic visits. Results: There was no difference in percentages of positive strep tests between encounter types for any of the McIsaac scores. There were significantly more phone and e-visit encounters with any missing score components compared with f2f visits. For individual score components, there were significantly fewer e-visits missing fever and cough information compared with phone encounters and f2f encounters. F2f encounters were significantly less likely to be missing descriptions of tonsils and lymphadenopathy compared with phone and e-visit encounters. McIsaac scores of 4 had positive GAS rates of 55% to 68% across encounter types. There were 4 encounters not missing any score components with a McIsaac score of 0. None of these 4 encounters had a positive GAS test. Conclusions: McIsaac scores of 4 collected during non-f2f care could be used to consider empiric treatment for GAS without testing if significant barriers to testing exist such as the COVID-19 pandemic or geographic barriers. Future studies should evaluate further whether non-f2f encounters with McIsaac scores of 0 can be safely excluded from GAS testing. %M 34932016 %R 10.2196/25899 %U https://www.jmir.org/2021/12/e25899 %U https://doi.org/10.2196/25899 %U http://www.ncbi.nlm.nih.gov/pubmed/34932016 %0 Journal Article %@ 2562-0959 %I JMIR Publications %V 4 %N 2 %P e30620 %T The Contact Dermatitis Quality of Life Index (CDQL): Survey Development and Content Validity Assessment %A Hill,Mary K %A Laughter,Melissa R %A Harmange,Cecile I %A Dellavalle,Robert P %A Rundle,Chandler W %A Dunnick,Cory A %+ School of Medicine, University of Colorado, 1665 Aurora Court, MS 703, Aurora, CO, 80045, United States, 1 7208480500, cecile.harmange@cuanschutz.edu %K contact dermatitis %K allergic contact dermatitis %K irritant contact dermatitis %K quality of life %K outcomes instruments %K health outcomes %D 2021 %7 16.12.2021 %9 Original Paper %J JMIR Dermatol %G English %X Background: There is limited measurement and reporting of quality of life (QoL) outcomes for patients with contact dermatitis (CD). Objective: The purpose of this study is to develop a standardized Contact Dermatitis Quality of Life index (CDQL) for adult patients. Methods: A list of 81 topics was compiled from a review of QoL measures used previously in CD research. A total of 2 rounds of web-based Delphi surveys were sent to physicians who registered to attend the 2018 American Contact Dermatitis Society meeting, asking that they rank the relevance of topics for measuring QoL in CD using a 4-point scale. Items met consensus for inclusion if at least 78% of respondents ranked them as relevant or very relevant, and their median score was ≥3.25. Results: Of the 210 physicians contacted, 34 physicians completed the initial survey and 17 completed the follow-up survey. A total of 22 topics met consensus for inclusion in the CDQL, addressing symptoms, emotions, functions of daily living, social and physical functions, work/school functions, and treatment. Conclusions: This study was limited by the following factors: few open-ended questions in the initial survey, a lack of direct patient feedback, and long survey length, which likely contributed to lower survey participation. The CDQL is a comprehensive, CD-specific QoL measure developed on the basis of expert consensus via a modified Delphi process to be used by physicians and other health care professionals who care for adult patients with contact dermatitis. %M 37632827 %R 10.2196/30620 %U https://derma.jmir.org/2021/2/e30620 %U https://doi.org/10.2196/30620 %U http://www.ncbi.nlm.nih.gov/pubmed/37632827 %0 Journal Article %@ 2561-1011 %I JMIR Publications %V 5 %N 2 %P e26072 %T Real-World Experience of mHealth Implementation in Clinical Practice (the Box): Design and Usability Study %A Biersteker,Tom %A Hilt,Alexander %A van der Velde,Enno %A Schalij,Martin Jan %A Treskes,Roderick Willem %+ Department of Cardiology, Leiden University Medical Center, Albinusdreef 2, Leiden, 2333 ZA, Netherlands, 31 715262020, m.j.schalij@lumc.nl %K eHealth %K mHealth %K remote patient monitoring %K cardiology %K patient satisfaction %K patient empowerment %K mobile phone %D 2021 %7 16.12.2021 %9 Original Paper %J JMIR Cardio %G English %X Background: Mobile health (mHealth) is an emerging field of scientific interest worldwide. Potential benefits include increased patient engagement, improved clinical outcomes, and reduced health care costs. However, mHealth is often studied in projects or trials, and structural implantation in clinical practice is less common. Objective: The purpose of this paper is to outline the design of the Box and its implementation and use in an outpatient clinic setting. The impact on logistical outcomes and patient and provider satisfaction is discussed. Methods: In 2016, an mHealth care track including smartphone-compatible devices, named the Box, was implemented in the cardiology department of a tertiary medical center in the Netherlands. Patients with myocardial infarction, rhythm disorders, cardiac surgery, heart failure, and congenital heart disease received devices to measure daily weight, blood pressure, heart rate, temperature, and oxygen saturation. In addition, professional and patient user comments on the experience with the care track were obtained via structured interviews. Results: From 2016 to April 2020, a total of 1140 patients were connected to the mHealth care track. On average, a Box cost €350 (US $375), not including extra staff costs. The median patient age was 60.8 (IQR 52.9-69.3) years, and 73.59% (839/1140) were male. A median of 260 (IQR 105-641) measurements was taken on a median of 189 (IQR 98-372) days. Patients praised the ease of use of the devices and felt more involved with their illness and care. Professionals reported more productive outpatient consultations as well as improved insight into health parameters such as blood pressure and weight. A feedback loop from the hospital to patient to focus on measurements was commented as an important improvement by both patients and professionals. Conclusions: In this study, the design and implementation of an mHealth care track for outpatient follow-up of patients with various cardiovascular diseases is described. Data from these 4 years indicate that mHealth is feasible to incorporate in outpatient management and is generally well-accepted by patients and providers. Limitations include the need for manual measurement data checks and the risk of data overload. Moreover, the tertiary care setting in which the Box was introduced may limit the external validity of logistical and financial end points to other medical centers. More evidence is needed to show the effects of mHealth on clinical outcomes and on cost-effectiveness. %M 34642159 %R 10.2196/26072 %U https://cardio.jmir.org/2021/2/e26072 %U https://doi.org/10.2196/26072 %U http://www.ncbi.nlm.nih.gov/pubmed/34642159 %0 Journal Article %@ 2562-0959 %I JMIR Publications %V 4 %N 2 %P e31047 %T Exploring Access to Surgical Interventions for Hidradenitis Suppurativa: Retrospective Population-Based Analysis %A Finstad,Alexandra %A Lee,Alex %A George,Ralph %A Alhusayen,Raed %+ Division of Dermatology, Department of Medicine, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada, 1 416 480 6100 ext 7243, Raed.Alhusayen@sunnybrook.ca %K hidradenitis suppurativa %K surgery %K dermatology %K access %K epidemiology %K universal health care %D 2021 %7 14.12.2021 %9 Original Paper %J JMIR Dermatol %G English %X Background: Hidradenitis suppurativa (HS) is a painful inflammatory disorder that confers significant distress to patients, with surgery as an integral treatment modality. Objective: To inform improvements in care, patterns in HS surgery were assessed. Methods: A retrospective population-based analysis was performed on Ontario billing claims for HS surgery across a period of 10 years from January 1, 2008 to December 31, 2017. HS surgery was defined as the excision of inguinal, perineal, or axillary skin and sweat glands for hidradenitis. The top 5 billing specialties, including general and plastic surgery, were analyzed. The total number of procedures performed as well as the number performed per physician were investigated. Patient and physician locations were compared. Results: A total of 7195 claims for the excision of inguinal, perineal, or axillary skin and sweat glands for HS were submitted across the study period. Annual HS surgery claims showed an increasing trend across 10 years, ranging between 4.9 and 5.8 per 100,000 population. However, overall, for every additional year, the number of claims per 100,000 population only increased slightly, by 0.03 claims. The number of providers steadily decreased, ranging between 1.7 and 1.9 per 100,000, with approximately twice as many general than plastic surgeons. However, again overall, for every additional year, the number of providers per 100,000 population decreased slightly, by 0.002 physicians. The mean annual number of procedures per physician rose from 2.8 to 3.1. In rural areas, analyzed per claim, general surgeons performed the majority of surgeries (1318/2003, 65.8%), while in urban areas, surgeries were more equally performed by general (2616/5192, 50.4%) and plastic (2495/5192, 48.1%) surgeons. Of HS surgery claims, 25.7%-35.9% were provided by a physician residing in a different area than the patient receiving care. Conclusions: No significant improvements in access to HS surgery were seen across the study period, with access potentially worsening with annual HS claims rising overall and number of providers decreasing, with patients travelling further to access surgery. System barriers across the continuum of HS diagnosis and management must be evaluated to improve access to surgical care. %M 37632848 %R 10.2196/31047 %U https://derma.jmir.org/2021/2/e31047 %U https://doi.org/10.2196/31047 %U http://www.ncbi.nlm.nih.gov/pubmed/37632848 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 8 %N 4 %P e27171 %T Communicating Guideline Recommendations Using Graphic Narrative Versus Text-Based Broadcast Screensavers: Design and Implementation Study %A Sinnenberg,Lauren %A Umscheid,Craig A %A Shofer,Frances S %A Leri,Damien %A Meisel,Zachary F %+ Center for Emergency Care Policy and Research, University of Pennsylvania, Ravdin Ground, 3400 Spruce Street, Philadelphia, PA, 19104, United States, 1 215 746 5618, zfm@pennmedicine.upenn.edu %K medical informatics %K screensaver %K guideline dissemination %K graphic narratives %K health communication %K workstation %K clinical workstation %K guidelines %K medical education %K education %D 2021 %7 13.12.2021 %9 Original Paper %J JMIR Hum Factors %G English %X Background: The use of graphic narratives, defined as stories that use images for narration, is growing in health communication. Objective: The aim of this study was to describe the design and implementation of a graphic narrative screensaver (GNS) to communicate a guideline recommendation (ie, avoiding low-value acid suppressive therapy [AST] use in hospital inpatients) and examine the comparative effectiveness of the GNS versus a text-based screensaver (TBS) on clinical practice (ie, low-value AST prescriptions) and clinician recall. Methods: During a 2-year period, the GNS and the TBS were displayed on inpatient clinical workstations. The numbers of new AST prescriptions were examined in the four quarters before, the three quarters during, and the one quarter after screensavers were implemented. Additionally, an electronic survey was sent to resident physicians 1 year after the intervention to assess screensaver recall. Results: Designing an aesthetically engaging graphic that could be rapidly understood was critical in the development of the GNS. The odds of receiving an AST prescription on medicine and medicine subspecialty services after the screensavers were implemented were lower for all four quarters (ie, GNS and TBS broadcast together, only TBS broadcast, only GNS broadcast, and no AST screensavers broadcast) compared to the quarter prior to implementation (odds ratio [OR] 0.85, 95% CI 0.78-0.92; OR 0.89, 95% CI 0.82-0.97; OR 0.87, 95% CI 0.80-0.95; and OR 0.81, 95% CI 0.75-0.89, respectively; P<.001 for all comparisons). There were no statistically significant decreases for other high-volume services, such as the surgical services. These declines appear to have begun prior to screensaver implementation. When surveyed about the screensaver content 1 year later, resident physicians recalled both the GNS and TBS (43/70, 61%, vs 54/70, 77%; P=.07) and those who recalled the screensaver were more likely to recall the main message of the GNS compared to the TBS (30/43, 70%, vs 1/54, 2%; P<.001). Conclusions: It is feasible to use a graphic narrative embedded in a broadcast screensaver to communicate a guideline recommendation, but further study is needed to determine the impact of graphic narratives on clinical practice. %M 34264197 %R 10.2196/27171 %U https://humanfactors.jmir.org/2021/4/e27171 %U https://doi.org/10.2196/27171 %U http://www.ncbi.nlm.nih.gov/pubmed/34264197 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 12 %P e30238 %T The Communicating Narrative Concerns Entered by Registered Nurses (CONCERN) Clinical Decision Support Early Warning System: Protocol for a Cluster Randomized Pragmatic Clinical Trial %A Rossetti,Sarah Collins %A Dykes,Patricia C %A Knaplund,Christopher %A Kang,Min-Jeoung %A Schnock,Kumiko %A Garcia Jr,Jose Pedro %A Fu,Li-Heng %A Chang,Frank %A Thai,Tien %A Fred,Matthew %A Korach,Tom Z %A Zhou,Li %A Klann,Jeffrey G %A Albers,David %A Schwartz,Jessica %A Lowenthal,Graham %A Jia,Haomiao %A Liu,Fang %A Cato,Kenrick %+ Department of Biomedical Informatics, Columbia University, 622 W 168th Street PH20, New York, NY, 10032, United States, 1 781 801 9211, sac2125@cumc.columbia.edu %K nursing documentation %K prediction %K early warning system %K deterioration %K clinical trial %K clinical decision support system %K natural language processing %D 2021 %7 10.12.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Every year, hundreds of thousands of inpatients die from cardiac arrest and sepsis, which could be avoided if those patients’ risk for deterioration were detected and timely interventions were initiated. Thus, a system is needed to convert real-time, raw patient data into consumable information that clinicians can utilize to identify patients at risk of deterioration and thus prevent mortality and improve patient health outcomes. The overarching goal of the COmmunicating Narrative Concerns Entered by Registered Nurses (CONCERN) study is to implement and evaluate an early warning score system that provides clinical decision support (CDS) in electronic health record systems. With a combination of machine learning and natural language processing, the CONCERN CDS utilizes nursing documentation patterns as indicators of nurses’ increased surveillance to predict when patients are at the risk of clinical deterioration. Objective: The objective of this cluster randomized pragmatic clinical trial is to evaluate the effectiveness and usability of the CONCERN CDS system at 2 different study sites. The specific aim is to decrease hospitalized patients’ negative health outcomes (in-hospital mortality, length of stay, cardiac arrest, unanticipated intensive care unit transfers, and 30-day hospital readmission rates). Methods: A multiple time-series intervention consisting of 3 phases will be performed through a 1-year period during the cluster randomized pragmatic clinical trial. Phase 1 evaluates the adoption of our algorithm through pilot and trial testing, phase 2 activates optimized versions of the CONCERN CDS based on experience from phase 1, and phase 3 will be a silent release mode where no CDS is viewable to the end user. The intervention deals with a series of processes from system release to evaluation. The system release includes CONCERN CDS implementation and user training. Then, a mixed methods approach will be used with end users to assess the system and clinician perspectives. Results: Data collection and analysis are expected to conclude by August 2022. Based on our previous work on CONCERN, we expect the system to have a positive impact on the mortality rate and length of stay. Conclusions: The CONCERN CDS will increase team-based situational awareness and shared understanding of patients predicted to be at risk for clinical deterioration in need of intervention to prevent mortality and associated harm. Trial Registration: ClinicalTrials.gov NCT03911687; https://clinicaltrials.gov/ct2/show/NCT03911687 International Registered Report Identifier (IRRID): DERR1-10.2196/30238 %M 34889766 %R 10.2196/30238 %U https://www.researchprotocols.org/2021/12/e30238 %U https://doi.org/10.2196/30238 %U http://www.ncbi.nlm.nih.gov/pubmed/34889766 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 12 %P e27984 %T Exploring the Intersection Between Health Professionals’ Learning and eHealth Data: Protocol for a Comprehensive Research Program in Practice Analytics in Health Care %A Janssen,Anna %A Talic,Stella %A Gasevic,Dragan %A Kay,Judy %A Shaw,Tim %+ Faculty of Medicine and Health, The University of Sydney, Level 2, Charles Perkins Centre, Sydney, 2006, Australia, 61 9036 9406, anna.janssen@sydney.edu.au %K digital health %K health informatics %K practice analytics in health care %K health professions education %K continuing professional development %D 2021 %7 9.12.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: There is an increasing amount of electronic data sitting within the health system. These data have untapped potential to improve clinical practice if extracted efficiently and harnessed to change the behavior of health professionals. Furthermore, there is an increasing expectation from the government and peak bodies that both individual health professionals and health care organizations will use electronic data for a range of applications, including improving health service delivery and informing clinical practice and professional accreditation. Objective: The aim of this research program is to make eHealth data captured within tertiary health care organizations more actionable to health professionals for use in practice reflection, professional development, and other quality improvement activities. Methods: A multidisciplinary approach was used to connect academic experts from core disciplines of health and medicine, education and learning sciences, and engineering and information communication technology with government and health service partners to identify key problems preventing the health care industry from using electronic data to support health professional learning. This multidisciplinary approach was used to design a large-scale research program to solve the problem of making eHealth data more accessible to health professionals for practice reflection. The program will be delivered over 5 years by doctoral candidates undertaking research projects with discrete aims that run in parallel to achieving this program’s objectives. Results: The process used to develop the research program identified 7 doctoral research projects to answer the program objectives, split across 3 streams. Conclusions: This research program has the potential to successfully unpack electronic data siloed within clinical sites and enable health professionals to use them to reflect on their practice and deliver informed and improved care. The program will contribute to current practices by fostering stronger connections between industry and academia, interlinking doctoral research projects to solve complex problems, and creating new knowledge for clinical sites on how data can be used to understand and improve performance. Furthermore, the program aims to affect policy by developing insights on how professional development programs may be strengthened to enhance their alignment with clinical practice. The key contributions of this paper include the introduction of a new conceptualized research program, Practice Analytics in Health care, by describing the foundational academic disciplines that the program is formed of and presenting scientific methods for its design and development. International Registered Report Identifier (IRRID): PRR1-10.2196/27984 %M 34889768 %R 10.2196/27984 %U https://www.researchprotocols.org/2021/12/e27984 %U https://doi.org/10.2196/27984 %U http://www.ncbi.nlm.nih.gov/pubmed/34889768 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 12 %P e30092 %T Assessing Patient Engagement in Health Care: Proposal for a Modeling and Simulation Framework for Behavioral Analysis %A Alwasel,Athary %A Stergioulas,Lampros %A Fakhimi,Masoud %A Garn,Wolfgang %+ Surrey Business School, University of Surrey, Stag Hill, Guildford, GU2 7XH, United Kingdom, 44 1483 683048, a.alwasel@surrey.ac.uk %K modeling and simulation %K behavioral analysis %K patient engagement %K behavioral factors, health care %K human factors %K outcomes %K patient health %K health policy %K chronic diseases %K behavioral model %D 2021 %7 8.12.2021 %9 Proposal %J JMIR Res Protoc %G English %X Human behavior plays a vital role in health care effectiveness and system performance. Therefore, it is necessary to look carefully at the interactions within a system and how a system is affected by the behavioral responses and activities of its various components, particularly human components and actions. Modeling patients’ engagement behaviors can be valuable in many ways; for example, models can evaluate the effects of therapeutic interventions on health improvement, health care effectiveness, and desired outcomes of changing health lifestyles. Modeling and simulation (M&S) help us to understand the interactions within a whole system under defined conditions. M&S in patient behavior analysis involve models that attempt to identify certain human behaviors that most likely have an impact on health care operations and services. Our study’s overall aims are (1) to investigate the impacts of patients’ engagement and various human behavior patterns on health care effectiveness and the achievement of desired outcomes and (2) to construct and validate a framework for modeling patient engagement and implementing and supporting patient management best practices, health policy-making processes, and innovative interventions in health care. We intend to extract routinely collected data of different parameters from general patients diagnosed with chronic diseases, such as diabetes. Our plan is to design data sets and extract health data from a pool of >4 million patient records from different general practices in England. We will focus on the primary electronic medical records of patients with at least 1 chronic disease (>200,000 records). Simulation techniques will be used to study patient engagement and its impact on health care effectiveness and outcome measures. The study will integrate available approaches to develop a framework for modeling how patients’ behaviors affect health care activities and outcomes and to underline the characteristics and salient factors that operational management needs to be aware of when developing a behavioral model for assessing patient engagement. The M&S framework, which is under development, will consider patient behavior in context and the underlying factors of human behavior with the help of simulation techniques. The proposed framework will be validated and evaluated through a health care case study. We expect to identify leading factors that influence and affect patient engagement and associated behavioral activities and to illustrate the challenges and complexities of developing simulation models for conducting behavioral analyses within health care settings. Additionally, we will assess patients’ engagement behaviors in terms of achieving health care effectiveness and desired outcomes, and we will specifically evaluate the impacts of patient engagement activities on health care services, patient management styles, and the effectiveness of health interventions in terms of achieving the intended outcomes—improved health and patient satisfaction.International Registered Report Identifier (IRRID): PRR1-10.2196/30092 %M 34889774 %R 10.2196/30092 %U https://www.researchprotocols.org/2021/12/e30092 %U https://doi.org/10.2196/30092 %U http://www.ncbi.nlm.nih.gov/pubmed/34889774 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 9 %N 12 %P e27072 %T The Effect of Automated Mammogram Orders Paired With Electronic Invitations to Self-schedule on Mammogram Scheduling Outcomes: Observational Cohort Comparison %A North,Frederick %A Nelson,Elissa M %A Buss,Rebecca J %A Majerus,Rebecca J %A Thompson,Matthew C %A Crum,Brian A %+ Division of Community Internal Medicine, Department of Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, United States, 1 507 284 2511, north.frederick@mayo.edu %K electronic health record %K schedule %K patient appointment %K preventive health service %K office visit %K outpatient care %K mammogram %K software tool %K computer software application %K mobile applications %K self-schedule %K app %K EHR %K screening %K diagnostic %K cancer %D 2021 %7 7.12.2021 %9 Original Paper %J JMIR Med Inform %G English %X Background: Screening mammography is recommended for the early detection of breast cancer. The processes for ordering screening mammography often rely on a health care provider order and a scheduler to arrange the time and location of breast imaging. Self-scheduling after automated ordering of screening mammograms may offer a more efficient and convenient way to schedule screening mammograms. Objective: The aim of this study was to determine the use, outcomes, and efficiency of an automated mammogram ordering and invitation process paired with self-scheduling. Methods: We examined appointment data from 12 months of scheduled mammogram appointments, starting in September 2019 when a web and mobile app self-scheduling process for screening mammograms was made available for the Mayo Clinic primary care practice. Patients registered to the Mayo Clinic Patient Online Services could view the schedules and book their mammogram appointment via the web or a mobile app. Self-scheduling required no telephone calls or staff appointment schedulers. We examined uptake (count and percentage of patients utilizing self-scheduling), number of appointment actions taken by self-schedulers and by those using staff schedulers, no-show outcomes, scheduling efficiency, and weekend and after-hours use of self-scheduling. Results: For patients who were registered to patient online services and had screening mammogram appointment activity, 15.3% (14,387/93,901) used the web or mobile app to do either some mammogram self-scheduling or self-cancelling appointment actions. Approximately 24.4% (3285/13,454) of self-scheduling occurred after normal business hours/on weekends. Approximately 9.3% (8736/93,901) of the patients used self-scheduling/cancelling exclusively. For self-scheduled mammograms, there were 5.7% (536/9433) no-shows compared to 4.6% (3590/77,531) no-shows in staff-scheduled mammograms (unadjusted odds ratio 1.24, 95% CI 1.13-1.36; P<.001). The odds ratio of no-shows for self-scheduled mammograms to staff-scheduled mammograms decreased to 1.12 (95% CI 1.02-1.23; P=.02) when adjusted for age, race, and ethnicity. On average, since there were only 0.197 staff-scheduler actions for each finalized self-scheduled appointment, staff schedulers were rarely used to redo or “clean up” self-scheduled appointments. Exclusively self-scheduled appointments were significantly more efficient than staff-scheduled appointments. Self-schedulers experienced a single appointment step process (one and done) for 93.5% (7553/8079) of their finalized appointments; only 74.5% (52,804/70,839) of staff-scheduled finalized appointments had a similar one-step appointment process (P<.001). For staff-scheduled appointments, 25.5% (18,035/70,839) of the finalized appointments took multiple appointment steps. For finalized appointments that were exclusively self-scheduled, only 6.5% (526/8079) took multiple appointment steps. The staff-scheduled to self-scheduled odds ratio of taking multiple steps for a finalized screening mammogram appointment was 4.9 (95% CI 4.48-5.37; P<.001). Conclusions: Screening mammograms can be efficiently self-scheduled but may be associated with a slight increase in no-shows. Self-scheduling can decrease staff scheduler work and can be convenient for patients who want to manage their appointment scheduling activity after business hours or on weekends. %M 34878997 %R 10.2196/27072 %U https://medinform.jmir.org/2021/12/e27072 %U https://doi.org/10.2196/27072 %U http://www.ncbi.nlm.nih.gov/pubmed/34878997 %0 Journal Article %@ 2561-9128 %I JMIR Publications %V 4 %N 2 %P e27037 %T Mobile Health Apps That Act as Surgical Preparatory Guides: App Store Search and Quality Evaluation %A Gadde,Naga Sindhura %A Yap,Kevin Yi-Lwern %+ Department of Pharmacy, Singapore General Hospital, SingHealth Tower, 10 Hospital Boulevard, Lobby A, Level 9, Singapore, 168582, Singapore, 65 63214366, kevin.yap.y.l@sgh.com.sg %K mHealth apps %K surgical apps %K surgery preparation %K operating room personnel %K quality assessment %K quality evaluation %K perioperative %K operative %K mobile health %K surgery %K post-operative %D 2021 %7 30.11.2021 %9 Original Paper %J JMIR Perioper Med %G English %X Background: Mobile health (mHealth) apps are becoming increasingly common in surgical practices for training, education, and communication. Factors leading to increased delays, morbidity, and mortality in surgery include inadequate preoperative patient preparation due to a failure to identify patients and procedure details, and missing instruments and equipment required for the procedure. Many apps are available for supporting preoperative, intraoperative, and postoperative care. However, there is a lack of studies that assess the quality of apps that act as surgical preparatory guides. Objective: The aim of this study is to evaluate the quality of apps that act as surgical preparatory guides for operating room personnel through an in-house quality assessment tool. Methods: The quality assessment tool comprises 35 questions categorized into 5 sections: (1) engagement (customization, interactivity, target audience; 19 points), (2) functionality (performance, ease of use, navigation; 12 points), (3) aesthetics (layout, visual appeal; 6 points), (4) information (quality and quantity of information, visual information, credibility; 29 points), and (5) privacy and security (4 points). An app search was conducted in the Australian Apple and Google Play stores using the following keywords: “surgical apps”, “surgical preferences”, “surgeon preferences”, “operating room”, and “perioperative procedures”. The overall total scores and scores for each section were reported as medians and IQRs, expressed as raw scores and percentages. Results: A total of 5 unique apps were evaluated on both iOS and Android platforms. The median overall score across all apps was 35/70 (50%; IQR 38.6%-64.3%). ScrubUp (48/70, 69%) and MySurgeon (42/70, 60%) had the highest overall scores, followed by PrefCard (35/70, 50%) and Scrubnote (28/70, 40%). The lowest scoring app was BrainPadd (26/70, 37%). The sections with the highest median scores, in decreasing order, were privacy and security (4/4, 100%; IQR 75%-100%), aesthetics (5/6, 83%; IQR 75%-91.7%), engagement (15/19, 79%; IQR 57.9%-86.8%), functionality (7/12, 58%; IQR 29.2%-75%), and information (5/29, 17%; IQR 15.5%-34.5%). Most apps scored well (4/4, 100%) on privacy and security, except for Scrubnote (2/4, 50%). ScrubUp received a perfect score for aesthetics (6/6, 100%). MySurgeon (17/19, 90%) had the highest engagement score, while ScrubUp and MySurgeon had the highest functionality scores (9/12, 75% each). All apps scored below 50% for the information section, with ScrubUp having the highest score of 13/29 (45%). Conclusions: ScrubUp and MySurgeon had the highest quality scores and can be used as adjuncts to hospital protocols by operating room personnel for their surgical preparation. Developers are encouraged to develop appropriate apps for surgical preparation based on relevant guidelines and standards, as well as the quality evaluation criteria in our tool. Operating room personnel can also use this tool as a guide to select and assess their preferred apps in their practices. %M 34851296 %R 10.2196/27037 %U https://periop.jmir.org/2021/2/e27037 %U https://doi.org/10.2196/27037 %U http://www.ncbi.nlm.nih.gov/pubmed/34851296 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 9 %N 11 %P e32507 %T Assessing the Performance of a New Artificial Intelligence–Driven Diagnostic Support Tool Using Medical Board Exam Simulations: Clinical Vignette Study %A Ben-Shabat,Niv %A Sloma,Ariel %A Weizman,Tomer %A Kiderman,David %A Amital,Howard %+ Department of Medicine ‘B’, Sheba Medical Center, Sheba Road 2, Ramat Gan, 52621, Israel, 972 3 530 2652, nivben7@gmail.com %K diagnostic decision support systems %K diagnostic support %K medical decision-making %K medical informatics %K artificial intelligence %K Kahun %K decision support %D 2021 %7 30.11.2021 %9 Original Paper %J JMIR Med Inform %G English %X Background: Diagnostic decision support systems (DDSS) are computer programs aimed to improve health care by supporting clinicians in the process of diagnostic decision-making. Previous studies on DDSS demonstrated their ability to enhance clinicians’ diagnostic skills, prevent diagnostic errors, and reduce hospitalization costs. Despite the potential benefits, their utilization in clinical practice is limited, emphasizing the need for new and improved products. Objective: The aim of this study was to conduct a preliminary analysis of the diagnostic performance of “Kahun,” a new artificial intelligence-driven diagnostic tool. Methods: Diagnostic performance was evaluated based on the program’s ability to “solve” clinical cases from the United States Medical Licensing Examination Step 2 Clinical Skills board exam simulations that were drawn from the case banks of 3 leading preparation companies. Each case included 3 expected differential diagnoses. The cases were entered into the Kahun platform by 3 blinded junior physicians. For each case, the presence and the rank of the correct diagnoses within the generated differential diagnoses list were recorded. Each diagnostic performance was measured in two ways: first, as diagnostic sensitivity, and second, as case-specific success rates that represent diagnostic comprehensiveness. Results: The study included 91 clinical cases with 78 different chief complaints and a mean number of 38 (SD 8) findings for each case. The total number of expected diagnoses was 272, of which 174 were different (some appeared more than once). Of the 272 expected diagnoses, 231 (87.5%; 95% CI 76-99) diagnoses were suggested within the top 20 listed diagnoses, 209 (76.8%; 95% CI 66-87) were suggested within the top 10, and 168 (61.8%; 95% CI 52-71) within the top 5. The median rank of correct diagnoses was 3 (IQR 2-6). Of the 91 expected diagnoses, 62 (68%; 95% CI 59-78) of the cases were suggested within the top 20 listed diagnoses, 44 (48%; 95% CI 38-59) within the top 10, and 24 (26%; 95% CI 17-35) within the top 5. Of the 91 expected diagnoses, in 87 (96%; 95% CI 91-100), at least 2 out of 3 of the cases’ expected diagnoses were suggested within the top 20 listed diagnoses; 78 (86%; 95% CI 79-93) were suggested within the top 10; and 61 (67%; 95% CI 57-77) within the top 5. Conclusions: The diagnostic support tool evaluated in this study demonstrated good diagnostic accuracy and comprehensiveness; it also had the ability to manage a wide range of clinical findings. %M 34672262 %R 10.2196/32507 %U https://medinform.jmir.org/2021/11/e32507 %U https://doi.org/10.2196/32507 %U http://www.ncbi.nlm.nih.gov/pubmed/34672262 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 9 %N 11 %P e32180 %T Health Professionals’ Perspectives on Electronic Medical Record Infusion and Individual Performance: Model Development and Questionnaire Survey Study %A Chen,Rai-Fu %A Hsiao,Ju-Ling %+ Department of Pharmacy, Chia-Nan University of Pharmacy and Science, Number 60, Sec 1, Erren Road, Rende District, Tainan City, 71710, Taiwan, 886 6 2664911 ext 5106, mayo5012@gmail.com %K health care professional %K electronic medical records %K IS infusion %K individual performance %K EHR %K electronic health record %K performance %K perspective %K information system %K integration %K decision-making %K health information exchange %K questionnaire %D 2021 %7 30.11.2021 %9 Original Paper %J JMIR Med Inform %G English %X Background: Electronic medical records (EMRs) are integrated information sources generated by health care professionals (HCPs) from various health care information systems. EMRs play crucial roles in improving the quality of care and medical decision-making and in facilitating cross-hospital health information exchange. Although many hospitals have invested considerable resources and efforts to develop EMRs for several years, the factors affecting the long-term success of EMRs, particularly in the EMR infusion stage, remain unclear. Objective: The aim of this study was to investigate the effects of technology, user, and task characteristics on EMR infusion to determine the factors that largely affect EMR infusion. In addition, we examined the effect of EMR infusion on individual HCP performance. Methods: A questionnaire survey was used to collect data from HCPs with >6 months experience in using EMRs in a Taiwanese teaching hospital. A total of 316 questionnaires were distributed and 211 complete copies were returned, yielding a valid response rate of 66.8%. The collected data were further analyzed using WarpPLS 5.0. Results: EMR infusion (R2=0.771) was mainly affected by user habits (β=.411), portability (β=.217), personal innovativeness (β=.198), technostress (β=.169), and time criticality (β=.168), and individual performance (R2=0.541) was affected by EMR infusion (β=.735). This finding indicated that user (habit, personal innovativeness, and technostress), technology (portability), and task (mobility and time criticality) characteristics have major effects on EMR infusion. Furthermore, the results indicated that EMR infusion positively affects individual performance. Conclusions: The factors identified in this study can extend information systems infusion theory and provide useful insights for the further improvement of EMR development in hospitals and by the government, specifically in its infusion stage. In addition, the developed instrument can be used as an assessment tool to identify the key factors for EMR infusion, and to evaluate the extent of EMR infusion and the individual performance of hospitals that have implemented EMR systems. Moreover, the results can help governments to understand the urgent needs of hospitals in implementing EMR systems, provide sufficient resources and support to improve the incentives of EMR development, and develop adequate EMR policies for the meaningful use of electronic health records among hospitals and clinics. %M 34851297 %R 10.2196/32180 %U https://medinform.jmir.org/2021/11/e32180 %U https://doi.org/10.2196/32180 %U http://www.ncbi.nlm.nih.gov/pubmed/34851297 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 8 %N 4 %P e31214 %T Stakeholder Perspectives on an Inpatient Hypoglycemia Informatics Alert: Mixed Methods Study %A Mathioudakis,Nestoras %A Aboabdo,Moeen %A Abusamaan,Mohammed S %A Yuan,Christina %A Lewis Boyer,LaPricia %A Pilla,Scott J %A Johnson,Erica %A Desai,Sanjay %A Knight,Amy %A Greene,Peter %A Golden,Sherita H %+ Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, Johns Hopkins University, 1830 E. Monument Street, Suite 333, Baltimore, MD, 21287, United States, 1 410 502 8089, nmathio1@jhmi.edu %K informatics alert %K clinical decision support %K hypoglycemia %K hospital %K inpatient %D 2021 %7 26.11.2021 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Iatrogenic hypoglycemia is a common occurrence among hospitalized patients and is associated with poor clinical outcomes and increased mortality. Clinical decision support systems can be used to reduce the incidence of this potentially avoidable adverse event. Objective: This study aims to determine the desired features and functionality of a real-time informatics alert to prevent iatrogenic hypoglycemia in a hospital setting. Methods: Using the Agency for Healthcare Research and Quality Five Rights of Effective Clinical Decision Support Framework, we conducted a mixed methods study using an electronic survey and focus group sessions of hospital-based providers. The goal was to elicit stakeholder input to inform the future development of a real-time informatics alert to target iatrogenic hypoglycemia. In addition to perceptions about the importance of the problem and existing barriers, we sought input regarding the content, format, channel, timing, and recipient for the alert (ie, the Five Rights). Thematic analysis of focus group sessions was conducted using deductive and inductive approaches. Results: A 21-item electronic survey was completed by 102 inpatient-based providers, followed by 2 focus group sessions (6 providers per session). Respondents universally agreed or strongly agreed that inpatient iatrogenic hypoglycemia is an important problem that can be addressed with an informatics alert. Stakeholders expressed a preference for an alert that is nonintrusive, accurate, communicated in near real time to the ordering provider, and provides actionable treatment recommendations. Several electronic medical record tools, including alert indicators in the patient header, glucose management report, and laboratory results section, were deemed acceptable formats for consideration. Concerns regarding alert fatigue were prevalent among both survey respondents and focus group participants. Conclusions: The design preferences identified in this study will provide the framework needed for an informatics team to develop a prototype alert for pilot testing and evaluation. This alert will help meet the needs of hospital-based clinicians caring for patients with diabetes who are at a high risk of treatment-related hypoglycemia. %M 34842544 %R 10.2196/31214 %U https://humanfactors.jmir.org/2021/4/e31214 %U https://doi.org/10.2196/31214 %U http://www.ncbi.nlm.nih.gov/pubmed/34842544 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 9 %N 11 %P e26456 %T Clinical Impact of an Analytic Tool for Predicting the Fall Risk in Inpatients: Controlled Interrupted Time Series %A Cho,Insook %A Jin,In sun %A Park,Hyunchul %A Dykes,Patricia C %+ Nursing Department, College of Medicine, Inha University, 100 Inha-ro, namu-gu, Incheon, 22212, Republic of Korea, 82 01042323943, insook.cho@inha.ac.kr %K clinical effectiveness %K data analytics %K event prediction %K inpatient falls %K process metrics %D 2021 %7 25.11.2021 %9 Original Paper %J JMIR Med Inform %G English %X Background: Patient falls are a common cause of harm in acute-care hospitals worldwide. They are a difficult, complex, and common problem requiring a great deal of nurses’ time, attention, and effort in practice. The recent rapid expansion of health care predictive analytic applications and the growing availability of electronic health record (EHR) data have resulted in the development of machine learning models that predict adverse events. However, the clinical impact of these models in terms of patient outcomes and clinicians’ responses is undetermined. Objective: The purpose of this study was to determine the impact of an electronic analytic tool for predicting fall risk on patient outcomes and nurses’ responses. Methods: A controlled interrupted time series (ITS) experiment was conducted in 12 medical-surgical nursing units at a public hospital between May 2017 and April 2019. In six of the units, the patients’ fall risk was assessed using the St. Thomas’ Risk Assessment Tool in Falling Elderly Inpatients (STRATIFY) system (control units), while in the other six, a predictive model for inpatient fall risks was implemented using routinely obtained data from the hospital’s EHR system (intervention units). The primary outcome was the rate of patient falls; secondary outcomes included the rate of falls with injury and analysis of process metrics (nursing interventions that are designed to mitigate the risk of fall). Results: During the study period, there were 42,476 admissions, of which 707 were for falls and 134 for fall injuries. Allowing for differences in the patients’ characteristics and baseline process metrics, the number of patients with falls differed between the control (n=382) and intervention (n=325) units. The mean fall rate increased from 1.95 to 2.11 in control units and decreased from 1.92 to 1.79 in intervention units. A separate ITS analysis revealed that the immediate reduction was 29.73% in the intervention group (z=–2.06, P=.039) and 16.58% in the control group (z=–1.28, P=.20), but there was no ongoing effect. The injury rate did not differ significantly between the two groups (0.42 vs 0.31, z=1.50, P=.134). Among the process metrics, the risk-targeted interventions increased significantly over time in the intervention group. Conclusions: This early-stage clinical evaluation revealed that implementation of an analytic tool for predicting fall risk may to contribute to an awareness of fall risk, leading to positive changes in nurses’ interventions over time. Trial Registration: Clinical Research Information Service (CRIS), Republic of Korea KCT0005286; https://cris.nih.go.kr/cris/search/detailSearch.do/16984 %M 34626168 %R 10.2196/26456 %U https://medinform.jmir.org/2021/11/e26456 %U https://doi.org/10.2196/26456 %U http://www.ncbi.nlm.nih.gov/pubmed/34626168 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 8 %N 4 %P e22325 %T Including the Reason for Use on Prescriptions Sent to Pharmacists: Scoping Review %A Mercer,Kathryn %A Carter,Caitlin %A Burns,Catherine %A Tennant,Ryan %A Guirguis,Lisa %A Grindrod,Kelly %+ Library, University of Waterloo, 200 University Avenue West, DC 1555, Waterloo, ON, N2L 3G1, Canada, 1 519 888 4567 ext 42659, kmercer@uwaterloo.ca %K patient safety %K human factors %K patient engagement %K multidisciplinary %D 2021 %7 25.11.2021 %9 Review %J JMIR Hum Factors %G English %X Background: In North America, although pharmacists are obligated to ensure prescribed medications are appropriate, information about a patient’s reason for use is not a required component of a legal prescription. The benefits of prescribers including the reason for use on prescriptions is evident in the current literature. However, it is not standard practice to share this information with pharmacists. Objective: Our aim was to characterize the research on how including the reason for use on a prescription impacts pharmacists. Methods: We performed an interdisciplinary scoping review, searching literature in the fields of health care, informatics, and engineering. The following databases were searched between December 2018 and January 2019: PubMed, Institute of Electrical and Electronics Engineers (IEEE), Association for Computing Machinery (ACM), International Pharmaceutical Abstracts (IPA), and EMBASE. Results: A total of 3912 potentially relevant articles were identified, with 9 papers meeting the inclusion criteria. The studies used different terminology (eg, indication, reason for use) and a wide variety of study methodologies, including prospective and retrospective observational studies, randomized controlled trials, and qualitative interviews and focus groups. The results suggest that including the reason for use on a prescription can help the pharmacist catch more errors, reduce the need to contact prescribers, support patient counseling, impact communication, and improve patient safety. Reasons that may prevent prescribers from adding the reason for use information are concerns about workflow and patient privacy. Conclusions: More research is needed to understand how the reason for use information should be provided to pharmacists. In the limited literature to date, there is a consensus that the addition of this information to prescriptions benefits patient safety and enables pharmacists to be more effective. Future research should use an implementation science or theory-based approach to improve prescriber buy-in and, consequently, adoption. %M 34842545 %R 10.2196/22325 %U https://humanfactors.jmir.org/2021/4/e22325 %U https://doi.org/10.2196/22325 %U http://www.ncbi.nlm.nih.gov/pubmed/34842545 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 11 %P e28620 %T A Phenotyping Algorithm to Identify People With HIV in Electronic Health Record Data (HIV-Phen): Development and Evaluation Study %A May,Sarah B %A Giordano,Thomas P %A Gottlieb,Assaf %+ School of Biomedical Informatics, University of Texas Health Science Center at Houston, 7000 Fannin, Suite 600, Houston, TX, 77030, United States, 1 713 500 3698, Assaf.Gottlieb@uth.tmc.edu %K phenotyping %K algorithms %K electronic health records %K people with HIV %K cohort identification %D 2021 %7 25.11.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Identification of people with HIV from electronic health record (EHR) data is an essential first step in the study of important HIV outcomes, such as risk assessment. This task has been historically performed via manual chart review, but the increased availability of large clinical data sets has led to the emergence of phenotyping algorithms to automate this process. Existing algorithms for identifying people with HIV rely on a combination of International Classification of Disease codes and laboratory tests or closely mimic clinical testing guidelines for HIV diagnosis. However, we found that existing algorithms in the literature missed a significant proportion of people with HIV in our data. Objective: The aim of this study is to develop and evaluate HIV-Phen, an updated criteria-based HIV phenotyping algorithm. Methods: We developed an algorithm using HIV-specific laboratory tests and medications and compared it with previously published algorithms in national and local data sets to identify cohorts of people with HIV. Cohort demographics were compared with those reported in the national and local surveillance data. Chart reviews were performed on a subsample of patients from the local database to calculate the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the algorithm. Results: Our new algorithm identified substantially more people with HIV in both national (up to an 85.75% increase) and local (up to an 83.20% increase) EHR databases than the previously published algorithms. The demographic characteristics of people with HIV identified using our algorithm were similar to those reported in national and local HIV surveillance data. Our algorithm demonstrated improved sensitivity over existing algorithms (98% vs 56%-92%) while maintaining a similar overall accuracy (96% vs 80%-96%). Conclusions: We developed and evaluated an updated criteria-based phenotyping algorithm for identifying people with HIV in EHR data that demonstrates improved sensitivity over existing algorithms. %M 34842532 %R 10.2196/28620 %U https://formative.jmir.org/2021/11/e28620 %U https://doi.org/10.2196/28620 %U http://www.ncbi.nlm.nih.gov/pubmed/34842532 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 11 %P e28196 %T Quality of Primary Care for the Adult Population With Autism Spectrum Disorder: Protocol for a Scoping Review %A Aylward,Shannon Marion %A Farrell,Alison %A Walsh,Anna %A Godwin,Marshall %A Chafe,Roger %A Asghari,Shabnam %+ Discipline of Family Medicine, Faculty of Medicine, Memorial University, Medical Education Centre, Room M5M107, 300 Prince Philip Drive, St. John's, NL, A1B 3V6, Canada, 1 7097772142, shabnam.asghari@med.mun.ca %K autism spectrum disorder %K primary care %K family physician %K quality %K scoping review %K protocol %D 2021 %7 19.11.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: A strong primary care system is vital to overall health. Research on the primary care of people with autism spectrum disorder (ASD) has mostly focused on children. A synthesis of the existing literature related to the quality of primary care for the adult population with ASD would elucidate what is known about the topic as well as inform future research and clinical practice. Objective: The purpose of our scoping review is to describe what is known about the quality of primary care for adults with ASD and identify knowledge gaps. Methods: Prior to beginning the literature search, we reviewed literature related to defining both primary care and primary care quality to establish the context and concept of the research question. The search strategy was designed and executed by a research librarian. The MEDLINE, CINAHL, EMBASE, PsycINFO, and ProQuest Dissertations and Theses databases were searched for relevant literature. Grey literature will include relevant reports from government websites and associations with a focus on ASD. Two members of the research team will independently screen the academic and grey literature. Quantitative, qualitative, or mixed methods study designs involving the quality of primary care services or patient-centered care for adults with ASD are eligible for inclusion in our scoping review. Studies that make it past the full-text review will undergo data extraction and quality appraisal by 2 independent reviewers. The data extraction results will be presented in a tabular format to clearly present what is known about the quality of primary care for adults with ASD; this table will be accompanied by a narrative synthesis. Literature selected for extraction will be coded for themes, which will form the basis of a thematic synthesis. The scoping review will follow the guidance proposed by the Joanna Briggs Institute. Results: The search of electronic databases was conducted in October 2020, and it returned 2820 results. This research is still in progress. The results from our scoping review are expected to be available by fall 2021. Conclusions: The results from our scoping review will be useful for guiding future research on the quality of primary care for adults with ASD. International Registered Report Identifier (IRRID): PRR1-10.2196/28196 %M 34806989 %R 10.2196/28196 %U https://www.researchprotocols.org/2021/11/e28196 %U https://doi.org/10.2196/28196 %U http://www.ncbi.nlm.nih.gov/pubmed/34806989 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 11 %P e30042 %T Use of Patient-Reported Outcome Measures and Patient-Reported Experience Measures Within Evaluation Studies of Telemedicine Applications: Systematic Review %A Knapp,Andreas %A Harst,Lorenz %A Hager,Stefan %A Schmitt,Jochen %A Scheibe,Madlen %+ Center for Evidence-Based Healthcare, University Hospital Carl Gustav Carus, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, Fetscherstrasse 74, Dresden, 01307, Germany, 49 3514585665, andreas.knapp@uniklinikum-dresden.de %K telemedicine %K telehealth %K evaluation %K outcome %K patient-reported outcome measures %K patient-reported outcome %K patient-reported experience measures %K patient-reported experience %K measurement instrument %K questionnaire %D 2021 %7 17.11.2021 %9 Review %J J Med Internet Res %G English %X Background: With the rise of digital health technologies and telemedicine, the need for evidence-based evaluation is growing. Patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs) are recommended as an essential part of the evaluation of telemedicine. For the first time, a systematic review has been conducted to investigate the use of PROMs and PREMs in the evaluation studies of telemedicine covering all application types and medical purposes. Objective: This study investigates the following research questions: in which scenarios are PROMs and PREMs collected for evaluation purposes, which PROM and PREM outcome domains have been covered and how often, which outcome measurement instruments have been used and how often, does the selection and quantity of PROMs and PREMs differ between study types and application types, and has the use of PROMs and PREMs changed over time. Methods: We conducted a systematic literature search of the MEDLINE and Embase databases and included studies published from inception until April 2, 2020. We included studies evaluating telemedicine with patients as the main users; these studies reported PROMs and PREMs within randomized controlled trials, controlled trials, noncontrolled trials, and feasibility trials in English and German. Results: Of the identified 2671 studies, 303 (11.34%) were included; of the 303 studies, 67 (22.1%) were feasibility studies, 70 (23.1%) were noncontrolled trials, 20 (6.6%) were controlled trials, and 146 (48.2%) were randomized controlled trials. Health-related quality of life (n=310; mean 1.02, SD 1.05), emotional function (n=244; mean 0.81, SD 1.18), and adherence (n=103; mean 0.34, SD 0.53) were the most frequently assessed outcome domains. Self-developed PROMs were used in 21.4% (65/303) of the studies, and self-developed PREMs were used in 22.3% (68/303). PROMs (n=884) were assessed more frequently than PREMs (n=234). As the evidence level of the studies increased, the number of PROMs also increased (τ=−0.45), and the number of PREMs decreased (τ=0.35). Since 2000, not only has the number of studies using PROMs and PREMs increased, but the level of evidence and the number of outcome measurement instruments used have also increased, with the number of PREMs permanently remaining at a lower level. Conclusions: There have been increasingly more studies, particularly high-evidence studies, which use PROMs and PREMs to evaluate telemedicine. PROMs have been used more frequently than PREMs. With the increasing maturity stage of telemedicine applications and higher evidence level, the use of PROMs increased in line with the recommendations of evaluation guidelines. Health-related quality of life and emotional function were measured in almost all the studies. Simultaneously, health literacy as a precondition for using the application adequately, alongside proper training and guidance, has rarely been reported. Further efforts should be pursued to standardize PROM and PREM collection in evaluation studies of telemedicine. %M 34523604 %R 10.2196/30042 %U https://www.jmir.org/2021/11/e30042 %U https://doi.org/10.2196/30042 %U http://www.ncbi.nlm.nih.gov/pubmed/34523604 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 9 %N 11 %P e30432 %T The Role of Electronic Medical Records in Reducing Unwarranted Clinical Variation in Acute Health Care: Systematic Review %A Hodgson,Tobias %A Burton-Jones,Andrew %A Donovan,Raelene %A Sullivan,Clair %+ The University of Queensland Business School, The University of Queensland, 39 Blair Drive, St Lucia, 4067, Australia, 61 733468100, t.hodgson@business.uq.edu.au %K clinical variation %K unwarranted clinical variation %K electronic health record %K EHR %K electronic medical record %K EMR %K PowerPlan %K SmartSet %K acute care %K eHealth %K digital health %K health care %K health care outcomes %K outcome %K review %K standard of care %K hospital %K research %K literature %K variation %K intervention %D 2021 %7 17.11.2021 %9 Review %J JMIR Med Inform %G English %X Background: The use of electronic medical records (EMRs)/electronic health records (EHRs) provides potential to reduce unwarranted clinical variation and thereby improve patient health care outcomes. Minimization of unwarranted clinical variation may raise and refine the standard of patient care provided and satisfy the quadruple aim of health care. Objective: A systematic review of the impact of EMRs and specific subcomponents (PowerPlans/SmartSets) on variation in clinical care processes in hospital settings was undertaken to summarize the existing literature on the effects of EMRs on clinical variation and patient outcomes. Methods: Articles from January 2000 to November 2020 were identified through a comprehensive search that examined EMRs/EHRs and clinical variation or PowerPlans/SmartSets. Thirty-six articles met the inclusion criteria. Articles were examined for evidence for EMR-induced changes in variation and effects on health care outcomes and mapped to the quadruple aim of health care. Results: Most of the studies reported positive effects of EMR-related interventions (30/36, 83%). All of the 36 included studies discussed clinical variation, but only half measured it (18/36, 50%). Those studies that measured variation generally examined how changes to variation affected individual patient care (11/36, 31%) or costs (9/36, 25%), while other outcomes (population health and clinician experience) were seldom studied. High-quality study designs were rare. Conclusions: The literature provides some evidence that EMRs can help reduce unwarranted clinical variation and thereby improve health care outcomes. However, the evidence is surprisingly thin because of insufficient attention to the measurement of clinical variation, and to the chain of evidence from EMRs to variation in clinical practices to health care outcomes. %M 34787585 %R 10.2196/30432 %U https://medinform.jmir.org/2021/11/e30432 %U https://doi.org/10.2196/30432 %U http://www.ncbi.nlm.nih.gov/pubmed/34787585 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 9 %N 11 %P e31186 %T The Relationship Between Electronic Health Record System and Performance on Quality Measures in the American College of Rheumatology’s Rheumatology Informatics System for Effectiveness (RISE) Registry: Observational Study %A Hammam,Nevin %A Izadi,Zara %A Li,Jing %A Evans,Michael %A Kay,Julia %A Shiboski,Stephen %A Schmajuk,Gabriela %A Yazdany,Jinoos %+ Division of Rheumatology, Department of Medicine, University of California, P O Box 0811, Floor 03, Room 3301, San Francisco, CA, 94110, United States, 1 628 206 8618, jinoos.yazdany@ucsf.edu %K rheumatoid arthritis %K electronic health record %K patient-reported outcomes %K quality measures %K electronic health record %K disease activity %K quality of care %K performance reporting %K medical informatics %K clinical informatics %D 2021 %7 12.11.2021 %9 Original Paper %J JMIR Med Inform %G English %X Background: Routine collection of disease activity (DA) and patient-reported outcomes (PROs) in rheumatoid arthritis (RA) are nationally endorsed quality measures and critical components of a treat-to-target approach. However, little is known about the role electronic health record (EHR) systems play in facilitating performance on these measures. Objective: Using the American College Rheumatology’s (ACR’s) RISE registry, we analyzed the relationship between EHR system and performance on DA and functional status (FS) quality measures. Methods: We analyzed data collected in 2018 from practices enrolled in RISE. We assessed practice-level performance on quality measures that require DA and FS documentation. Multivariable linear regression and zero-inflated negative binomial models were used to examine the independent effect of EHR system on practice-level quality measure performance, adjusting for practice characteristics and patient case-mix. Results: In total, 220 included practices cared for 314,793 patients with RA. NextGen was the most commonly used EHR system (34.1%). We found wide variation in performance on DA and FS quality measures by EHR system (median 30.1, IQR 0-74.8, and median 9.0, IQR 0-74.2), respectively). Even after adjustment, NextGen practices performed significantly better than Allscripts on the DA measure (51.4% vs 5.0%; P<.05) and significantly better than eClinicalWorks and eMDs on the FS measure (49.3% vs 29.0% and 10.9%; P<.05). Conclusions: Performance on national RA quality measures was associated with the EHR system, even after adjusting for practice and patient characteristics. These findings suggest that future efforts to improve quality of care in RA should focus not only on provider performance reporting but also on developing and implementing rheumatology-specific standards across EHRs. %M 34766910 %R 10.2196/31186 %U https://medinform.jmir.org/2021/11/e31186 %U https://doi.org/10.2196/31186 %U http://www.ncbi.nlm.nih.gov/pubmed/34766910 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 9 %N 11 %P e28090 %T Toward Personalized Web-Based Cognitive Rehabilitation for Patients With Ischemic Stroke: Elo Rating Approach %A Garcia-Rudolph,Alejandro %A Opisso,Eloy %A Tormos,Jose M %A Madai,Vince Istvan %A Frey,Dietmar %A Becerra,Helard %A Kelleher,John D %A Bernabeu Guitart,Montserrat %A López,Jaume %+ Institut Guttmann Hospital de Neurorehabilitacio, Cami de Can Ruti s/n, Badalona, Spain, 34 934 97 77 00, alejandropablogarcia@gmail.com %K cognitive rehabilitation %K Elo rating %K predictors %K stroke rehabilitation %K web-based tasks %D 2021 %7 10.11.2021 %9 Original Paper %J JMIR Med Inform %G English %X Background: Stroke is a worldwide cause of disability; 40% of stroke survivors sustain cognitive impairments, most of them following inpatient rehabilitation at specialized clinical centers. Web-based cognitive rehabilitation tasks are extensively used in clinical settings. The impact of task execution depends on the ratio between the skills of the treated patient and the challenges imposed by the task itself. Thus, treatment personalization requires a trade-off between patients’ skills and task difficulties, which is still an open issue. In this study, we propose Elo ratings to support clinicians in tasks assignations and representing patients’ skills to optimize rehabilitation outcomes. Objective: This study aims to stratify patients with ischemic stroke at an early stage of rehabilitation into three levels according to their Elo rating; to show the relationships between the Elo rating levels, task difficulty levels, and rehabilitation outcomes; and to determine if the Elo rating obtained at early stages of rehabilitation is a significant predictor of rehabilitation outcomes. Methods: The PlayerRatings R library was used to obtain the Elo rating for each patient. Working memory was assessed using the DIGITS subtest of the Barcelona test, and the Rey Auditory Verbal Memory Test (RAVLT) was used to assess verbal memory. Three subtests of RAVLT were used: RAVLT learning (RAVLT075), free-recall memory (RAVLT015), and recognition (RAVLT015R). Memory predictors were identified using forward stepwise selection to add covariates to the models, which were evaluated by assessing discrimination using the area under the receiver operating characteristic curve (AUC) for logistic regressions and adjusted R2 for linear regressions. Results: Three Elo levels (low, middle, and high) with the same number of patients (n=96) in each Elo group were obtained using the 50 initial task executions (from a total of 38,177) for N=288 adult patients consecutively admitted for inpatient rehabilitation in a clinical setting. The mid-Elo level showed the highest proportions of patients that improved in all four memory items: 56% (54/96) of them improved in DIGITS, 67% (64/96) in RAVLT075, 58% (56/96) in RAVLT015, and 53% (51/96) in RAVLT015R (P<.001). The proportions of patients from the mid-Elo level that performed tasks at difficulty levels 1, 2, and 3 were 32.1% (3997/12,449), 31.% (3997/12,449), and 36.9% (4595/12,449), respectively (P<.001), showing the highest match between skills (represented by Elo level) and task difficulties, considering the set of 38,177 task executions. Elo ratings were significant predictors in three of the four models and quasi-significant in the fourth. When predicting RAVLT075 and DIGITS at discharge, we obtained R2=0.54 and 0.43, respectively; meanwhile, we obtained AUC=0.73 (95% CI 0.64-0.82) and AUC=0.81 (95% CI 0.72-0.89) in RAVLT075 and DIGITS improvement predictions, respectively. Conclusions: Elo ratings can support clinicians in early rehabilitation stages in identifying cognitive profiles to be used for assigning task difficulty levels. %M 34757325 %R 10.2196/28090 %U https://medinform.jmir.org/2021/11/e28090 %U https://doi.org/10.2196/28090 %U http://www.ncbi.nlm.nih.gov/pubmed/34757325 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 11 %P e27748 %T A Web-Based, Population-Based Cirrhosis Identification and Management System for Improving Cirrhosis Care: Qualitative Formative Evaluation %A Javier,Sarah J %A Wu,Justina %A Smith,Donna L %A Kanwal,Fasiha %A Martin,Lindsey A %A Clark,Jack %A Midboe,Amanda M %+ Center for Innovation to Implementation (Ci2i), VA Palo Alto Health Care System, 795 Willow Road (152-MPD), Menlo Park, CA, 94025, United States, 1 6504935000, Sarah.Javier@va.gov %K cirrhosis %K informatics %K care coordination %K implementation %K Consolidated Framework for Implementation Research (CFIR) %K quality improvement %D 2021 %7 9.11.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Cirrhosis, or scarring of the liver, is a debilitating condition that affects millions of US adults. Early identification, linkage to care, and retention of care are critical for preventing severe complications and death from cirrhosis. Objective: The purpose of this study is to conduct a preimplementation formative evaluation to identify factors that could impact implementation of the Population-Based Cirrhosis Identification and Management System (P-CIMS) in clinics serving patients with cirrhosis. P-CIMS is a web-based informatics tool designed to facilitate patient outreach and cirrhosis care management. Methods: Semistructured interviews were conducted between January and May 2016 with frontline providers in liver disease and primary care clinics at 3 Veterans Health Administration medical centers. A total of 10 providers were interviewed, including 8 physicians and midlevel providers from liver-related specialty clinics and 2 primary care providers who managed patients with cirrhosis. The Consolidated Framework for Implementation Research guided the development of the interview guides. Inductive consensus coding and content analysis were used to analyze transcribed interviews and abstracted coded passages, elucidated themes, and insights. Results: The following themes and subthemes emerged from the analyses: outer setting: needs and resources for patients with cirrhosis; inner setting: readiness for implementation (subthemes: lack of resources, lack of leadership support), and implementation climate (subtheme: competing priorities); characteristics of individuals: role within clinic; knowledge and beliefs about P-CIMS (subtheme: perceived and realized benefits; useful features; suggestions for improvement); and perceptions of current practices in managing cirrhosis cases (subthemes: preimplementation process for identifying and linking patients to cirrhosis care; structural and social barriers to follow-up). Overall, P-CIMS was viewed as a powerful tool for improving linkage and retention, but its integration in the clinical workflow required leadership support, time, and staffing. Providers also cited the need for more intuitive interface elements to enhance usability. Conclusions: P-CIMS shows promise as a powerful tool for identifying, linking, and retaining care in patients living with cirrhosis. The current evaluation identified several improvements and advantages of P-CIMS over current care processes and provides lessons for others implementing similar population-based identification and management tools in populations with chronic disease. %M 34751653 %R 10.2196/27748 %U https://formative.jmir.org/2021/11/e27748 %U https://doi.org/10.2196/27748 %U http://www.ncbi.nlm.nih.gov/pubmed/34751653 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 11 %P e23789 %T A Fully Collaborative, Noteless Electronic Medical Record Designed to Minimize Information Chaos: Software Design and Feasibility Study %A Steinkamp,Jackson %A Sharma,Abhinav %A Bala,Wasif %A Kantrowitz,Jacob J %+ Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, United States, 1 215 662 4000, jacksonsteinkamp@gmail.com %K electronic medical records %K clinical notes %K information chaos %K information overload %K clinician burnout %K software design %K problem-oriented medical record %K medical records %K electronic records %K documentation %K clinical %K software %D 2021 %7 9.11.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Clinicians spend large amounts of their workday using electronic medical records (EMRs). Poorly designed documentation systems contribute to the proliferation of out-of-date information, increased time spent on medical records, clinician burnout, and medical errors. Beyond software interfaces, examining the underlying paradigms and organizational structures for clinical information may provide insights into ways to improve documentation systems. In particular, our attachment to the note as the major organizational unit for storing unstructured medical data may be a cause of many of the problems with modern clinical documentation. Notes, as currently understood, systematically incentivize information duplication and information scattering, both within a single clinician’s notes over time and across multiple clinicians’ notes. Therefore, it is worthwhile to explore alternative paradigms for unstructured data organization. Objective: The aim of this study is to demonstrate the feasibility of building an EMR that does not use notes as the core organizational unit for unstructured data and which is designed specifically to disincentivize information duplication and information scattering. Methods: We used specific design principles to minimize the incentive for users to duplicate and scatter information. By default, the majority of a patient’s medical history remains the same over time, so users should not have to redocument that information. Clinicians on different teams or services mostly share the same medical information, so all data should be collaboratively shared across teams and services (while still allowing for disagreement and nuance). In all cases where a clinician must state that information has remained the same, they should be able to attest to the information without redocumenting it. We designed and built a web-based EMR based on these design principles. Results: We built a medical documentation system that does not use notes and instead treats the chart as a single, dynamically updating, and fully collaborative workspace. All information is organized by clinical topic or problem. Version history functionality is used to enable granular tracking of changes over time. Our system is highly customizable to individual workflows and enables each individual user to decide which data should be structured and which should be unstructured, enabling individuals to leverage the advantages of structured templating and clinical decision support as desired without requiring programming knowledge. The system is designed to facilitate real-time, fully collaborative documentation and communication among multiple clinicians. Conclusions: We demonstrated the feasibility of building a non–note-based, fully collaborative EMR system. Our attachment to the note as the only possible atomic unit of unstructured medical data should be reevaluated, and alternative models should be considered. %M 34751651 %R 10.2196/23789 %U https://formative.jmir.org/2021/11/e23789 %U https://doi.org/10.2196/23789 %U http://www.ncbi.nlm.nih.gov/pubmed/34751651 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 10 %P e28098 %T Comparing the Impact of Online Ratings and Report Cards on Patient Choice of Cardiac Surgeon: Large Observational Study %A Li,Xuan %A Chou,Shin-Yi %A Deily,Mary E %A Qian,Mengcen %+ School of Public Health, Fudan University, Key Laboratory of Health Technology Assessment, Ministry of Health, 130 Dong’an Road, Shanghai, 200032, China, 86 13524622077, qianmengcen@fudan.edu.cn %K online physician reviews %K report cards %K cardiac surgeons %K patient choice %D 2021 %7 28.10.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Patients may use two information sources about a health care provider’s quality: online physician reviews, which are written by patients to reflect their subjective experience, and report cards, which are based on objective health outcomes. Objective: The aim of this study was to examine the impact of online ratings on patient choice of cardiac surgeon compared to that of report cards. Methods: We obtained ratings from a leading physician review platform, Vitals; report card scores from Pennsylvania Cardiac Surgery Reports; and information about patients’ choices of surgeons from inpatient records on coronary artery bypass graft (CABG) surgeries done in Pennsylvania from 2008 to 2017. We scraped all reviews posted on Vitals for surgeons who performed CABG surgeries in Pennsylvania during our study period. We linked the average overall rating and the most recent report card score at the time of a patient’s surgery to the patient’s record based on the surgeon’s name, focusing on fee-for-service patients to avoid impacts of insurance networks on patient choices. We used random coefficient logit models with surgeon fixed effects to examine the impact of receiving a high online rating and a high report card score on patient choice of surgeon for CABG surgeries. Results: We found that a high online rating had positive and significant effects on patient utility, with limited variation in preferences across individuals, while the impact of a high report card score on patient choice was trivial and insignificant. About 70.13% of patients considered no information on Vitals better than a low rating; the corresponding figure was 26.66% for report card scores. The findings were robust to alternative choice set definitions and were not explained by surgeon attrition, referral effect, or admission status. Our results also show that the interaction effect of rating information and a time trend was positive and significant for online ratings, but small and insignificant for report cards. Conclusions: A patient’s choice of surgeon is affected by both types of rating information; however, over the past decade, online ratings have become more influential, while the effect of report cards has remained trivial. Our findings call for information provision strategies that incorporate the advantages of both online ratings and report cards. %M 34709192 %R 10.2196/28098 %U https://www.jmir.org/2021/10/e28098 %U https://doi.org/10.2196/28098 %U http://www.ncbi.nlm.nih.gov/pubmed/34709192 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 8 %N 4 %P e27671 %T Medical Specialists' Perspectives on the Influence of Electronic Medical Record Use on the Quality of Hospital Care: Semistructured Interview Study %A van Poelgeest,Rube %A Schrijvers,Augustinus %A Boonstra,Albert %A Roes,Kit %+ Julius Center, University Medical Center, University of Utrecht, Universiteitsweg 100, Utrecht, 3584 CG, Netherlands, 31 620139545, rube.van.poelgeest@planet.nl %K electronic medical record (emr) %K hospitals %K quality %K health care %K medical specialist %D 2021 %7 27.10.2021 %9 Original Paper %J JMIR Hum Factors %G English %X Background: Numerous publications show that electronic medical records (EMRs) may make an important contribution to increasing the quality of care. There are indications that particularly the medical specialist plays an important role in the use of EMRs in hospitals. Objective: The aim of this study was to examine how, and by which aspects, the relationship between EMR use and the quality of care in hospitals is influenced according to medical specialists. Methods: To answer this question, a qualitative study was conducted in the period of August-October 2018. Semistructured interviews of around 90 min were conducted with 11 medical specialists from 11 different Dutch hospitals. For analysis of the answers, we used a previously published taxonomy of factors that can influence the use of EMRs. Results: The professional experience of the participating medical specialists varied between 5 and 27 years. Using the previously published taxonomy, these medical specialists considered technical barriers the most significant for EMR use. The suboptimal change processes surrounding implementation were also perceived as a major barrier. A final major problem is related to the categories “social” (their relationships with the patients and fellow care providers), “psychological” (based on their personal issues, knowledge, and perceptions), and “time” (the time required to select, implement, and learn how to use EMR systems and subsequently enter data into the system). However, the medical specialists also identified potential technical facilitators, particularly in the assured availability of information to all health care professionals involved in the care of a patient. They see promise in using EMRs for medical decision support to improve the quality of care but consider these possibilities currently lacking. Conclusions: The 11 medical specialists shared positive experiences with EMR use when comparing it to formerly used paper records. The fact that involved health care professionals can access patient data at any time they need is considered important. However, in practice, potential quality improvement lags as long as decision support cannot be applied because of the lack of a fully coded patient record. %M 34704955 %R 10.2196/27671 %U https://humanfactors.jmir.org/2021/4/e27671 %U https://doi.org/10.2196/27671 %U http://www.ncbi.nlm.nih.gov/pubmed/34704955 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 10 %P e33158 %T An Advanced Nursing Directive for Children With Suspected Appendicitis: Protocol for a Quality Improvement Feasibility Study %A Chaudhari,Hanu %A Schneeweiss,Michelle %A Rebinsky,Reid %A Rullo,Enrico %A Eltorki,Mohamed %+ Faculty of Health Sciences, McMaster University, 1200 Main St W, Hamilton, ON, L8N 3Z5, Canada, 1 416 985 4520, hanu.chaudhari@medportal.ca %K quality improvement %K pediatric %K nursing %K medical directive %K appendicitis %K emergency department flow %K nursing directive %D 2021 %7 20.10.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Pediatric appendicitis accounts for an estimated 7% to 10% of abdominal pain cases in the emergency department (ED). The diagnosis is time-consuming, and the investigative process depends on physician assessment, resulting in delays in diagnosis and therapeutic management. The utility of an advanced nursing directive (AND) to expedite this process is unclear and needs further exploration. Objective: This study aims to describe key components of ED flow in patients with suspected appendicitis seen at a pediatric ED and pilot a directive that allows ED nurses to perform an order set that includes blood work, urine tests, analgesics, fluids, and an abdominal-pelvis ultrasound prior to physician assessment. Methods: This study involves conducting a retrospective chart review alongside a quality improvement initiative to compare key ED flow metrics before and after AND implementation. Primary outcome measures include median time from ED triage assessment to ultrasound completion, analgesia administration, blood work results, and time to disposition (consult or discharge), alongside other key ED flow metrics for suspected appendicitis. Secondary outcomes will involve patient and caretaker satisfaction surveys. Descriptive statistics will be used to summarize the data. For differences in proportions, a chi-square test will be used. The Student t test will be used for continuous variables. A variable-controlled run chart will be performed to assess impact on ED flow metrics. Patient and family satisfaction surveys are administered immediately after the directive encounter and 7 days afterward. Results: There are currently 3900 patients who have been screened, 344 patients who have been enrolled, and 90 patients who have received the medical directive since implementation in June 2020. Interim results on reduction of time to diagnostic and therapeutic ED flow parameters and satisfaction surveys are expected to be published in February 2022. The final study endpoint will be in June 2022. Conclusions: This study proposes a novel protocol for improving the diagnosis and treatment of suspected pediatric appendicitis through implementation of an evidence-based AND. This model may provide a standardized, international pathway for management of common pediatric and adult emergencies. International Registered Report Identifier (IRRID): RR1-10.2196/33158 %M 34668867 %R 10.2196/33158 %U https://www.researchprotocols.org/2021/10/e33158 %U https://doi.org/10.2196/33158 %U http://www.ncbi.nlm.nih.gov/pubmed/34668867 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 9 %P e27285 %T Assessment of the Quality Management System for Clinical Nutrition in Jiangsu: Survey Study %A Wang,Jin %A Pan,Chen %A Ma,Xianghua %+ First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing, 210029, China, 86 17625989728, yixingpanchen@163.com %K quality management system %K human resource management %K artificial intelligence %K online health %K health science %K clinical nutrition %K online platform %K health platform %K nutrition %K patient education %K dietitian %D 2021 %7 27.9.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: An electronic system that automatically collects medical information can realize timely monitoring of patient health and improve the effectiveness and accuracy of medical treatment. To our knowledge, the application of artificial intelligence (AI) in medical service quality assessment has been minimally evaluated, especially for clinical nutrition departments in China. From the perspective of medical ethics, patient safety comes before any other factors within health science, and this responsibility belongs to the quality management system (QMS) within medical institutions. Objective: This study aims to evaluate the QMS for clinical nutrition in Jiangsu, monitor its performance in quality assessment and human resource management from a nutrition aspect, and investigate the application and development of AI in medical quality control. Methods: The participants for this study were the staff of 70 clinical nutrition departments of the tertiary hospitals in Jiangsu Province, China. These departments are all members of the Quality Management System of Clinical Nutrition in Jiangsu (QMSNJ). An online survey was conducted on all 341 employees within all clinical nutrition departments based on the staff information from the surveyed medical institutions. The questionnaire contains five sections, and the data analysis and AI evaluation were focused on human resource information. Results: A total of 330 questionnaires were collected, with a response rate of 96.77% (330/341). A QMS for clinical nutrition was built for clinical nutrition departments in Jiangsu and achieved its target of human resource improvements, especially among dietitians. The growing number of participating departments (an increase of 42.8% from 2018 to 2020) and the significant growth of dietitians (t93.4=–0.42; P=.02) both show the advancements of the QMSNJ. Conclusions: As the first innovation of an online platform for quality management in Jiangsu, the Jiangsu Province Clinical Nutrition Management Platform was successfully implemented as a QMS for this study. This multidimensional electronic system can help the QMSNJ and clinical nutrition departments achieve quality assessment from various aspects so as to realize the continuous improvement of clinical nutrition. The use of an online platform and AI technology for quality assessment is worth recommending and promoting in the future. %M 34569942 %R 10.2196/27285 %U https://formative.jmir.org/2021/9/e27285 %U https://doi.org/10.2196/27285 %U http://www.ncbi.nlm.nih.gov/pubmed/34569942 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 8 %P e26350 %T A Study to Investigate the Prevalence of Device-Specific Errors in Inhaler Technique in Adults With Airway Disease (The SCORES Study): Protocol for a Single Visit Prevalence Study %A De Vos,Ruth %A Brown,Thomas %A Longstaff,Jayne %A Lomax,Mitch %A Mackenzie,Heather %A Hicks,Alexander %A Rupani,Hitasha %A Gates,Jessica %A Fox,Lauren %A Wiffen,Laura %A Chauhan,Anoop J %+ Portsmouth Hospitals University NHS Trust, Research and Innovation Department, Southwick Hill Road, Cosham, Portsmouth, PO6 3LY, United Kingdom, 44 2392286000 ext 3125, ruth.devos@porthosp.nhs.uk %K inhaler %K inhaler technique %K inhaler technique error %K asthma %K COPD %D 2021 %7 27.8.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: It is a recurring theme in clinical practice that patients using inhaled medications via an inhaler do not use their device to a standard that allows for optimum therapeutic effect, and some studies have shown that up to 90% of people do not use their inhalers properly. Observation and correction of the inhaler technique by health care professionals is advised by both national and international guidelines and should be performed at every opportunity to ensure that the optimum inhaler technique is achieved by the user. This study will provide a greater understanding of the most frequent technique errors made by people using 13 different inhaler types. Objective: This study aims to identify and compare inhaler technique errors and their prevalence in adults, using device-specific checklists in accordance with manufacturers’ guidelines, for 13 specific inhaler types across all lung conditions and to correlate these errors with possible determinants of poor technique. It also aims to assess the error frequency at each step in the device-specific questionnaires and compare the error rates among device types. Methods: In a single visit, participants using an inhaler included in the inclusion criteria will have their inhaler technique observed using an identical placebo device, which will be recorded using device-specific checklists, and technique-optimized, or switched to a suitable inhaler. Results: The study is already underway, and it is anticipated that the results will be available by 2022. Conclusions: The SCORES (Study to Investigate the Prevalence of Device-Specific Errors in Inhaler Technique in Adults With Airway Disease) study will ascertain the prevalence of device-specific inhaler technique errors at each step in the device-specific checklists, compare error rates among 13 device types, and correlate these errors with possible determinants of poor technique. Future work will involve the clarification and classification of these errors into critical and noncritical categories. Trial Registration: ClinicalTrials.gov NCT04262271; https://clinicaltrials.gov/ct2/show/NCT04262271 International Registered Report Identifier (IRRID): DERR1-10.2196/26350 %M 34448728 %R 10.2196/26350 %U https://www.researchprotocols.org/2021/8/e26350 %U https://doi.org/10.2196/26350 %U http://www.ncbi.nlm.nih.gov/pubmed/34448728 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 8 %P e26887 %T Analysis of Hospital Quality Measures and Web-Based Chargemasters, 2019: Cross-sectional Study %A Patel,Kunal N %A Mazurenko,Olena %A Ford,Eric %+ Northern Illinois University, 1425 West Lincoln Highway, DeKalb, IL, 60115, United States, 1 815 753 1891, kpatel27@niu.edu %K chargemaster %K standard charge %K price transparency %K health care %K diagnosis-related group %K DRG %K quality measures %K the Centers for Medicare and Medicaid Services regulation %K CMS %D 2021 %7 19.8.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: The federal health care price transparency regulation from 2019 is aimed at bending the health care cost curve by increasing the availability of hospital pricing information for the public. Objective: This study aims to examine the associations between publicly reported diagnosis-related group chargemaster prices on the internet and quality measures, process indicators, and patient-reported experience measures. Methods: In this cross-sectional study, we collected and analyzed a random 5.02% (212/4221) stratified sample of US hospital prices in 2019 using descriptive statistics and multivariate analysis. Results: We found extreme price variation in shoppable services and significantly greater price variation for medical versus surgical services (P=.006). In addition, we found that quality indicators were positively associated with standard charges, such as mortality (β=.929; P<.001) and readmissions (β=.514; P<.001). Other quality indicators, such as the effectiveness of care (β=−.919; P<.001), efficient use of medical imaging (β=−.458; P=.001), and patient recommendation scores (β=−.414; P<.001), were negatively associated with standard charges. Conclusions: We found that hospital chargemasters display wide variations in prices for medical services and procedures and match variations in quality measures. Further work is required to investigate 100% of US hospital prices posted publicly on the internet and their relationship with quality measures. %M 34420914 %R 10.2196/26887 %U https://formative.jmir.org/2021/8/e26887 %U https://doi.org/10.2196/26887 %U http://www.ncbi.nlm.nih.gov/pubmed/34420914 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 8 %P e26700 %T Matching Registered Nurse Services With Changing Care Demands in Psychiatric Hospitals: Protocol for a Multicenter Observational Study (MatchRN Psychiatry Study) %A Gehri,Beatrice %A Bachnick,Stefanie %A Schwendimann,René %A Simon,Michael %+ Institute of Nursing Science, University of Basel, Bernoullistrasse 28, Basel, 4056, Switzerland, 41 41 61 207 0912, m.simon@unibas.ch %K quality of care %K psychiatric hospitals %K nurses %K patient routine data %K work environment %K Switzerland %D 2021 %7 17.8.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: The quality of care is often poorly assessed in mental health settings, and accurate evaluation requires the monitoring and comparison of not only the outcomes but also the structures and processes. The resulting data allow hospital administrators to compare their patient outcome data against those reported nationally. As Swiss psychiatric hospitals are planned and coordinated at the cantonal level, they vary considerably. In addition, nursing care structures and processes, such as nurse staffing, are only reported and aggregated at the national level, whereas nurse outcomes, such as job satisfaction or intention to leave, have yet to be assessed in Swiss psychiatric hospitals. Because they lack these key figures, psychiatric hospitals’ quality of care cannot be reasonably described. Objective: This study’s purpose is to describe health care quality by exploring hospital structures such as nurse staffing and the work environment; processes such as the rationing of care; nurse outcomes, including job satisfaction and work-life balance; and patients’ symptom burden. Methods: MatchRN Psychiatry is a multicenter observational study of Swiss psychiatric hospitals. The sample for this study included approximately 1300 nurses from 113 units of 13 psychiatric hospitals in Switzerland’s German-speaking region. In addition, routine patient assessment data from each participating hospital were included. The nurse survey consisted of 164 items covering three dimensions—work environment, patient safety climate, and the rationing of care. The unit-level questionnaire included 57 items, including the number of beds, number of nurses, and nurses’ education levels. Routine patient data included items such as main diagnosis, the number and duration of freedom-restrictive measures, and symptom burden at admission and discharge. Data were collected between September 2019 and June 2021. The data will be analyzed descriptively by using multilevel regression linear mixed models and generalized linear mixed models to explore associations between variables of interest. Results: The response rate from the nurse survey was 71.49% (1209/1691). All data are currently being checked for consistency and plausibility. The MatchRN Psychiatry study is funded by the participating psychiatric hospitals and the Swiss Psychiatric Nursing Leaders Association (Vereinigung Pflegekader Psychiatrie Schweiz). Conclusions: For the first time, the MatchRN Psychiatry study will systematically evaluate the quality of care in psychiatric hospitals in Switzerland in terms of organizational structures, processes, and patient and nurse outcomes. The participating psychiatric hospitals will benefit from findings that are relevant to the future planning of nurse staffing. The findings of this study will contribute to improvement strategies for nurses’ work environments and patient experiences in Swiss psychiatric hospitals. International Registered Report Identifier (IRRID): DERR1-10.2196/26700 %M 34402796 %R 10.2196/26700 %U https://www.researchprotocols.org/2021/8/e26700 %U https://doi.org/10.2196/26700 %U http://www.ncbi.nlm.nih.gov/pubmed/34402796 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 8 %P e30453 %T Digital Orientation of Health Systems in the Post–COVID-19 “New Normal” in the United States: Cross-sectional Survey %A Khuntia,Jiban %A Ning,Xue %A Stacey,Rulon %+ CU Business School, University of Colorado Denver, 1475 Lawrence Street, Denver, CO, 80202, United States, 1 3038548024, jiban.khuntia@ucdenver.edu %K post–COVID-19 %K digital orientation %K health systems %K digital transformation %K digital health %K telehealth %K telemedicine %K COVID-19 %K impact %K insight %K cross-sectional %K survey %K United States %K electronic health record %K EHR %D 2021 %7 16.8.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Almost all health systems have developed some form of customer-facing digital technologies and have worked to align these systems to their existing electronic health records to accommodate the surge in remote and virtual care deliveries during the COVID-19 pandemic. Others have developed analytics-driven decision-making capabilities. However, it is not clear how health systems in the United States are embracing digital technologies and there is a gap in health systems’ abilities to integrate workflows with expanding technologies to spur innovation and futuristic growth. There is a lack of reliable and reported estimates of the current and futuristic digital orientations of health systems. Periodic assessments will provide imperatives to policy formulation and align efforts to yield the transformative power of emerging digital technologies. Objective: The aim of this study was to explore and examine differences in US health systems with respect to digital orientations in the post–COVID-19 “new normal” in 2021. Differences were assessed in four dimensions: (1) analytics-oriented digital technologies (AODT), (2) customer-oriented digital technologies (CODT), (3) growth and innovation–oriented digital technologies (GODT), and (4) futuristic and experimental digital technologies (FEDT). The former two dimensions are foundational to health systems’ digital orientation, whereas the latter two will prepare for future disruptions. Methods: We surveyed a robust group of health system chief executive officers (CEOs) across the United States from February to March 2021. Among the 625 CEOs, 135 (22%) responded to our survey. We considered the above four broad digital technology orientations, which were ratified with expert consensus. Secondary data were collected from the Agency for Healthcare Research and Quality Hospital Compendium, leading to a matched usable dataset of 124 health systems for analysis. We examined the relationship of adopting the four digital orientations to specific hospital characteristics and earlier reported factors as barriers or facilitators to technology adoption. Results: Health systems showed a lower level of CODT (mean 4.70) or GODT (mean 4.54) orientations compared with AODT (mean 5.03), and showed the lowest level of FEDT orientation (mean 4.31). The ordered logistic estimation results provided nuanced insights. Medium-sized (P<.001) health systems, major teaching health systems (P<.001), and systems with high-burden hospitals (P<.001) appear to be doing worse with respect to AODT orientations, raising some concerns. Health systems of medium (P<.001) and large (P=.02) sizes, major teaching health systems (P=.07), those with a high revenue (P=.05), and systems with high-burden hospitals (P<.001) have less CODT orientation. Health systems in the midwest (P=.05) and southern (P=.04) states are more likely to adopt GODT, whereas high-revenue (P=.004) and investor-ownership (P=.01) health systems are deterred from GODT. Health systems of a medium size, and those that are in the midwest (P<.001), south (P<.001), and west (P=.01) are more adept to FEDT, whereas medium (P<.001) and high-revenue (P<.001) health systems, and those with a high discharge rate (P=.04) or high burden (P=.003, P=.005) have subdued FEDT orientations. Conclusions: Almost all health systems have some current foundational digital technological orientations to glean intelligence or service delivery to customers, with some notable exceptions. Comparatively, fewer health systems have growth or futuristic digital orientations. The transformative power of digital technologies can only be leveraged by adopting futuristic digital technologies. Thus, the disparities across these orientations suggest that a holistic, consistent, and well-articulated direction across the United States remains elusive. Accordingly, we suggest that a policy strategy and financial incentives are necessary to spur a well-visioned and articulated digital orientation for all health systems across the United States. In the absence of such a policy to collectively leverage digital transformations, differences in care across the country will continue to be a concern. %M 34254947 %R 10.2196/30453 %U https://www.jmir.org/2021/8/e30453 %U https://doi.org/10.2196/30453 %U http://www.ncbi.nlm.nih.gov/pubmed/34254947 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 9 %N 8 %P e27842 %T Quality of Hospital Electronic Health Record (EHR) Data Based on the International Consortium for Health Outcomes Measurement (ICHOM) in Heart Failure: Pilot Data Quality Assessment Study %A Aerts,Hannelore %A Kalra,Dipak %A Sáez,Carlos %A Ramírez-Anguita,Juan Manuel %A Mayer,Miguel-Angel %A Garcia-Gomez,Juan M %A Durà-Hernández,Marta %A Thienpont,Geert %A Coorevits,Pascal %+ Research Programme on Biomedical Informatics, Hospital del Mar Medical Research Institute and Universitat Pompeu Fabra, C/ Dr Aiguader 88, Barcelona, 08003, Spain, 34 933 160 539, miguelangel.mayer@upf.edu %K data quality %K electronic health records %K heart failure %K value-based health insurance %K patient outcome assessment %D 2021 %7 4.8.2021 %9 Original Paper %J JMIR Med Inform %G English %X Background: There is increasing recognition that health care providers need to focus attention, and be judged against, the impact they have on the health outcomes experienced by patients. The measurement of health outcomes as a routine part of clinical documentation is probably the only scalable way of collecting outcomes evidence, since secondary data collection is expensive and error-prone. However, there is uncertainty about whether routinely collected clinical data within electronic health record (EHR) systems includes the data most relevant to measuring and comparing outcomes and if those items are collected to a good enough data quality to be relied upon for outcomes assessment, since several studies have pointed out significant issues regarding EHR data availability and quality. Objective: In this paper, we first describe a practical approach to data quality assessment of health outcomes, based on a literature review of existing frameworks for quality assessment of health data and multistakeholder consultation. Adopting this approach, we performed a pilot study on a subset of 21 International Consortium for Health Outcomes Measurement (ICHOM) outcomes data items from patients with congestive heart failure. Methods: All available registries compatible with the diagnosis of heart failure within an EHR data repository of a general hospital (142,345 visits and 12,503 patients) were extracted and mapped to the ICHOM format. We focused our pilot assessment on 5 commonly used data quality dimensions: completeness, correctness, consistency, uniqueness, and temporal stability. Results: We found high scores (>95%) for the consistency, completeness, and uniqueness dimensions. Temporal stability analyses showed some changes over time in the reported use of medication to treat heart failure, as well as in the recording of past medical conditions. Finally, the investigation of data correctness suggested several issues concerning the characterization of missing data values. Many of these issues appear to be introduced while mapping the IMASIS-2 relational database contents to the ICHOM format, as the latter requires a level of detail that is not explicitly available in the coded data of an EHR. Conclusions: Overall, results of this pilot study revealed good data quality for the subset of heart failure outcomes collected at the Hospital del Mar. Nevertheless, some important data errors were identified that were caused by fundamentally different data collection practices in routine clinical care versus research, for which the ICHOM standard set was originally developed. To truly examine to what extent hospitals today are able to routinely collect the evidence of their success in achieving good health outcomes, future research would benefit from performing more extensive data quality assessments, including all data items from the ICHOM standards set and across multiple hospitals. %M 34346902 %R 10.2196/27842 %U https://medinform.jmir.org/2021/8/e27842 %U https://doi.org/10.2196/27842 %U http://www.ncbi.nlm.nih.gov/pubmed/34346902 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 9 %N 7 %P e27980 %T Frequency of Participation in External Quality Assessment Programs Focused on Rare Diseases: Belgian Guidelines for Human Genetics Centers %A Lantoine,Joséphine %A Brysse,Anne %A Dideberg,Vinciane %A Claes,Kathleen %A Symoens,Sofie %A Coucke,Wim %A Benoit,Valérie %A Rombout,Sonia %A De Rycke,Martine %A Seneca,Sara %A Van Laer,Lut %A Wuyts,Wim %A Corveleyn,Anniek %A Van Den Bogaert,Kris %A Rydlewski,Catherine %A Wilkin,Françoise %A Ravoet,Marie %A Fastré,Elodie %A Capron,Arnaud %A Vandevelde,Nathalie Monique %+ Rare Diseases Unit, Department of Quality of Laboratories, Sciensano, Juliette Wytsman street, 14, Brussels, 1050, Belgium, 32 2 642 55 89, nathalie.vandevelde@sciensano.be %K human genetics %K external quality assessment %K quality control %K proficiency testing %K frequency %K genetic testing %K rare diseases %K cost-effectiveness %K surveillance, public health authorities %K public health %K health informatics %K medical informatics %K genetics %K human genetics %K algorithm %D 2021 %7 12.7.2021 %9 Original Paper %J JMIR Med Inform %G English %X Background: Participation in quality controls, also called external quality assessment (EQA) schemes, is required for the ISO15189 accreditation of the Medical Centers of Human Genetics. However, directives on the minimal frequency of participation in genetic quality control schemes are lacking or too heterogeneous, with a possible impact on health care quality. Objective: The aim of this project is to develop Belgian guidelines on the frequency of participation in quality controls for genetic testing in the context of rare diseases. Methods: A group of experts analyzed 90 EQA schemes offered by accredited providers and focused on analyses used for the diagnosis of rare diseases. On that basis, the experts developed practical recommendations about the minimal frequencies of participation of the Medical Centers of Human Genetics in quality controls and how to deal with poor performances and change management. These guidelines were submitted to the Belgian Accreditation Body and then reviewed and approved by the Belgian College of Human Genetics and Rare Diseases and by the National Institute for Health and Disability Insurance. Results: The guidelines offer a decisional algorithm for the minimal frequency of participation in human genetics EQA schemes. This algorithm has been developed taking into account the scopes of the EQA schemes, the levels of experience, and the annual volumes of the Centers of Human Genetics in the performance of the tests considered. They include three key principles: (1) the recommended annual assessment of all genetic techniques and technological platforms, if possible through EQAs covering the technique, genotyping, and clinical interpretation; (2) the triennial assessment of the genotyping and interpretation of specific germline mutations and pharmacogenomics analyses; and (3) the documentation of actions undertaken in the case of poor performances and the participation to quality control the following year. The use of a Bayesian statistical model has been proposed to help the Centers of Human Genetics to determine the theoretical number of tests that should be annually performed to achieve a certain threshold of performance (eg, a maximal error rate of 1%). Besides, the guidelines insist on the role and responsibility of the national public health authorities in the follow-up of the quality of analyses performed by the Medical Centers of Human Genetics and in demonstrating the cost-effectiveness and rationalization of participation frequency in these quality controls. Conclusions: These guidelines have been developed based on the analysis of a large panel of EQA schemes and data collected from the Belgian Medical Centers of Human Genetics. They are applicable to other countries and will facilitate and improve the quality management and financing systems of the Medical Centers of Human Genetics. %M 34255700 %R 10.2196/27980 %U https://medinform.jmir.org/2021/7/e27980 %U https://doi.org/10.2196/27980 %U http://www.ncbi.nlm.nih.gov/pubmed/34255700 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 6 %P e26391 %T A Typology of Existing Machine Learning–Based Predictive Analytic Tools Focused on Reducing Costs and Improving Quality in Health Care: Systematic Search and Content Analysis %A Nichol,Ariadne A %A Batten,Jason N %A Halley,Meghan C %A Axelrod,Julia K %A Sankar,Pamela L %A Cho,Mildred K %+ Stanford School of Medicine, Stanford Center for Biomedical Ethics, 1215 Welch Road, Modular A, Stanford, CA, 94305, United States, 1 650 723 5760, ariadnen@stanford.edu %K machine learning %K artificial intelligence %K ethics %K regulation %K health care quality %K costs %D 2021 %7 22.6.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Considerable effort has been devoted to the development of artificial intelligence, including machine learning–based predictive analytics (MLPA) for use in health care settings. The growth of MLPA could be fueled by payment reforms that hold health care organizations responsible for providing high-quality, cost-effective care. Policy analysts, ethicists, and computer scientists have identified unique ethical and regulatory challenges from the use of MLPA in health care. However, little is known about the types of MLPA health care products available on the market today or their stated goals. Objective: This study aims to better characterize available MLPA health care products, identifying and characterizing claims about products recently or currently in use in US health care settings that are marketed as tools to improve health care efficiency by improving quality of care while reducing costs. Methods: We conducted systematic database searches of relevant business news and academic research to identify MLPA products for health care efficiency meeting our inclusion and exclusion criteria. We used content analysis to generate MLPA product categories and characterize the organizations marketing the products. Results: We identified 106 products and characterized them based on publicly available information in terms of the types of predictions made and the size, type, and clinical training of the leadership of the companies marketing them. We identified 5 categories of predictions made by MLPA products based on publicly available product marketing materials: disease onset and progression, treatment, cost and utilization, admissions and readmissions, and decompensation and adverse events. Conclusions: Our findings provide a foundational reference to inform the analysis of specific ethical and regulatory challenges arising from the use of MLPA to improve health care efficiency. %M 34156338 %R 10.2196/26391 %U https://www.jmir.org/2021/6/e26391 %U https://doi.org/10.2196/26391 %U http://www.ncbi.nlm.nih.gov/pubmed/34156338 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 6 %P e17095 %T Rating Hospital Performance in China: Review of Publicly Available Measures and Development of a Ranking System %A Dong,Shengjie %A Millar,Ross %A Shi,Chenshu %A Dong,Minye %A Xiao,Yuyin %A Shen,Jie %A Li,Guohong %+ China Hospital Development Institute, Shanghai Jiao Tong University School of Medicine, 227 South Chong Qing Road, Shanghai, 200025, China, 86 21 63846590, guohongli@sjtu.edu.cn %K hospital ranking %K performance measurement %K health care quality %K China health care reform %D 2021 %7 17.6.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: In China, significant emphasis and investment in health care reform since 2009 has brought with it increasing scrutiny of its public hospitals. Calls for greater accountability in the quality of hospital care have led to increasing attention toward performance measurement and the development of hospital ratings. Despite such interest, there has yet to be a comprehensive analysis of what performance information is publicly available to understand the performance of hospitals in China. Objective: This study aims to review the publicly available performance information about hospitals in China to assess options for ranking hospital performance. Methods: A review was undertaken to identify performance measures based on publicly available data. Following several rounds of expert consultation regarding the utility of these measures, we clustered the available options into three key areas: research and development, academic reputation, and quality and safety. Following the identification and clustering of the available performance measures, we set out to translate these into a practical performance ranking system to assess variation in hospital performance. Results: A new hospital ranking system termed the China Hospital Development Index (CHDI) is thus presented. Furthermore, we used CHDI for ranking well-known tertiary hospitals in China. Conclusions: Despite notable limitations, our assessment of available measures and the development of a new ranking system break new ground in understanding hospital performance in China. In doing so, CHDI has the potential to contribute to wider discussions and debates about assessing hospital performance across global health care systems. %M 34137724 %R 10.2196/17095 %U https://www.jmir.org/2021/6/e17095 %U https://doi.org/10.2196/17095 %U http://www.ncbi.nlm.nih.gov/pubmed/34137724 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 5 %P e23479 %T Information Quality Frameworks for Digital Health Technologies: Systematic Review %A Fadahunsi,Kayode Philip %A O'Connor,Siobhan %A Akinlua,James Tosin %A Wark,Petra A %A Gallagher,Joseph %A Carroll,Christopher %A Car,Josip %A Majeed,Azeem %A O'Donoghue,John %+ Department of Public Health and Primary Care, Imperial College London, The Reynolds Building, St. Dunstan’s Road, London, W6 8RP, United Kingdom, 44 07477854209, K.fadahunsi14@imperial.ac.uk %K digital health %K patient safety %K information quality %D 2021 %7 17.5.2021 %9 Review %J J Med Internet Res %G English %X Background: Digital health technologies (DHTs) generate a large volume of information used in health care for administrative, educational, research, and clinical purposes. The clinical use of digital information for diagnostic, therapeutic, and prognostic purposes has multiple patient safety problems, some of which result from poor information quality (IQ). Objective: This systematic review aims to synthesize an IQ framework that could be used to evaluate the extent to which digital health information is fit for clinical purposes. Methods: The review was conducted according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines. We searched Embase, MEDLINE, PubMed, CINAHL, Maternity and Infant Care, PsycINFO, Global Health, ProQuest Dissertations and Theses Global, Scopus, and HMIC (the Health Management Information Consortium) from inception until October 2019. Multidimensional IQ frameworks for assessing DHTs used in the clinical context by health care professionals were included. A thematic synthesis approach was used to synthesize the Clinical Information Quality (CLIQ) framework for digital health. Results: We identified 10 existing IQ frameworks from which we developed the CLIQ framework for digital health with 13 unique dimensions: accessibility, completeness, portability, security, timeliness, accuracy, interpretability, plausibility, provenance, relevance, conformance, consistency, and maintainability, which were categorized into 3 meaningful categories: availability, informativeness, and usability. Conclusions: This systematic review highlights the importance of the IQ of DHTs and its relevance to patient safety. The CLIQ framework for digital health will be useful in evaluating and conceptualizing IQ issues associated with digital health, thus forestalling potential patient safety problems. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42018097142; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=97142 International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2018-024722 %M 33835034 %R 10.2196/23479 %U https://www.jmir.org/2021/5/e23479 %U https://doi.org/10.2196/23479 %U http://www.ncbi.nlm.nih.gov/pubmed/33835034 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 5 %P e27963 %T Presenteeism Among Nurses in Switzerland and Portugal and Its Impact on Patient Safety and Quality of Care: Protocol for a Qualitative Study %A Pereira,Filipa %A Querido,Ana Isabel %A Bieri,Marion %A Verloo,Henk %A Laranjeira,Carlos António %+ School of Health Sciences, HES-SO Valais/Wallis, Chemin de l'Agasse 5, Sion, 1950, Switzerland, 41 786661700, filipa.pereira@hevs.ch %K healthcare %K nurses %K predictors %K presenteeism %K quality of care %K frontline %K managers %K Portugal %K Switzerland %K patient safety %K patients %K safety %K stress %K emotion %K knowledge transfer %K acute care %K long-term care %D 2021 %7 13.5.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Nurses dispense direct care in a wide variety of settings and are considered the backbone of the health care system. They often work long hours, face emotional stress, and are at a high risk of psychosocial and somatic illnesses. Nurses sometimes fall sick but work regardless, leading to presenteeism and subsequent risks to quality of care and patient safety due to the increased likelihood of patients falling, medication errors, and staff-to-patient disease transmission. Objective: This study aims to understand presenteeism among frontline nurses and nurse managers in acute, primary, and long-term health care settings and to contribute to the development of future interventional studies and recommendations. Methods: A qualitative study based on online focus group discussions will explore the perceptions of, attitudes to, and experiences with presenteeism among frontline nurses and nurse managers. Using a pilot-tested interview guide, 8 focus group discussions will involve nurses working in acute care hospitals, primary care settings, and long-term residential care facilities in Switzerland’s French-speaking region and Portugal’s Center region. The data collected will be examined using a content analysis approach via NVivo 12 QSR International software. Results: The University of Applied Sciences and Arts Western Switzerland’s School of Health Sciences and the Polytechnic of Leiria’s School of Health Sciences in Portugal have both approved funding for the study. The research protocol has been approved by ethics committees in both countries. Study recruitment commenced in February 2021. The results of the data analysis are expected by September 2021. Conclusions: This present study aims to gain more insight into the dilemmas facing nurses as a result of all causes of presenteeism among frontline nurses and nurse managers in different health care settings. The researchers will prepare manuscripts on the study’s findings, publish them in relevant peer-reviewed journals, exhibit them in poster presentations, and give oral presentations at appropriate academic and nonscientific conferences. Regarding further knowledge transfer, researchers will engage with stakeholders to craft messages focused on the needs of nurses and nurse managers and on disseminating our research findings to deal with the issue of nursing presenteeism. International Registered Report Identifier (IRRID): PRR1-10.2196/27963 %M 33983134 %R 10.2196/27963 %U https://www.researchprotocols.org/2021/5/e27963 %U https://doi.org/10.2196/27963 %U http://www.ncbi.nlm.nih.gov/pubmed/33983134 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 5 %P e27180 %T The Challenge of Integrating eHealth Into Health Care: Systematic Literature Review of the Donabedian Model of Structure, Process, and Outcome %A Tossaint-Schoenmakers,Rosian %A Versluis,Anke %A Chavannes,Niels %A Talboom-Kamp,Esther %A Kasteleyn,Marise %+ Saltro Diagnostic Centre, Mississippidreef 83, Utrecht, 3565 CE, Netherlands, 31 6 55895361, rtossaint@saltro.nl %K eHealth %K digital health %K blended care %K quality %K integration %K health care organization %K structure %K process %K outcome %D 2021 %7 10.5.2021 %9 Review %J J Med Internet Res %G English %X Background: Health care organizations are increasingly working with eHealth. However, the integration of eHealth into regular health care is challenging. It requires organizations to change the way they work and their structure and care processes to be adapted to ensure that eHealth supports the attainment of the desired outcomes. Objective: The aims of this study are to investigate whether there are identifiable indicators in the structure, process, and outcome categories that are related to the successful integration of eHealth in regular health care, as well as to investigate which indicators of structure and process are related to outcome indicators. Methods: A systematic literature review was conducted using the Donabedian Structure-Process-Outcome (SPO) framework to identify indicators that are related to the integration of eHealth into health care organizations. Data extraction sheets were designed to provide an overview of the study characteristics, eHealth characteristics, and indicators. The extracted indicators were organized into themes and subthemes of the structure, process, and outcome categories. Results: Eleven studies were included, covering a variety of study designs, diseases, and eHealth tools. All studies identified structure, process, and outcome indicators that were potentially related to the integration of eHealth. The number of indicators found in the structure, process, and outcome categories was 175, 84, and 88, respectively. The themes with the most-noted indicators and their mutual interaction were inner setting (51 indicators, 16 interactions), care receiver (40 indicators, 11 interactions), and technology (38 indicators, 12 interactions)—all within the structure category; health care actions (38 indicators, 15 interactions) within the process category; and efficiency (30 indicators, 15 interactions) within the outcome category. In-depth examination identified four most-reported indicators, namely “deployment of human resources” (n=11), in the inner setting theme within the structure category; “ease of use” (n=16) and “technical issue” (n=10), both in the technology theme within the structure category; and “health logistics” (n=26), in the efficiency theme within the outcome category. Conclusions: Three principles are important for the successful integration of eHealth into health care. First, the role of the care receiver needs to be incorporated into the organizational structure and daily care process. Second, the technology must be well attuned to the organizational structure and daily care process. Third, the deployment of human resources to the daily care processes needs to be aligned with the desired end results. Not adhering to these points could negatively affect the organization, daily process, or the end results. %M 33970123 %R 10.2196/27180 %U https://www.jmir.org/2021/5/e27180 %U https://doi.org/10.2196/27180 %U http://www.ncbi.nlm.nih.gov/pubmed/33970123 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 5 %P e17240 %T Validation of 4D Components for Measuring Quality of the Public Health Data Collection Process: Elicitation Study %A Chen,Hong %A Yu,Ping %A Hailey,David %A Cui,Tingru %+ School of Computing and Information Technology, Faculty of Engineering and Information Sciences, University of Wollongong, Northfields Ave, Wollongong, 2522, Australia, 61 2 42215412, ping@uow.edu.au %K data quality %K data collection %K HIV/AIDS %K public health informatics %K health information systems %K component validation %K expert elicitation %K public health %K health informatics %D 2021 %7 10.5.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Identification of the essential components of the quality of the data collection process is the starting point for designing effective data quality management strategies for public health information systems. An inductive analysis of the global literature on the quality of the public health data collection process has led to the formation of a preliminary 4D component framework, that is, data collection management, data collection personnel, data collection system, and data collection environment. It is necessary to empirically validate the framework for its use in future research and practice. Objective: This study aims to obtain empirical evidence to confirm the components of the framework and, if needed, to further develop this framework. Methods: Expert elicitation was used to evaluate the preliminary framework in the context of the Chinese National HIV/AIDS Comprehensive Response Information Management System. The research processes included the development of an interview guide and data collection form, data collection, and analysis. A total of 3 public health administrators, 15 public health workers, and 10 health care practitioners participated in the elicitation session. A framework qualitative data analysis approach and a quantitative comparative analysis were followed to elicit themes from the interview transcripts and to map them to the elements of the preliminary 4D framework. Results: A total of 302 codes were extracted from interview transcripts. After iterative and recursive comparison, classification, and mapping, 46 new indicators emerged; 24.8% (37/149) of the original indicators were deleted because of a lack of evidence support and another 28.2% (42/149) were merged. The validated 4D component framework consists of 116 indicators (82 facilitators and 34 barriers). The first component, data collection management, includes data collection protocols and quality assurance. It was measured by 41 indicators, decreased from the original 49% (73/149) to 35.3% (41/116). The second component, data collection environment, was measured by 37 indicators, increased from the original 13.4% (20/149) to 31.9% (37/116). It comprised leadership, training, funding, organizational policy, high-level management support, and collaboration among parallel organizations. The third component, data collection personnel, includes the perception of data collection, skills and competence, communication, and staffing patterns. There was no change in the proportion for data collection personnel (19.5% vs 19.0%), although the number of its indicators was reduced from 29 to 22. The fourth component, the data collection system, was measured using 16 indicators, with a slight decrease in percentage points from 18.1% (27/149) to 13.8% (16/116). It comprised functions, system integration, technical support, and data collection devices. Conclusions: This expert elicitation study validated and improved the 4D framework. The framework can be useful in developing a questionnaire survey instrument for measuring the quality of the public health data collection process after validation of psychometric properties and item reduction. %M 33970112 %R 10.2196/17240 %U https://www.jmir.org/2021/5/e17240 %U https://doi.org/10.2196/17240 %U http://www.ncbi.nlm.nih.gov/pubmed/33970112 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 4 %P e23961 %T Association of Electronic Health Record Vendors With Hospital Financial and Quality Performance: Retrospective Data Analysis %A Beauvais,Bradley %A Kruse,Clemens Scott %A Fulton,Lawrence %A Shanmugam,Ramalingam %A Ramamonjiarivelo,Zo %A Brooks,Matthew %+ School of Health Administration, College of Health Professions, Texas State University, 601 University Dr, San Marcos, TX, 78666, United States, 1 2103554742, scottkruse@txstate.edu %K electronic health records %K medical informatics %K hospitals %K delivery of health care %K financial management %K quality of health care %K treatment outcome %D 2021 %7 14.4.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: Electronic health records (EHRs) are a central feature of care delivery in acute care hospitals; however, the financial and quality outcomes associated with system performance remain unclear. Objective: In this study, we aimed to evaluate the association between the top 3 EHR vendors and measures of hospital financial and quality performance. Methods: This study evaluated 2667 hospitals with Cerner, Epic, or Meditech as their primary EHR and considered their performance with regard to net income, Hospital Value–Based Purchasing Total Performance Score (TPS), and the unweighted subdomains of efficiency and cost reduction; clinical care; patient- and caregiver-centered experience; and patient safety. We hypothesized that there would be a difference among the 3 vendors for each measure. Results: None of the EHR systems were associated with a statistically significant financial relationship in our study. Epic was positively associated with TPS outcomes (R2=23.6%; β=.0159, SE 0.0079; P=.04) and higher patient perceptions of quality (R2=29.3%; β=.0292, SE 0.0099; P=.003) but was negatively associated with patient safety quality scores (R2=24.3%; β=−.0221, SE 0.0102; P=.03). Cerner and Epic were positively associated with improved efficiency (R2=31.9%; Cerner: β=.0330, SE 0.0135, P=.01; Epic: β=.0465, SE 0.0133, P<.001). Finally, all 3 vendors were associated with positive performance in the clinical care domain (Epic: β=.0388, SE 0.0122, P=.002; Cerner: β=.0283, SE 0.0124, P=.02; Meditech: β=.0273, SE 0.0123, P=.03) but with low explanatory power (R2=4.2%). Conclusions: The results of this study provide evidence of a difference in clinical outcome performance among the top 3 EHR vendors and may serve as supportive evidence for health care leaders to target future capital investments to improve health care delivery. %M 33851924 %R 10.2196/23961 %U https://www.jmir.org/2021/4/e23961 %U https://doi.org/10.2196/23961 %U http://www.ncbi.nlm.nih.gov/pubmed/33851924 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 3 %P e15443 %T Implementation of the Operating Room Black Box Research Program at the Ottawa Hospital Through Patient, Clinical, and Organizational Engagement: Case Study %A Boet,Sylvain %A Etherington,Cole %A Lam,Sandy %A Lê,Maxime %A Proulx,Laurie %A Britton,Meghan %A Kenna,Julie %A Przybylak-Brouillard,Antoine %A Grimshaw,Jeremy %A Grantcharov,Teodor %A Singh,Sukhbir %+ Department of Anesthesiology and Pain Medicine, University of Ottawa, 501 Smyth Road, Ottawa, ON, K1H 8L6, Canada, 1 613 798 5555 ext 78187, sboet@toh.ca %K patient safety %K implementation science %K quality improvement %K health personnel %K operating rooms %D 2021 %7 16.3.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: A large proportion of surgical patient harm is preventable; yet, our ability to systematically learn from these incidents and improve clinical practice remains limited. The Operating Room Black Box was developed to address the need for comprehensive assessments of clinical performance in the operating room. It captures synchronized audio, video, patient, and environmental clinical data in real time, which are subsequently analyzed by a combination of expert raters and software-based algorithms. Despite its significant potential to facilitate research and practice improvement, there are many potential implementation challenges at the institutional, clinician, and patient level. This paper summarizes our approach to implementation of the Operating Room Black Box at a large academic Canadian center. Objective: We aimed to contribute to the development of evidence-based best practices for implementing innovative technology in the operating room for direct observation of the clinical performance by using the case of the Operating Room Black Box. Specifically, we outline the systematic approach to the Operating Room Black Box implementation undertaken at our center. Methods: Our implementation approach included seeking support from hospital leadership; building frontline support and a team of champions among patients, nurses, anesthesiologists, and surgeons; accounting for stakeholder perceptions using theory-informed qualitative interviews; engaging patients; and documenting the implementation process, including barriers and facilitators, using the consolidated framework for implementation research. Results: During the 12-month implementation period, we conducted 23 stakeholder engagement activities with over 200 participants. We recruited 10 clinician champions representing nursing, anesthesia, and surgery. We formally interviewed 15 patients and 17 perioperative clinicians and identified key themes to include in an information campaign run as part of the implementation process. Two patient partners were engaged and advised on communications as well as grant and protocol development. Many anticipated and unanticipated challenges were encountered at all levels. Implementation was ultimately successful, with the Operating Room Black Box installed in August 2018, and data collection beginning shortly thereafter. Conclusions: This paper represents the first step toward evidence-guided implementation of technologies for direct observation of performance for research and quality improvement in surgery. With technology increasingly being used in health care settings, the health care community should aim to optimize implementation processes in the best interest of health care professionals and patients. %M 33724199 %R 10.2196/15443 %U https://www.jmir.org/2021/3/e15443 %U https://doi.org/10.2196/15443 %U http://www.ncbi.nlm.nih.gov/pubmed/33724199 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 9 %N 3 %P e23306 %T The Effect of Innovation Capabilities of Health Care Organizations on the Quality of Health Information Technology: Model Development With Cross-sectional Data %A Esdar,Moritz %A Hübner,Ursula %A Thye,Johannes %A Babitsch,Birgit %A Liebe,Jan-David %+ Health Informatics Research Group, Faculty of Business Management and Social Sciences, University of Applied Sciences Osnabrueck, Caprivistr 30A, Osnabrueck, 49076, Germany, 49 541 969 2012, u.huebner@hs-osnabrueck.de %K organizational innovation %K health information management %K organizational culture %K diffusion of innovation %K hospital information systems %K organizational change management %D 2021 %7 15.3.2021 %9 Original Paper %J JMIR Med Inform %G English %X Background: Large health organizations often struggle to build complex health information technology (HIT) solutions and are faced with ever-growing pressure to continuously innovate their information systems. Limited research has been conducted that explores the relationship between organizations’ innovative capabilities and HIT quality in the sense of achieving high-quality support for patient care processes. Objective: The aim of this study is to explain how core constructs of organizational innovation capabilities are linked to HIT quality based on a conceptual sociotechnical model on innovation and quality of HIT, called the IQHIT model, to help determine how better information provision in health organizations can be achieved. Methods: We designed a survey to assess various domains of HIT quality, innovation capabilities of health organizations, and context variables and administered it to hospital chief information officers across Austria, Germany, and Switzerland. Data from 232 hospitals were used to empirically fit the model using partial least squares structural equation modeling to reveal associations and mediating and moderating effects. Results: The resulting empirical IQHIT model reveals several associations between the analyzed constructs, which can be summarized in 2 main insights. First, it illustrates the linkage between the constructs measuring HIT quality by showing that the professionalism of information management explains the degree of HIT workflow support (R²=0.56), which in turn explains the perceived HIT quality (R²=0.53). Second, the model shows that HIT quality was positively influenced by innovation capabilities related to the top management team, the information technology department, and the organization at large. The assessment of the model’s statistical quality criteria indicated valid model specifications, including sufficient convergent and discriminant validity for measuring the latent constructs that underlie the measures of HIT quality and innovation capabilities. Conclusions: The proposed sociotechnical IQHIT model points to the key role of professional information management for HIT workflow support in patient care and perceived HIT quality from the viewpoint of hospital chief information officers. Furthermore, it highlights that organizational innovation capabilities, particularly with respect to the top management team, facilitate HIT quality and suggests that health organizations establish this link by applying professional information management practices. The model may serve to stimulate further scientific work in the field of HIT adoption and diffusion and to provide practical guidance to managers, policy makers, and educators on how to achieve better patient care using HIT. %M 33720029 %R 10.2196/23306 %U https://medinform.jmir.org/2021/3/e23306 %U https://doi.org/10.2196/23306 %U http://www.ncbi.nlm.nih.gov/pubmed/33720029 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 3 %P e14563 %T Investigating the Food and Drug Administration Biotherapeutics Review and Approval Process: Narrative Review %A Bonet Olivencia,Samuel %A Sasangohar,Farzan %+ Department of Industrial and Systems Engineering, Texas A&M University, 3131 TAMU, College Station, TX, 77843, United States, 1 9794582337, sasangohar@tamu.edu %K biotherapeutics %K drug approval %K drug review process %K model-based systems engineering %D 2021 %7 4.3.2021 %9 Review %J JMIR Form Res %G English %X Background: The development, review, and approval process of therapeutic biological products in the United States presents two primary challenges: time and cost. Advancing a biotherapeutic from concept to market may take an average of 12 years, with costs exceeding US $1 billion, and the product may still fail the US Food and Drug Administration (FDA) approval process. Despite the FDA’s practices to expedite the approval of new therapies, seeking FDA approval remains a long, costly, and risky process. Objective: The objective of this paper is to explore the factors and gaps related to the FDA review and approval process that contribute to process inefficiencies and complexities as well as proposed methods and solutions to address such gaps. This paper also aims to investigate the available modeling efforts for the FDA approval process of therapeutic biological products. Methods: A narrative review of literature was conducted to understand the scope of published knowledge about challenges, opportunities, and specific methods to address the factors and gaps related to the review and approval of new drugs, including therapeutic biological products. Relevant peer-reviewed journal articles, conference proceedings, book chapters, official reports from public policy professional centers, and official reports and guidelines from the FDA were reviewed. Results: Of the 23 articles identified in this narrative literature review, none modeled the current FDA review and approval process structure to address issues related to the robustness, reliability, and efficiency of its operations from an external point of view. Although several studies summarize the FDA approval process with clarity, in addition to bringing to light the problems and challenges faced by the regulatory agency, only a few attempts have been made to provide solutions for the problems and challenges identified. In addition, although several reform models have been discussed, these models lack the application of scientific methodologies and modeling techniques in understanding FDA as a complex sociotechnical system. Furthermore, tools and methods to assess the efficacy of the models before implementation are largely absent. Conclusions: The findings suggest the efficacy of model-based systems engineering approaches for identifying opportunities for significant improvements to the FDA review and approval process. Using this holistic approach will serve several investigative purposes: identify influential sources of variability that cause major delays, including individual, team, and organizational decision making; identify the human-system bottlenecks; identify areas of opportunity for design-driven improvements; study the effect of induced changes in the system; and assess the robustness of the structure of the FDA approval process in terms of enforcement and information symmetry. %M 33661119 %R 10.2196/14563 %U https://formative.jmir.org/2021/3/e14563 %U https://doi.org/10.2196/14563 %U http://www.ncbi.nlm.nih.gov/pubmed/33661119 %0 Journal Article %@ 2561-1011 %I JMIR Publications %V 5 %N 1 %P e22975 %T Digital Footprint of Academic Vascular Surgeons in the Southern United States on Physician Rating Websites: Cross-sectional Evaluation Study %A Yan,Qi %A Jensen,Katherine J %A Thomas,Rose %A Field,Alyssa R %A Jiang,Zheng %A Goei,Christian %A Davies,Mark G %+ Division of Vascular Surgery, Department of Surgery, UT Health San Antonio, 7703 Floyd Curl Dr, MC7741, San Antonio, TX, 78229, United States, 1 210 567 5715, DaviesM@uthscsa.edu %K internet %K patient satisfaction %K quality of care %K physician rating sites %K patient experience %K professional reviews %K social media %D 2021 %7 24.2.2021 %9 Original Paper %J JMIR Cardio %G English %X Background: The internet has become a popular platform for patients to obtain information and to review the health care providers they interact with. However, little is known about the digital footprint of vascular surgeons and their interactions with patients on social media. Objective: This study aims to understand the activity of academic vascular surgeons on physician rating websites. Methods: Information on attending vascular surgeons affiliated with vascular residency or with fellowships in the Southern Association for Vascular Surgery (SAVS) was collected from public sources. A listing of websites containing physician ratings was obtained via literature reviews and Google search. Open access websites with either qualitative or quantitative evaluations of vascular surgeons were included. Closed access websites were excluded. Ranking scores from each website were converted to a standard 5-point scale for comparison. Results: A total of 6238 quantitative and 967 qualitative reviews were written for 287 physicians (236 males, 82.2%) across 16 websites that met the inclusion criteria out of the 62 websites screened. The surgeons affiliated with the integrated vascular residency and vascular fellowship programs in SAVS had a median of 8 (IQR 7-10) profiles across 16 websites, with only 1 surgeon having no web presence in any of the websites. The median number of quantitative ratings for each physician was 17 (IQR 6-34, range 1-137) and the median number of narrative reviews was 3 (IQR 2-6, range 1-28). Vitals, WebMD, and Healthgrades were the only 3 websites where over a quarter of the physicians were rated, and those rated had more than 5 ratings on average. The median score for the quantitative reviews was 4.4 (IQR 4.0-4.9). Most narrative reviews (758/967, 78.4%) were positive, but 20.2% (195/967) were considered negative; only 1.4% (14/967) were considered equivocal. No statistical difference was found in the number of quantitative reviews or in the overall average score in the physician ratings between physicians with social media profiles and those without social media profiles (departmental social media profile: median 23 vs 15, respectively, P=.22; personal social media profile: median 19 vs 14, respectively, P=.08). Conclusions: The representation of vascular surgeons on physician rating websites is varied, with the majority of the vascular surgeons represented only in half of the physician rating websites The number of quantitative and qualitative reviews for academic vascular surgeons is low. No vascular surgeon responded to any of the reviews. The activity of vascular surgeons in this area of social media is low and reflects only a small digital footprint that patients can reach and review. %M 33625359 %R 10.2196/22975 %U https://cardio.jmir.org/2021/1/e22975 %U https://doi.org/10.2196/22975 %U http://www.ncbi.nlm.nih.gov/pubmed/33625359 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 9 %N 2 %P e25467 %T Culturally Competent Gender, Sex, and Sexual Orientation Information Practices and Electronic Health Records: Rapid Review %A Davison,Kelly %A Queen,Roz %A Lau,Francis %A Antonio,Marcy %+ University of Victoria, PO Box 1700 STN CSC, Victoria, BC, V8W 2Y2, Canada, 1 250 721 7211, kdaviso@uvic.ca %K sex and gender minorities %K gender studies %K information practices %K electronic health record %K health equity %K rapid review %K LGBTQ issues %D 2021 %7 11.2.2021 %9 Review %J JMIR Med Inform %G English %X Background: Outdated gender, sex, and sexual orientation (GSSO) information practices in health care contribute to health inequities for sexual and gender minorities (SGMs). Governments, statistics agencies, and health care organizations are developing and implementing modernized practices that support health equity for SGMs. Extending our work, we conducted a rapid review of grey literature to explore information practices that support quality health care for SGMs. Objective: The aim of this rapid review of grey literature was to elucidate modern GSSO information practices from leading agencies for adaptation, adoption, and application by health care providers and organizations seeking to modernize outdated GSSO information practices that contribute to health inequities among SGMs. Methods: We searched MEDLINE and Google from 2015 to 2020 with terms related to gender, sex, sexual orientation, and electronic health/medical records for English-language grey literature resources including government and nongovernment organization publications, whitepapers, data standards, toolkits, health care organization and health quality practice and policy guides, conference proceedings, unpublished academic work, and statistical papers. Peer-reviewed journal articles were excluded, as were resources irrelevant to information practices. We also screened the reference sections of included articles for additional resources, and canvassed a working group of international topic experts for additional relevant resources. Duplicates were eliminated. ATLAS.ti was used to support analysis. Themes and codes were developed through an iterative process of writing and discussion with the research team. Results: Twenty-six grey literature resources met the inclusion criteria. The overarching themes that emerged from the literature were the interrelated behaviors, attitudes, and policies that constitute SGM cultural competence as follows: shared language with unambiguous definitions of GSSO concepts; welcoming and inclusive care environments and affirming practices to reduce barriers to access; health care policy that supports competent health care; and adoption of modernized GSSO information practices and electronic health record design requirements that address invisibility in health data. Conclusions: Health equity for SGMs requires systemic change. Binary representation of sex and gender in electronic health records (EHRs) obfuscates natural and cultural diversity and, in the context of health care, places SGM patients at risk of clinical harm because it leads to clinical assumptions. Agencies and agents in health care need to be equipped with the knowledge and tools needed to cultivate modern attitudes, policies, and practices that enable health equity for SGMs. Adopting small but important changes in the language and terminology used in technical and social health care systems is essential for institutionalizing SGM competency. Modern GSSO information practices depend on and reinforce SGM competency in health care. %M 33455901 %R 10.2196/25467 %U http://medinform.jmir.org/2021/2/e25467/ %U https://doi.org/10.2196/25467 %U http://www.ncbi.nlm.nih.gov/pubmed/33455901 %0 Journal Article %@ 2561-1011 %I JMIR Publications %V 5 %N 1 %P e25074 %T Patient Perspectives With Telehealth Visits in Cardiology During COVID-19: Online Patient Survey Study %A Singh,Aniruddha %A Mountjoy,Natalie %A McElroy,Doug %A Mittal,Shilpi %A Al Hemyari,Bashar %A Coffey,Nicholas %A Miller,Kristen %A Gaines,Kenneth %+ Western Kentucky Heart and Lung Research Foundation, 421 US31W By-pass, Bowling Green, KY, 42101, United States, 1 2707820151, Aniruddha.Singh@uky.edu %K COVID-19 %K telehealth %K cardiology %K internet %K broadband %K patient satisfaction %K restriction %K survey %D 2021 %7 22.1.2021 %9 Original Paper %J JMIR Cardio %G English %X Background: The rise of COVID-19 and the issue of a mandatory stay-at-home order in March 2020 led to the use of a direct-to-consumer model for cardiology telehealth in Kentucky. Kentucky has poor health outcomes and limited broadband connectivity. Given these and other practice-specific constraints, the region serves as a unique context to explore the efficacy of telehealth in cardiology. Objective: This study aims to determine the limitations of telehealth accessibility, patient satisfaction with telehealth relative to in-person visits, and the perceived advantages and disadvantages to telehealth. Our intent was two-fold. First, we wanted to conduct a rapid postassessment of the mandated overhaul of the health care delivery system, focusing on a representative specialty field, and how it was affecting patients. Second, we intend to use our findings to make suggestions about the future application of a telehealth model in specialty fields such as cardiology. Methods: We constructed an online survey in Qualtrics following the Patient Assessment of Communication During Telemedicine, a patient self-report questionnaire that has been previously developed and validated. We invited all patients who had a visit scheduled during the COVID-19 telehealth-only time frame to participate. Questions included factors for declining telehealth, patient satisfaction ratings of telehealth and in-person visits, and perceived advantages and disadvantages associated with telehealth. We also used electronic medical records to collect no-show data for in-person versus telehealth visits to check for nonresponse bias. Results: A total of 224 respondents began our survey (11% of our sample of 2019 patients). Our recruitment rate was 86% (n=193) and our completion rate was 62% (n=120). The no-show rate for telehealth visits (345/2019, 17%) was nearly identical to the typical no-show rate for in-person appointments. Among the 32 respondents who declined a telehealth visit, 20 (63%) cited not being aware of their appointment as a primary factor, and 15 (47%) respondents cited their opinion that a telehealth appointment was not medically necessary as at least somewhat of a factor in their decision. Both in-person and telehealth were viewed favorably, but in-person was rated higher across all domains of patient satisfaction. The only significantly lower mean score for telehealth (3.7 vs 4.2, P=.007) was in the clinical competence domain. Reduced travel time, lower visit wait time, and cost savings were seen as big advantages. Poor internet connectivity was rated as at least somewhat of a factor by 33.0% (35/106) of respondents. Conclusions: This study takes advantage of the natural experiment provided by the COVID-19 pandemic to assess the efficacy of telehealth in cardiology. Patterns of satisfaction are consistent across modalities and show that telehealth appears to be a viable alternative to in-person appointments. However, we found evidence that scheduling of telehealth visits may be problematic and needs additional attention. Additionally, we include a note of caution that patient satisfaction with telehealth may be artificially inflated during COVID-19 due to external health concerns connected with in-person visits. %M 33385234 %R 10.2196/25074 %U http://cardio.jmir.org/2021/1/e25074/ %U https://doi.org/10.2196/25074 %U http://www.ncbi.nlm.nih.gov/pubmed/33385234 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 9 %N 1 %P e24164 %T Application of Robot Positioning for Cannulated Screw Internal Fixation in the Treatment of Femoral Neck Fracture: Retrospective Study %A Wan,Lei %A Zhang,Xiangyun %A Wu,Dalong %A Li,Zhihao %A Yuan,Dongtao %A Li,Junming %A Zhang,Shikui %A Yue,Long %A Zhang,Shao'an %+ Department of Osteology, The Second Affiliated Hospital of Luohe Medical College, 463 Haihe Road, Luohe, 462300, China, 86 13938012488, 13938012488@163.com %K percutaneous cannulated screw fixation %K robot positioning %K femoral neck fracture %K clinical efficacy %K prognosis %D 2021 %7 21.1.2021 %9 Original Paper %J JMIR Med Inform %G English %X Background: Femoral neck fracture is a common type of hip fracture. Conventional surgical treatment aims at fixing the fracture site with screws and then gradually promoting bone healing. A robot-assisted orthopedic surgery system is computer technology applied to surgical treatment. Objective: This study aimed to explore the therapeutic effect and prognostic value of percutaneous cannulated screw internal fixation using robot-assisted positioning in patients with femoral neck fractures. Methods: From July 2018 to September 2019, 42 cases of femoral neck fracture admitted to the Second Affiliated Hospital of Luohe Medical College were randomly and averagely divided into control and study groups. The patients in the control group were treated with conventional percutaneous cannulated screw internal fixation, while the patients in the study group were treated with robot-assisted percutaneous cannulated screw fixation during surgical treatment. We compared the treatment conditions and results of the operation between the 2 groups. The Harris score was used to evaluate the treatment efficacy. The state of fracture healing was followed up and compared between the 2 groups. Results: The duration of the operation was shorter, there was less fluoroscopy use, and there were fewer drilled holes in the study group than in the control group (all, P<.001). There was no statistical difference in the amount of intraoperative bleeding between the 2 groups (P=.33). The Harris score (P=.045) and number of excellent and good ratings (P=.01) were significantly higher in the study group than in the control group. The difference in the fracture healing rate between the 2 groups was not statistically significant (P=.23). The fracture healing duration of the study group was shorter than that of the control group (P=.001). Conclusions: The use of robotic positioning aids in the treatment of femoral neck fractures with percutaneous cannulated screw fixation can effectively improve the efficiency of surgery, shorten the duration of surgery, and reduce the radiation damage to patients. Meanwhile, it improves postoperative treatment and recovery rates of the patients and shortens the fracture healing time. %M 33475515 %R 10.2196/24164 %U http://medinform.jmir.org/2021/1/e24164/ %U https://doi.org/10.2196/24164 %U http://www.ncbi.nlm.nih.gov/pubmed/33475515 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 1 %P e20195 %T The Role of Health Technologies in Multicomponent Primary Care Interventions: Systematic Review %A Jimenez,Geronimo %A Matchar,David %A Koh,Choon Huat Gerald %A van der Kleij,Rianne %A Chavannes,Niels H %A Car,Josip %+ Centre for Population Health Sciences (CePHaS), Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, 11 Mandalay Road, Level 18, Clinical Sciences Building, Novena Campus, Singapore, 308232, 65 6904 7027, geronimo.jimenez@gmail.com %K digital health %K health system improvements %K health technologies %K primary care %K systematic review %D 2021 %7 11.1.2021 %9 Review %J J Med Internet Res %G English %X Background: Several countries around the world have implemented multicomponent interventions to enhance primary care, as a way of strengthening their health systems to cope with an aging chronically ill population and rising costs. Some of these efforts have included technology-based enhancements as one of the features to support the overall intervention, but their details and impacts have not been explored. Objective: This study aimed to identify the role of digital/health technologies within wider multifeature interventions that are aimed at enhancing primary care, and to describe their aims and stakeholders, types of technologies used, and potential impacts. Methods: A systematic review was performed following Cochrane guidelines. An electronic search, conducted on May 30, 2019, was supplemented with manual and grey literature searches in December 2019, to identify multicomponent interventions that included at least one technology-based enhancement. After title/abstract and full text screening, selected articles were assessed for quality based on their study design. A descriptive narrative synthesis was used for analysis and presentation of the results. Results: Of 37 articles, 14 (38%) described the inclusion of a technology-based innovation as part of their multicomponent interventions to enhance primary care. The most commonly identified technologies were the use of electronic health records, data monitoring technologies, and online portals with messaging platforms. The most common aim of these technologies was to improve continuity of care and comprehensiveness, which resulted in increased patient satisfaction, increased primary care visits compared to specialist visits, and the provision of more health prevention education and improved prescribing practices. Technologies seem also to increase costs and utilization for some parameters, such as increased consultation costs and increased number of drugs prescribed. Conclusions: Technologies and digital health have not played a major role within comprehensive innovation efforts aimed at enhancing primary care, reflecting that these technologies have not yet reached maturity or wider acceptance as a means for improving primary care. Stronger policy and financial support, and advocacy of key stakeholders are needed to encourage the introduction of efficient technological innovations, which are backed by evidence-based research, so that digital technologies can fulfill the promise of supporting strong sustainable primary care. %M 33427676 %R 10.2196/20195 %U http://www.jmir.org/2021/1/e20195/ %U https://doi.org/10.2196/20195 %U http://www.ncbi.nlm.nih.gov/pubmed/33427676 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 1 %P e21240 %T Differences in Mode Preferences, Response Rates, and Mode Effect Between Automated Email and Phone Survey Systems for Patients of Primary Care Practices: Cross-Sectional Study %A Johnston,Sharon %A Hogg,William %A Wong,Sabrina T %A Burge,Fred %A Peterson,Sandra %+ Department of Family Medicine, University of Ottawa, 43 Bruyere St, Ottawa, ON, K1N5C8, Canada, 1 613 562 6262 ext 2931, sjohnston@bruyere.org %K response rates %K primary care %K mixed-mode survey %D 2021 %7 11.1.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: A growing number of health care practices are adopting software systems that link with their existing electronic medical records to generate outgoing phone calls, emails, or text notifications to patients for appointment reminders or practice updates. While practices are adopting this software technology for service notifications to patients, its use for collection of patient-reported measures is still nascent. Objective: This study assessed the mode preferences, response rates, and mode effect for a practice-based automated patient survey using phone and email modalities to patients of primary care practices. Methods: This cross-sectional study analyzed responses and respondent demographics for a short, fully automated, telephone or email patient survey sent to individuals within 72 hours of a visit to their regular primary care practice. Each survey consisted of 5 questions drawn from a larger study’s patient survey that all respondents completed in the waiting room at the time of their visit. Automated patient survey responses were linked to self-reported sociodemographic information provided on the waiting room survey including age, sex, reported income, and health status. Results: A total of 871 patients from 87 primary care practices in British Columbia, Ontario, and Nova Scotia, Canada, agreed to the automated patient survey and 470 patients (45.2%) completed all 5 questions on the automated survey. Email administration of the follow-up survey was preferred over phone-based administration, except among patients aged 75 years and older (P<.001). Overall, response rates for those who selected an emailed survey (369/606, 60.9%) were higher (P<.001) than those who selected the phone survey (101/265, 38.1%). This held true irrespective of age, sex, or chronic disease status of individuals. Response rates were also higher for email (range 57.4% [58/101] to 66.3% [108/163]) compared with phone surveys (range 36% [23/64] to 43% [10/23]) for all income groups except the lowest income quintile, which had similar response rates (email: 29/63, 46%; phone: 23/50, 46%) for phone and email modes. We observed moderate (range 64.6% [62/96] to 78.8% [282/358]) agreement between waiting room survey responses and those obtained in the follow-up automated survey. However, overall agreement in responses was poor (range 45.3% [43/95] to 46.2% [43/93]) for 2 questions relating to care coordination. Conclusions: An automated practice-based patient experience survey achieved significantly different response rates between phone and email and increased response rates for email as income group rose. Potential mode effects for the different survey modalities may limit multimodal survey approaches. An automated minimal burden patient survey could facilitate the integration of patient-reported outcomes into care planning and service organization, supporting the move of our primary care practices toward a more responsive, patient-centered, continual learning system. However, practices must be attentive to furthering inequities in health care by underrepresenting the experience of certain groups in decision making based on the reach of different survey modes. %M 33427675 %R 10.2196/21240 %U https://www.jmir.org/2021/1/e21240 %U https://doi.org/10.2196/21240 %U http://www.ncbi.nlm.nih.gov/pubmed/33427675 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 1 %P e17655 %T How the Use of a Patient-Accessible Health Record Contributes to Patient-Centered Care: Scoping Review %A Benjamins,Janine %A Haveman-Nies,Annemien %A Gunnink,Marian %A Goudkuil,Annemieke %A de Vet,Emely %+ Icare JGZ, Blankenstein 550, Meppel, 7943 PH, Netherlands, 31 612329494, j.benjamins@cjgnoordveluwe.nl %K personal health records %K patient portals %K patient-centered care %K patient-accessible records %D 2021 %7 11.1.2021 %9 Review %J J Med Internet Res %G English %X Background: Worldwide, patient-centered care is becoming a widely used concept in medical practice, getting more and more attention because of its proven ability to improve quality of care and reduce costs. Although several studies show that patient-accessible electronic health records (PAEHRs) influence certain aspects of patient-centered care, the possible contribution of PAEHR implementation to patient-centered care as a comprehensive concept has not, to our knowledge, been structurally evaluated to date. Objective: The objective of this study is to review whether and how the use of PAEHRs contributes to patient-centered care both in general and among specific population groups. Methods: We followed PRISMA Extension for Scoping Reviews reporting guidelines. We identified literature in 5 databases, using the terms “patient-accessible medical records,” “patient experiences,” and “professional experiences” as key concepts. A total of 49 articles were included and analyzed with a charting code list containing 10 elements of patient-centered care. Results: Studies were diverse in design, country of origin, functionalities of the investigated PAEHR, and target population. Participants in all studies were adults. Most studies reported positive influence of PAEHR use on patient-centered care; patient accessible health records were appreciated for their opportunity to empower patients, inform patients about their health, and involve patients in their own care. There were mixed results for the extent to which PAEHRs affected the relation between patients and clinicians. Professionals and patients in mental health care held opposing views concerning the impact of transparency, where professionals appeared more worried about potential negative impact of PAEHRs on the patient-clinician relationship. Their worries seemed to be influenced by a reluctant attitude toward patient-centered care. Disadvantaged groups appeared to have less access to and make less use of patient-accessible records than the average population but experienced more benefits than the average population when they actually used PAEHRs. Conclusions: The review indicates that PAEHRs bear the potential to positively contribute to patient-centered care. However, concerns from professionals about the impact of transparency on the patient-clinician relationship as well as the importance of a patient-centered attitude need to be addressed. Potentially significant benefits for disadvantaged groups will be achieved only through easily accessible and user-friendly PAEHRs. %M 33427683 %R 10.2196/17655 %U http://www.jmir.org/2021/1/e17655/ %U https://doi.org/10.2196/17655 %U http://www.ncbi.nlm.nih.gov/pubmed/33427683 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 8 %N 12 %P e22649 %T Detecting Miscoded Diabetes Diagnosis Codes in Electronic Health Records for Quality Improvement: Temporal Deep Learning Approach %A Rashidian,Sina %A Abell-Hart,Kayley %A Hajagos,Janos %A Moffitt,Richard %A Lingam,Veena %A Garcia,Victor %A Tsai,Chao-Wei %A Wang,Fusheng %A Dong,Xinyu %A Sun,Siao %A Deng,Jianyuan %A Gupta,Rajarsi %A Miller,Joshua %A Saltz,Joel %A Saltz,Mary %+ Department of Computer Science, Stony Brook University, 2212 Computer Science, Stony Brook, NY, 11794, United States, 1 631 632 8470, srashidian@cs.stonybrook.edu %K electronic health records %K diabetes %K deep learning %D 2020 %7 17.12.2020 %9 Original Paper %J JMIR Med Inform %G English %X Background: Diabetes affects more than 30 million patients across the United States. With such a large disease burden, even a small error in classification can be significant. Currently billing codes, assigned at the time of a medical encounter, are the “gold standard” reflecting the actual diseases present in an individual, and thus in aggregate reflect disease prevalence in the population. These codes are generated by highly trained coders and by health care providers but are not always accurate. Objective: This work provides a scalable deep learning methodology to more accurately classify individuals with diabetes across multiple health care systems. Methods: We leveraged a long short-term memory-dense neural network (LSTM-DNN) model to identify patients with or without diabetes using data from 5 acute care facilities with 187,187 patients and 275,407 encounters, incorporating data elements including laboratory test results, diagnostic/procedure codes, medications, demographic data, and admission information. Furthermore, a blinded physician panel reviewed discordant cases, providing an estimate of the total impact on the population. Results: When predicting the documented diagnosis of diabetes, our model achieved an 84% F1 score, 96% area under the curve–receiver operating characteristic curve, and 91% average precision on a heterogeneous data set from 5 distinct health facilities. However, in 81% of cases where the model disagreed with the documented phenotype, a blinded physician panel agreed with the model. Taken together, this suggests that 4.3% of our studied population have either missing or improper diabetes diagnosis. Conclusions: This study demonstrates that deep learning methods can improve clinical phenotyping even when patient data are noisy, sparse, and heterogeneous. %M 33331828 %R 10.2196/22649 %U http://medinform.jmir.org/2020/12/e22649/ %U https://doi.org/10.2196/22649 %U http://www.ncbi.nlm.nih.gov/pubmed/33331828 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 8 %N 12 %P e18716 %T Effects of Erythropoietin Payment Policy on Cardiovascular Outcomes of Peritoneal Dialysis Patients: Observational Study %A Hou,Ying-Hui %A Yang,Feng-Jung %A Lai,I-Chun %A Lin,Shih-Pi %A Wan,Thomas TH %A Chang,Ray-E %+ Institute of Health Policy and Management, College of Public Health, National Taiwan University, 17 Xu-Zhou Road, Room 639, Taipei, 100, Taiwan, 886 2 3366 8069, rchang@ntu.edu.tw %K erythropoietin %K cardiovascular disease %K peritoneal dialysis %K diabetes mellitus %D 2020 %7 17.12.2020 %9 Original Paper %J JMIR Med Inform %G English %X Background: The change in the reimbursement policy of erythropoietin administration to patients receiving peritoneal dialysis by the Taiwan National Health Insurance (NHI) system provided a natural experimental venue to examine whether cardiovascular risk differs when maintaining the hematocrit (Hct) level below or above 30%. Objective: The aim of this study was to analyze the impact of loosening the erythropoietin payment criteria for peritoneal dialysis patients on their cardiovascular outcomes. Methods: Two cohorts of incident peritoneal dialysis patients were identified according to the time before and after relaxation of the NHI’s erythropoietin payment criteria, designated cohort 1 (n=1759) and cohort 2 (n=2981), respectively. The cohorts were matched according to propensity scores (1754 patients in each cohort) and then followed up for cardiovascular events, which were analyzed with Cox regressions. Results: For the composite cardiovascular endpoint, patients in cohort 2 had a significantly lower risk than those in cohort 1. However, subgroup analysis showed that this risk reduction was observed only in patients with diabetes. Conclusions: After loosening erythropoietin payment criteria, reduced cardiovascular risks were observed, particularly for patients with diabetes. These results indicate that it is crucial to maintain an Hct level above 30% to reduce the cardiovascular risk in patients with diabetes undergoing peritoneal dialysis. %M 33331829 %R 10.2196/18716 %U http://medinform.jmir.org/2020/12/e18716/ %U https://doi.org/10.2196/18716 %U http://www.ncbi.nlm.nih.gov/pubmed/33331829 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 12 %P e16691 %T The Influence of Doctors’ Online Reputation on the Sharing of Outpatient Experiences: Empirical Study %A Wang,Yang %A Wu,Hong %A Lei,Xueqin %A Shen,Jingxuan %A Feng,Zhanchun %+ School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Qiaokou District, Hubei Province, Wuhan, 430030, China, 86 13277942186, wuhong634214924@163.com %K online health communities %K individual reputation %K doctor reputation %K patient feedback %K organizational reputation %K disease severity %D 2020 %7 11.12.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: The internet enables consumers to evaluate products before purchase based on feedback submitted by like-minded individuals. Displaying reviews allows customers to assess comparable experiences and encourages trust, increased sales, and brand positivity. Customers use reviews to inform decision making, whereas organizations use reviews to predict future sales. Prior studies have focused on manufactured products, with little attention being paid to health care services. In particular, whether patients prefer to use websites to discuss doctors’ reputation has so far remained unanswered. Objective: This study aims to investigate how patient propensity to post treatment experiences changes based on doctors’ online reputation (medical quality and service attitude) in delivering outpatient care services. Further, this study examines the moderating effects of hospitals’ (organizational) online reputation and disease severity. Methods: Fractional logistic regression was conducted on data collected from 7183 active doctors in a Chinese online health community to obtain empirical results. Results: Our findings show that patients prefer to share treatment experiences for doctors who have a higher medical quality and service attitude (βservice attitude=.233; P<.001 and βmedical quality=.052; P<.001) and who work in hospitals with a higher online reputation (β=.001; P<.001). Patients are more likely to share experiences of doctors who treat less severe diseases, as opposed to those treating severe diseases (β=−.004; P=.009). In addition, hospitals’ online reputation positively (negatively) moderates the relationship between medical quality (service attitude) and patient propensity to post treatment experiences, whereas the moderating effects of disease severity on doctors’ online reputation are negative. Conclusions: Our research contributes to both theory and practice by extending the current understanding of the impact of individual reputation on consumer behavior. We investigate the moderating effects of organizational reputation and consumer characteristics in online health communities. %M 33306028 %R 10.2196/16691 %U http://www.jmir.org/2020/12/e16691/ %U https://doi.org/10.2196/16691 %U http://www.ncbi.nlm.nih.gov/pubmed/33306028 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 12 %P e18046 %T Capitated Telehealth Coaching Hospital Readmission Service in Australia: Pragmatic Controlled Evaluation %A Martin,Carmel %A Hinkley,Narelle %A Stockman,Keith %A Campbell,Donald %+ Monash Health Faculty of Medicine, Nursing and Health Sciences, Monash University, Monash Medicine (Level 5), 35 Rainforest Walk, Clayton, VIC 3800, Australia, 61 3 9905 5035, carmelmarymartin@gmail.com %K telehealth %K funding model %K evaluation %K health services research %K potentially preventable hospitalizations, medical informatics %D 2020 %7 1.12.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: MonashWatch is a telehealth public hospital outreach pilot service as a component of the Government of Victoria’s statewide redesign initiative called HealthLinks: Chronic Care. Rather than only paying for hospitalizations, projected funding is released earlier to hospitals to allow them to reduce hospitalization costs. MonashWatch introduced a web-based app, Patient Journey Record System, to assess the risk of the journeys of a cohort of patients identified as frequent admitters. Telecare guides call patients using the Patient Journey Record System to flag potential deterioration. Health coaches (nursing and allied health staff) triage risk and adapt care for individuals. Objective: The aim was a pragmatic controlled evaluation of the impact of MonashWatch on the primary outcome of bed days for acute nonsurgical admissions in the intention-to-treat group versus the usual care group. The secondary outcome was hospital admission rates. The net promoter score was used to gauge satisfaction. Methods: Patients were recruited into an intention-to-treat group, which included active telehealth and declined/lost/died groups, versus a systematically sampled (4:1) usual care group. A rolling sample of 250-300 active telehealth patients was maintained from December 23, 2016 to June 23, 2019. The outcome—mean bed days in intervention versus control—was adjusted using analysis of covariance for age, gender, admission type, and effective days active in MonashWatch. Time-series analysis tested for trends in change patterns. Results: MonashWatch recruited 1373 suitable patients who were allocated into the groups: usual care (n=293) and intention-to-treat (n=1080; active telehealth: 471/1080, 43.6%; declined: 485, 44.9%; lost to follow-up: 178 /1080, 10.7%; died: 8/1080, 0.7%). Admission frequency of intention-to-treat compared to that of the usual care group did not significantly improve (P=.05), with a small number of very frequent admitters in the intention-to-treat group. Age, MonashWatch effective days active, and treatment group independently predicted bed days. The analysis of covariance demonstrated a reduction in bed days of 1.14 (P<.001) in the intention-to-treat group compared with that in the usual care group, with 1236 bed days estimated savings. Both groups demonstrated regression-to-the-mean. The downward trend in improved bed days was significantly greater (P<.001) in the intention-to-treat group (Sen slope –406) than in the usual care group (Sen slope –104). The net promoter score was 95% in the active telehealth group compared with typical hospital scores of 77%. Conclusions: Clinically and statistically meaningful reductions in acute hospital bed days in the intention-to-treat group when compared to that of the usual care group were demonstrated (P<.001), although admission frequency was unchanged with more short stay admissions in the intention-to-treat group. Nonrandomized control selection was a limitation. Nonetheless, MonashWatch was successful in the context of the HealthLinks: Chronic Care capitation initiative and is expanding. %M 33258781 %R 10.2196/18046 %U https://www.jmir.org/2020/12/e18046 %U https://doi.org/10.2196/18046 %U http://www.ncbi.nlm.nih.gov/pubmed/33258781 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 12 %P e22765 %T Comparing Precision Machine Learning With Consumer, Quality, and Volume Metrics for Ranking Orthopedic Surgery Hospitals: Retrospective Study %A Goyal,Dev %A Guttag,John %A Syed,Zeeshan %A Mehta,Rudra %A Elahi,Zahoor %A Saeed,Mohammed %+ Department of Internal Medicine, University of Michigan, 1500 East Medical Center Drive, Ann Arbor, MI, 48109, United States, 1 6176421280, msaeed@umich.edu %K machine learning %K hospital ratings %K precision delivery %K hospital %K surgery %K outcome %K perioperative %K internet %K reputation %K machine learning %D 2020 %7 1.12.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Patients’ choices of providers when undergoing elective surgeries significantly impact both perioperative outcomes and costs. There exist a variety of approaches that are available to patients for evaluating between different hospital choices. Objective: This paper aims to compare differences in outcomes and costs between hospitals ranked using popular internet-based consumer ratings, quality stars, reputation rankings, average volumes, average outcomes, and precision machine learning–based rankings for hospital settings performing hip replacements in a large metropolitan area. Methods: Retrospective data from 4192 hip replacement surgeries among Medicare beneficiaries in 2018 in a the Chicago metropolitan area were analyzed for variations in outcomes (90-day postprocedure hospitalizations and emergency department visits) and costs (90-day total cost of care) between hospitals ranked through multiple approaches: internet-based consumer ratings, quality stars, reputation rankings, average yearly surgical volume, average outcome rates, and machine learning–based rankings. The average rates of outcomes and costs were compared between the patients who underwent surgery at a hospital using each ranking approach in unadjusted and propensity-based adjusted comparisons. Results: Only a minority of patients (1159/4192, 27.6% to 2078/4192, 49.6%) were found to be matched to higher-ranked hospitals for each of the different approaches. Of the approaches considered, hip replacements at hospitals that were more highly ranked by consumer ratings, quality stars, and machine learning were all consistently associated with improvements in outcomes and costs in both adjusted and unadjusted analyses. The improvement was greatest across all metrics and analyses for machine learning–based rankings. Conclusions: There may be a substantive opportunity to increase the number of patients matched to appropriate hospitals across a broad variety of ranking approaches. Elective hip replacement surgeries performed at hospitals where patients were matched based on patient-specific machine learning were associated with better outcomes and lower total costs of care. %M 33258459 %R 10.2196/22765 %U https://www.jmir.org/2020/12/e22765 %U https://doi.org/10.2196/22765 %U http://www.ncbi.nlm.nih.gov/pubmed/33258459 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 8 %N 11 %P e23626 %T Parental Experiences of the Pediatric Day Surgery Pathway and the Needs for a Digital Gaming Solution: Qualitative Study %A Rantala,Arja %A Jansson,Miia M %A Helve,Otto %A Lahdenne,Pekka %A Pikkarainen,Minna %A Pölkki,Tarja %+ Research Group of Medical Imaging, Physics and Technology, Research Unit of Nursing Science and Health Management, Faculty of Medicine, University of Oulu, Pentti Kaiteran katu 1, Oulu, FI-90014, Finland, 358 504340424, arja.rantala@oulu.fi %K anxiety %K children %K day surgery %K delivery of health care %K digital solution %K gamification %K nursing %K pain %K qualitative study %K technology %D 2020 %7 13.11.2020 %9 Original Paper %J JMIR Med Inform %G English %X Background: The parents of hospitalized children are often dissatisfied with waiting times, fasting, discharge criteria, postoperative pain relief, and postoperative guidance. Parents’ experiences help care providers to provide effective, family-centered care that responds to parents’ needs throughout the day surgery pathway. Objective: The objective of our study was to describe parental experiences of the pediatric day surgery pathway and the needs for a digital gaming solution in order to facilitate the digitalization of these pathways. Methods: This was a descriptive qualitative study. The participants (N=31) were parents whose children were admitted to the hospital for the day surgical treatments or magnetic resonance imaging. The data were collected through an unstructured, open-ended questionnaire; an inductive content analysis was conducted to analyze the qualitative data. Reporting of the study findings adheres to the Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist. Results: Parental experiences of the children’s day surgery pathway included 3 main categories: (1) needs for parental guidance, (2) needs for support, and (3) child involved in his or her own pathway (eg, consideration of an individual child and preparation of child for treatment). The needs for a digital gaming solution were identified as 1 main category—the digital gaming solution for children and families to support care. This main category included 3 upper categories: (1) preparing children and families for the day surgery via the solution, (2) gamification in the solution, and (3) connecting people through the solution. Conclusions: Parents need guidance and support for their children’s day surgery care pathways. A digital gaming solution may be a relevant tool to support communication and to provide information on day surgeries. Families are ready for and are open to digital gaming solutions that provide support and guidance and engage children in the day surgery pathways. %M 33185556 %R 10.2196/23626 %U http://medinform.jmir.org/2020/11/e23626/ %U https://doi.org/10.2196/23626 %U http://www.ncbi.nlm.nih.gov/pubmed/33185556 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 11 %P e23299 %T Role of Technology in Self-Assessment and Feedback Among Hospitalist Physicians: Semistructured Interviews and Thematic Analysis %A Yin,Andrew Lukas %A Gheissari,Pargol %A Lin,Inna Wanyin %A Sobolev,Michael %A Pollak,John P %A Cole,Curtis %A Estrin,Deborah %+ Medical College, Weill Cornell Medicine, 1300 York Avenue, New York, NY, , United States, 1 212 746 5454, aly2011@med.cornell.edu %K feedback %K self-assessment %K self-learning %K hospitalist %K electronic medical record %K digital health %K assessment %K learning %D 2020 %7 3.11.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Lifelong learning is embedded in the culture of medicine, but there are limited tools currently available for many clinicians, including hospitalists, to help improve their own practice. Although there are requirements for continuing medical education, resources for learning new clinical guidelines, and developing fields aimed at facilitating peer-to-peer feedback, there is a gap in the availability of tools that enable clinicians to learn based on their own patients and clinical decisions. Objective: The aim of this study was to explore the technologies or modifications to existing systems that could be used to benefit hospitalist physicians in pursuing self-assessment and improvement by understanding physicians’ current practices and their reactions to proposed possibilities. Methods: Semistructured interviews were conducted in two separate stages with analysis performed after each stage. In the first stage, interviews (N=12) were conducted to understand the ways in which hospitalist physicians are currently gathering feedback and assessing their practice. A thematic analysis of these interviews informed the prototype used to elicit responses in the second stage. Results: Clinicians actively look for feedback that they can apply to their practice, with the majority of the feedback obtained through self-assessment. The following three themes surrounding this aspect were identified in the first round of semistructured interviews: collaboration, self-reliance, and uncertainty, each with three related subthemes. Using a wireframe, the second round of interviews led to identifying the features that are currently challenging to use or could be made available with technology. Conclusions: Based on each theme and subtheme, we provide targeted recommendations for use by relevant stakeholders such as institutions, clinicians, and technologists. Most hospitalist self-assessments occur on a rolling basis, specifically using data in electronic medical records as their primary source. Specific objective data points or subjective patient relationships lead clinicians to review their patient cases and to assess their own performance. However, current systems are not built for these analyses or for clinicians to perform self-assessment, making this a burdensome and incomplete process. Building a platform that focuses on providing and curating the information used for self-assessment could help physicians make more accurately informed changes to their own clinical practice and decision-making. %M 33141098 %R 10.2196/23299 %U http://www.jmir.org/2020/11/e23299/ %U https://doi.org/10.2196/23299 %U http://www.ncbi.nlm.nih.gov/pubmed/33141098 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 10 %P e17595 %T Recommendations From the Twitter Hashtag #DoctorsAreDickheads: Qualitative Analysis %A Sharma,Anjana Estelle %A Mann,Ziva %A Cherian,Roy %A Del Rosario,Jan Bing %A Yang,Janine %A Sarkar,Urmimala %+ Department of Family & Community Medicine, University of California San Francisco, 995 Potrero Ave, Ward 83, San Francisco, CA, 94110, United States, 1 6179454776, anjana.sharma@ucsf.edu %K social media %K patient engagement %K Twitter messaging %K missed diagnosis %K internet %K physician patient relationship %D 2020 %7 28.10.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: The social media site Twitter has 145 million daily active users worldwide and has become a popular forum for users to communicate their health care concerns and experiences as patients. In the fall of 2018, a hashtag titled #DoctorsAreDickheads emerged, with almost 40,000 posts calling attention to health care experiences. Objective: This study aims to identify common health care conditions and conceptual themes represented within the phenomenon of this viral Twitter hashtag. Methods: We analyzed a random sample of 5.67% (500/8818) available tweets for qualitative analysis between October 15 and December 31, 2018, when the hashtag was the most active. Team coders reviewed the same 20.0% (100/500) tweets and the remainder individually. We abstracted the user’s health care role and clinical conditions from the tweet and user profile, and used phenomenological content analysis to identify prevalent conceptual themes through sequential open coding, memoing, and discussion of concepts until an agreement was reached. Results: Our final sample comprised 491 tweets and unique Twitter users. Of this sample, 50.5% (248/491) were from patients or patient advocates, 9.6% (47/491) from health care professionals, 4.3% (21/491) from caregivers, 3.7% (18/491) from academics or researchers, 1.0% (5/491) from journalists or media, and 31.6% (155/491) from non–health care individuals or other. The most commonly mentioned clinical conditions were chronic pain, mental health, and musculoskeletal conditions (mainly Ehlers-Danlos syndrome). We identified 3 major themes: disbelief in patients’ experience and knowledge that contributes to medical errors and harm, the power inequity between patients and providers, and metacommentary on the meaning and impact of the #DoctorsAreDickheads hashtag. Conclusions: People publicly disclose personal and often troubling health care experiences on Twitter. This adds new accountability for the patient-provider interaction, highlights how harmful communication affects diagnostic safety, and shapes the public’s viewpoint of how clinicians behave. Hashtags such as this offer valuable opportunities to learn from patient experiences. Recommendations include developing best practices for providers to improve communication, supporting patients through challenging diagnoses, and promoting patient engagement. %M 33112246 %R 10.2196/17595 %U http://www.jmir.org/2020/10/e17595/ %U https://doi.org/10.2196/17595 %U http://www.ncbi.nlm.nih.gov/pubmed/33112246 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 10 %P e21057 %T Authors’ Reply to: Is a Ratio Scale Assumption for Physician Ratings Justified? Comment on “What Patients Value in Physicians: Analyzing Drivers of Patient Satisfaction Using Physician-Rating Website Data” %A Bidmon,Sonja %A Elshiewy,Ossama %A Terlutter,Ralf %A Boztug,Yasemin %+ Department of Marketing and International Management, Alpen-Adria-Universitaet Klagenfurt, Universitaetsstrasse 65-67, Klagenfurt am Woerthersee, 9020, Austria, 43 463 2700 4048, sonja.bidmon@aau.at %K online physician ratings %K patient satisfaction %K multiattribute models %K health care management %D 2020 %7 26.10.2020 %9 Letter to the Editor %J J Med Internet Res %G English %X %M 33104006 %R 10.2196/21057 %U https://www.jmir.org/2020/10/e21057 %U https://doi.org/10.2196/21057 %U http://www.ncbi.nlm.nih.gov/pubmed/33104006 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 10 %P e18289 %T Is a Ratio Scale Assumption for Physician Ratings Justified? Comment on “What Patients Value in Physicians: Analyzing Drivers of Patient Satisfaction Using Physician-Rating Website Data” %A Konerding,Uwe %+ Trimberg Research Academy, University of Bamberg, An der Weberei 5, Bamberg, D-96045, Germany, 49 951 863 3098, uwe.konerding@uni-bamberg.de %K patient satisfaction %K modeling %K method %K scale level %K measurement theory %D 2020 %7 26.10.2020 %9 Letter to the Editor %J J Med Internet Res %G English %X %M 33104009 %R 10.2196/18289 %U http://www.jmir.org/2020/10/e18289/ %U https://doi.org/10.2196/18289 %U http://www.ncbi.nlm.nih.gov/pubmed/33104009 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 9 %P e19198 %T Client Satisfaction and Experience With Telepsychiatry: Development and Validation of a Survey Using Clinical Quality Domains %A Serhal,Eva %A Kirvan,Anne %A Sanches,Marcos %A Crawford,Allison %+ Virtual Mental Health and Outreach, Centre for Addiction and Mental Health, 825-250 College St, Toronto, ON, M5T1R8, Canada, 1 4165358501 ext 30318, allison.crawford@utoronto.ca %K telemedicine %K psychiatry %K mental health %K patient satisfaction %K quality of health care %D 2020 %7 29.9.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Telepsychiatry is an increasingly used model of mental health care that connects patients with psychiatrists at a distance via videoconference. Telepsychiatry is an effective clinical intervention that improves access to quality care in regions with limited resources or in clinical situations where in-person care is unavailable. Objective: This study aims to develop a validated survey tool to measure patient experience and satisfaction with telepsychiatry based on the quality of care domains. This study also seeks to understand which health service outcomes were most strongly correlated with overall satisfaction in the context of telepsychiatry. Methods: The survey created in this study was developed and validated with a panel of subject matter and process experts and was piloted with 274 patients who received clinical consultations through the TeleMental Health Program at the Centre for Addiction and Mental Health. Factor analysis was used to determine correlations between questions and quality of care domains and was also used to assess model fit. Results: The study provides a validated survey to measure patient satisfaction and experience with telepsychiatry across 4 domains: access and timeliness, appropriateness, effectiveness, and safety. Both safety and access and timeliness were found to be statistically significant predictors of satisfaction in our sample. Conclusions: By situating patient satisfaction and experience within this framework, the survey facilitates patient data collection and interpretation through a clinical quality lens. %M 32755896 %R 10.2196/19198 %U http://www.jmir.org/2020/9/e19198/ %U https://doi.org/10.2196/19198 %U http://www.ncbi.nlm.nih.gov/pubmed/32755896 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 8 %N 9 %P e18147 %T How Specialist Aftercare Impacts Long-Term Readmission Risks in Elderly Patients With Metabolic, Cardiac, and Chronic Obstructive Pulmonary Diseases: Cohort Study Using Administrative Data %A Kaleta,Michaela %A Niederkrotenthaler,Thomas %A Kautzky-Willer,Alexandra %A Klimek,Peter %+ Section for Science of Complex Systems, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Spitalgasse 23, BT86, Vienna, 1090, Austria, 43 140160 ext 36255, peter.klimek@meduniwien.ac.at %K multimorbity %K patient-sharing networks %K network analysis %K gender medicine %K chronic disease %K morbidity %K elderly %K older adults %K cohort study %D 2020 %7 16.9.2020 %9 Original Paper %J JMIR Med Inform %G English %X Background: The health state of elderly patients is typically characterized by multiple co-occurring diseases requiring the involvement of several types of health care providers. Objective: We aimed to quantify the benefit for multimorbid patients from seeking specialist care in terms of long-term readmission risks. Methods: From an administrative database, we identified 225,238 elderly patients with 97 different diagnosis (ICD-10 codes) from hospital stays and contact with 13 medical specialties. For each diagnosis associated with the first hospital stay, we used multiple logistic regression analysis to quantify the sex-specific and age-adjusted long-term all-cause readmission risk (hospitalizations occurring between 3 months and 3 years after the first admission) and how specialist contact impacts these risks. Results: Men have a higher readmission risk than women (mean difference over all first diagnoses 1.9%, P<.001), but similar reduction in readmission risk after receiving specialist care. Specialist care can reduce readmission risk by almost 50%. We found the greatest reductions in risk when the first hospital stay was associated with diagnoses corresponding to complex chronic diseases such as acute myocardial infarction (57.6% reduction in readmission risk, SE 7.6% for men [m]; 55.9% reduction, SE 9.8% for women [w]), diabetic and other retinopathies (m: 62.3%, SE 8.0; w: 60.1%, SE 8.4%), chronic obstructive pulmonary disease (m: 63.9%, SE 7.8%; w: 58.1%, SE 7.5%), disorders of lipoprotein metabolism (m: 64.7%, SE 3.7%; w: 63.8%, SE 4.0%), and chronic ischemic heart diseases (m: 63.6%, SE 3.1%; w: 65.4%, SE 3.0%). Conclusions: Specialist care can greatly reduce long-term readmission risk for patients with chronic and multimorbid diseases. Further research is needed to identify the specific reasons for these findings and to understand the detected sex-specific differences. %M 32936077 %R 10.2196/18147 %U http://medinform.jmir.org/2020/9/e18147/ %U https://doi.org/10.2196/18147 %U http://www.ncbi.nlm.nih.gov/pubmed/32936077 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 9 %P e20786 %T Patient Satisfaction With Telemedicine During the COVID-19 Pandemic: Retrospective Cohort Study %A Ramaswamy,Ashwin %A Yu,Miko %A Drangsholt,Siri %A Ng,Eric %A Culligan,Patrick J %A Schlegel,Peter N %A Hu,Jim C %+ Department of Urology, Weill Cornell Medicine, 525 East 68th Street, New York, NY, 10065, United States, 1 646 962 9600, asr9066@nyp.org %K telemedicine %K medicine %K pandemics %K patient satisfaction %K remote consultation %K disruptive technology %K medical informatics %K health care delivery %K practice patterns %K physicians %K health policy %K health services research %K health care reform %K COVID-19 %D 2020 %7 9.9.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: New York City was the international epicenter of the COVID-19 pandemic. Health care providers responded by rapidly transitioning from in-person to video consultations. Telemedicine (ie, video visits) is a potentially disruptive innovation; however, little is known about patient satisfaction with this emerging alternative to the traditional clinical encounter. Objective: This study aimed to determine if patient satisfaction differs between video and in-person visits. Methods: In this retrospective observational cohort study, we analyzed 38,609 Press Ganey patient satisfaction survey outcomes from clinic encounters (620 video visits vs 37,989 in-person visits) at a single-institution, urban, quaternary academic medical center in New York City for patients aged 18 years, from April 1, 2019, to March 31, 2020. Time was categorized as pre–COVID-19 and COVID-19 (before vs after March 4, 2020). Wilcoxon-Mann-Whitney tests and multivariable linear regression were used for hypothesis testing and statistical modeling, respectively. Results: We experienced an 8729% increase in video visit utilization during the COVID-19 pandemic compared to the same period last year. Video visit Press Ganey scores were significantly higher than in-person visits (94.9% vs 92.5%; P<.001). In adjusted analyses, video visits (parameter estimate [PE] 2.18; 95% CI 1.20-3.16) and the COVID-19 period (PE 0.55; 95% CI 0.04-1.06) were associated with higher patient satisfaction. Younger age (PE –2.05; 95% CI –2.66 to –1.22), female gender (PE –0.73; 95% CI –0.96 to –0.50), and new visit type (PE –0.75; 95% CI –1.00 to –0.49) were associated with lower patient satisfaction. Conclusions: Patient satisfaction with video visits is high and is not a barrier toward a paradigm shift away from traditional in-person clinic visits. Future research comparing other clinic visit quality indicators is needed to guide and implement the widespread adoption of telemedicine. %M 32810841 %R 10.2196/20786 %U http://www.jmir.org/2020/9/e20786/ %U https://doi.org/10.2196/20786 %U http://www.ncbi.nlm.nih.gov/pubmed/32810841 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 9 %P e18787 %T Quality of Care Perceived by Older Patients and Caregivers in Integrated Care Pathways With Interviewing Assistance From a Social Robot: Noninferiority Randomized Controlled Trial %A Boumans,Roel %A van Meulen,Fokke %A van Aalst,William %A Albers,Joyce %A Janssen,Marèse %A Peters-Kop,Marieke %A Huisman - de Waal,Getty %A van de Poll,Alexandra %A Hindriks,Koen %A Neerincx,Mark %A Olde Rikkert,Marcel %+ Geriatric Department, Radboud University Medical Center, Reinier Postlaan 4, Nijmegen, 6525 GC, Netherlands, 31 0622372708, roel.boumans@radboudumc.nl %K integrated care pathway %K social robot %K quality of care %K noninferiority randomized controlled trial %D 2020 %7 9.9.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Society is facing a global shortage of 17 million health care workers, along with increasing health care demands from a growing number of older adults. Social robots are being considered as solutions to part of this problem. Objective: Our objective is to evaluate the quality of care perceived by patients and caregivers for an integrated care pathway in an outpatient clinic using a social robot for patient-reported outcome measure (PROM) interviews versus the currently used professional interviews. Methods: A multicenter, two-parallel-group, nonblinded, randomized controlled trial was used to test for noninferiority of the quality of care delivered through robot-assisted care. The randomization was performed using a computer-generated table. The setting consisted of two outpatient clinics, and the study took place from July to December 2019. Of 419 patients who visited the participating outpatient clinics, 110 older patients met the criteria for recruitment. Inclusion criteria were the ability to speak and read Dutch and being assisted by a participating health care professional. Exclusion criteria were serious hearing or vision problems, serious cognitive problems, and paranoia or similar psychiatric problems. The intervention consisted of a social robot conducting a 36-item PROM. As the main outcome measure, the customized Consumer Quality Index (CQI) was used, as reported by patients and caregivers for the outpatient pathway of care. Results: In total, 75 intermediately frail older patients were included in the study, randomly assigned to the intervention and control groups, and processed: 36 female (48%) and 39 male (52%); mean age 77.4 years (SD 7.3), range 60-91 years. There was no significant difference in the total patient CQI scores between the patients included in the robot-assisted care pathway (mean 9.27, SD 0.65, n=37) and those in the control group (mean 9.00, SD 0.70, n=38): P=.08, 95% CI –0.04 to 0.58. There was no significant difference in the total CQI scores between caregivers in the intervention group (mean 9.21, SD 0.76, n=30) and those in the control group (mean 9.09, SD 0.60, n=35): P=.47, 95% CI –0.21 to 0.46. No harm or unintended effects occurred. Conclusions: Geriatric patients and their informal caregivers valued robot-assisted and nonrobot-assisted care pathways equally. Trial Registration: ClinicalTrials.gov NCT03857789; https://clinicaltrials.gov/ct2/show/NCT03857789 %M 32902387 %R 10.2196/18787 %U http://www.jmir.org/2020/9/e18787/ %U https://doi.org/10.2196/18787 %U http://www.ncbi.nlm.nih.gov/pubmed/32902387 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 8 %N 9 %P e19774 %T Integrating and Evaluating the Data Quality and Utility of Smart Pump Information in Detecting Medication Administration Errors: Evaluation Study %A Ni,Yizhao %A Lingren,Todd %A Huth,Hannah %A Timmons,Kristen %A Melton,Krisin %A Kirkendall,Eric %+ Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, MLC 7024, Cincinnati, OH, 45229, United States, 1 5138034269, yizhao.ni@cchmc.org %K medication administration errors %K smart infusion pumps %K electronic health records %K concordance %D 2020 %7 2.9.2020 %9 Original Paper %J JMIR Med Inform %G English %X Background: At present, electronic health records (EHRs) are the central focus of clinical informatics given their role as the primary source of clinical data. Despite their granularity, the EHR data heavily rely on manual input and are prone to human errors. Many other sources of data exist in the clinical setting, including digital medical devices such as smart infusion pumps. When incorporated with prescribing data from EHRs, smart pump records (SPRs) are capable of shedding light on actions that take place during the medication use process. However, harmoniz-ing the 2 sources is hindered by multiple technical challenges, and the data quality and utility of SPRs have not been fully realized. Objective: This study aims to evaluate the quality and utility of SPRs incorporated with EHR data in detecting medication administration errors. Our overarching hypothesis is that SPRs would contribute unique information in the med-ication use process, enabling more comprehensive detection of discrepancies and potential errors in medication administration. Methods: We evaluated the medication use process of 9 high-risk medications for patients admitted to the neonatal inten-sive care unit during a 1-year period. An automated algorithm was developed to align SPRs with their medica-tion orders in the EHRs using patient ID, medication name, and timestamp. The aligned data were manually re-viewed by a clinical research coordinator and 2 pediatric physicians to identify discrepancies in medication ad-ministration. The data quality of SPRs was assessed with the proportion of information that was linked to valid EHR orders. To evaluate their utility, we compared the frequency and severity of discrepancies captured by the SPR and EHR data, respectively. A novel concordance assessment was also developed to understand the detec-tion power and capabilities of SPR and EHR data. Results: Approximately 70% of the SPRs contained valid patient IDs and medication names, making them feasible for data integration. After combining the 2 sources, the investigative team reviewed 2307 medication orders with 10,575 medication administration records (MARs) and 23,397 SPRs. A total of 321 MAR and 682 SPR dis-crepancies were identified, with vasopressors showing the highest discrepancy rates, followed by narcotics and total parenteral nutrition. Compared with EHR MARs, substantial dosing discrepancies were more commonly detectable using the SPRs. The concordance analysis showed little overlap between MAR and SPR discrepan-cies, with most discrepancies captured by the SPR data. Conclusions: We integrated smart infusion pump information with EHR data to analyze the most error-prone phases of the medication lifecycle. The findings suggested that SPRs could be a more reliable data source for medication error detection. Ultimately, it is imperative to integrate SPR information with EHR data to fully detect and mitigate medication administration errors in the clinical setting. %M 32876578 %R 10.2196/19774 %U https://medinform.jmir.org/2020/9/e19774 %U https://doi.org/10.2196/19774 %U http://www.ncbi.nlm.nih.gov/pubmed/32876578 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 8 %P e17022 %T Technological Capabilities to Assess Digital Excellence in Hospitals in High Performing Health Care Systems: International eDelphi Exercise %A Krasuska,Marta %A Williams,Robin %A Sheikh,Aziz %A Franklin,Bryony Dean %A Heeney,Catherine %A Lane,Wendy %A Mozaffar,Hajar %A Mason,Kathy %A Eason,Sally %A Hinder,Susan %A Dunscombe,Rachel %A Potts,Henry W W %A Cresswell,Kathrin %+ Usher Institute, University of Edinburgh, Old Medical School, Teviot Place, Edinburgh, EH8 9AG, United Kingdom, 44 131 651 7878, Kathrin.Cresswell@ed.ac.uk %K digital excellence %K digital maturity %K Delphi technique %K hospitals, eHealth %D 2020 %7 18.8.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Hospitals worldwide are developing ambitious digital transformation programs as part of broader efforts to create digitally advanced health care systems. However, there is as yet no consensus on how best to characterize and assess digital excellence in hospitals. Objective: Our aim was to develop an international agreement on a defined set of technological capabilities to assess digital excellence in hospitals. Methods: We conducted a two-stage international modified electronic Delphi (eDelphi) consensus-building exercise, which included a qualitative analysis of free-text responses. In total, 31 international health informatics experts participated, representing clinical, academic, public, and vendor organizations. Results: We identified 35 technological capabilities that indicate digital excellence in hospitals. These are divided into two categories: (a) capabilities within a hospital (n=20) and (b) capabilities enabling communication with other parts of the health and social care system, and with patients and carers (n=15). The analysis of free-text responses pointed to the importance of nontechnological aspects of digitally enabled change, including social and organizational factors. Examples included an institutional culture characterized by a willingness to transform established ways of working and openness to risk-taking. The availability of a range of skills within digitization teams, including technological, project management and business expertise, and availability of resources to support hospital staff, were also highlighted. Conclusions: We have identified a set of criteria for assessing digital excellence in hospitals. Our findings highlight the need to broaden the focus from technical functionalities to wider digital transformation capabilities. %M 32808938 %R 10.2196/17022 %U https://www.jmir.org/2020/8/e17022 %U https://doi.org/10.2196/17022 %U http://www.ncbi.nlm.nih.gov/pubmed/32808938 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 8 %N 8 %P e17283 %T Effects of Computerized Decision Support Systems on Practitioner Performance and Patient Outcomes: Systematic Review %A Kruse,Clemens Scott %A Ehrbar,Nolan %+ School of Health Administration, Texas State University, 601 University Dr, San Marcos, TX, , United States, 1 512 245 4462, scottkruse@txstate.edu %K CDSS %K performance %K outcomes %D 2020 %7 11.8.2020 %9 Review %J JMIR Med Inform %G English %X Background: Computerized decision support systems (CDSSs) are software programs that support the decision making of practitioners and other staff. Other reviews have analyzed the relationship between CDSSs, practitioner performance, and patient outcomes. These reviews reported positive practitioner performance in over half the articles analyzed, but very little information was found for patient outcomes. Objective: The purpose of this review was to analyze the relationship between CDSSs, practitioner performance, and patient medical outcomes. PubMed, CINAHL, Embase, Web of Science, and Cochrane databases were queried. Methods: Articles were chosen based on year published (last 10 years), high quality, peer-reviewed sources, and discussion of the relationship between the use of CDSS as an intervention and links to practitioner performance or patient outcomes. Reviewers used an Excel spreadsheet (Microsoft Corporation) to collect information on the relationship between CDSSs and practitioner performance or patient outcomes. Reviewers also collected observations of participants, intervention, comparison with control group, outcomes, and study design (PICOS) along with those showing implicit bias. Articles were analyzed by multiple reviewers following the Kruse protocol for systematic reviews. Data were organized into multiple tables for analysis and reporting. Results: Themes were identified for both practitioner performance (n=38) and medical outcomes (n=36). A total of 66% (25/38) of articles had occurrences of positive practitioner performance, 13% (5/38) found no difference in practitioner performance, and 21% (8/38) did not report or discuss practitioner performance. Zero articles reported negative practitioner performance. A total of 61% (22/36) of articles had occurrences of positive patient medical outcomes, 8% (3/36) found no statistically significant difference in medical outcomes between intervention and control groups, and 31% (11/36) did not report or discuss medical outcomes. Zero articles found negative patient medical outcomes attributed to using CDSSs. Conclusions: Results of this review are commensurate with previous reviews with similar objectives, but unlike these reviews we found a high level of reporting of positive effects on patient medical outcomes. %M 32780714 %R 10.2196/17283 %U http://medinform.jmir.org/2020/8/e17283/ %U https://doi.org/10.2196/17283 %U http://www.ncbi.nlm.nih.gov/pubmed/32780714 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 8 %P e17186 %T Communication Behavior Changes Between Patients With Diabetes and Healthcare Providers Over 9 Years: Retrospective Cohort Study %A Benis,Arriel %A Barak Barkan,Refael %A Sela,Tomer %A Harel,Nissim %+ Faculty of Technology Management, Holon Institute of Technology, Golomb St 52, POB 305, Holon, Israel, 972 3 5026892, arrielb@hit.ac.il %K population characteristics %K eHealth %K mHealth %K consumer health informatics %K delivery of health care %K machine learning %K clustering %K quality of health care %K point-of-care systems %K physician-patient relations %D 2020 %7 11.8.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Health organizations and patients interact over different communication channels and are harnessing digital communications for this purpose. Assisting health organizations to improve, adapt, and introduce new patient–health care practitioner communication channels (such as patient portals, mobile apps, and text messaging) enhances health care services access. Objective: This retrospective data study aims to assist health care administrators and policy makers to improve and personalize communication between patients and health care professionals by expanding the capabilities of current communication channels and introducing new ones. Our main hypothesis is that patient follow-up and clinical outcomes are influenced by their preferred communication channels with the health care organization. Methods: This study analyzes data stored in electronic medical records and logs documenting access to various communication channels between patients and a health organization (Clalit Health Services, Israel). Data were collected between 2008 and 2016 from records of 311,168 patients diagnosed with diabetes, aged 21 years and over, members of Clalit at least since 2007, and still alive in 2016. The analysis consisted of characterizing the use profiles of communication channels over time and used clustering for discretization purposes and patient profile building and then a hierarchical clustering and heatmaps to visualize the different communication profiles. Results: A total of 13 profiles of patients were identified and characterized. We have shown how the communication channels provided by the health organization influence the communication behavior of patients. We observed how different patients respond differently to technological means of communication and change or don’t change their communication patterns with the health care organization based on the communication channels available to them. Conclusions: Identifying the channels of communication within the health organization and which are preferred by each patient creates an opportunity to convey messages adapted to the patient in the most appropriate way. The greater the likelihood that the therapeutic message is received by the patient, the greater the patient's response and proactiveness to the treatment will be. International Registered Report Identifier (IRRID): RR2-10.2196/10734 %M 32648555 %R 10.2196/17186 %U http://www.jmir.org/2020/8/e17186/ %U https://doi.org/10.2196/17186 %U http://www.ncbi.nlm.nih.gov/pubmed/32648555 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 7 %P e17087 %T Investigation of Geographic and Macrolevel Variations in LGBTQ Patient Experiences: Longitudinal Social Media Analysis %A Hswen,Yulin %A Zhang,Amanda %A Sewalk,Kara C %A Tuli,Gaurav %A Brownstein,John S %A Hawkins,Jared B %+ Computational Epidemiology Lab, Harvard Medical School, 401 Park Drive, Boston, MA, United States, 1 6177751889, yhswen@gmail.com %K LGBTQ %K sexual and gender minorities %K health care quality %K health care disparities %K social media %K digital health %K sentiment analysis %K infodemiology %D 2020 %7 31.7.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Discrimination in the health care system contributes to worse health outcomes among lesbian, gay, bisexual, transgender, and queer (LGBTQ) patients. Objective: The aim of this study is to examine disparities in patient experience among LGBTQ persons using social media data. Methods: We collected patient experience data from Twitter from February 2013 to February 2017 in the United States. We compared the sentiment of patient experience tweets between Twitter users who self-identified as LGBTQ and non-LGBTQ. The effect of state-level partisan identity on patient experience sentiment and differences between LGBTQ users and non-LGBTQ users were analyzed. Results: We observed lower (more negative) patient experience sentiment among 13,689 LGBTQ users compared to 1,362,395 non-LGBTQ users. Increasing state-level liberal political identification was associated with higher patient experience sentiment among all users but had stronger effects for LGBTQ users. Conclusions: Our findings highlight that social media data can yield insights about patient experience for LGBTQ persons and suggest that a state-level sociopolitical environment influences patient experience for this group. Efforts are needed to reduce disparities in patient care for LGBTQ persons while taking into context the effect of the political climate on these inequities. %M 33137713 %R 10.2196/17087 %U http://www.jmir.org/2020/7/e17087/ %U https://doi.org/10.2196/17087 %U http://www.ncbi.nlm.nih.gov/pubmed/33137713 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 7 %P e18569 %T Consequences of Gift Giving in Online Health Communities on Physician Service Quality: Empirical Text Mining Study %A Peng,Li %A Wang,Yanan %A Chen,Jing %+ School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Qiaokou District, Wuhan, Hubei, China, 86 15972965520, yanan_wang2020@163.com %K online health community %K gift giving %K affective/instrumental gifts %K service quality %K bedside manner %K physicians %K physician-patient relationship %D 2020 %7 30.7.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Gift giving, which has been a heavily debated topic in health care for many years, is considered as a way of expressing gratitude and to be beneficial for the physician-patient relationship within a reasonable range. However, not much work has been done to examine the influence of gift giving on physicians’ service quality, especially in the online health care environment. Objective: This study addressed the consequences of gift giving by mining and analyzing the dynamic physician-patient interaction processes in an online health community. Specifically, gift types (affective or instrumental) based on the motivations and physician-patient tie strength were carefully considered to account for differences in physicians’ service quality. Methods: The dynamic interaction processes (involving 3154 gifts) between 267 physicians and 14,187 patients from a well-known online health community in China (haodf.com) were analyzed to obtain empirical results. Results: Our results reveal that patient gift giving inspires physicians to improve their service quality as measured by physicians’ more detailed responses and improved bedside manner, and the degree of influence varied according to the strength of the physician-patient tie. Moreover, affective gifts and instrumental gifts had different effects in improving physicians’ service quality online. Conclusions: This study is among the first to explore gift giving in online health communities providing both important theoretical and practical contributions. All of our results suggest that gift giving online is of great significance to promoting effective physician-patient communication and is conducive to the relief of physician-patient conflicts. %M 32729834 %R 10.2196/18569 %U http://www.jmir.org/2020/7/e18569/ %U https://doi.org/10.2196/18569 %U http://www.ncbi.nlm.nih.gov/pubmed/32729834 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 7 %P e14455 %T Gender, Soft Skills, and Patient Experience in Online Physician Reviews: A Large-Scale Text Analysis %A Dunivin,Zackary %A Zadunayski,Lindsay %A Baskota,Ujjwal %A Siek,Katie %A Mankoff,Jennifer %+ University of Washington, Bill & Melinda Gates Center for Computer Science and Engineering, 3800 E Stevens Way NE, Seattle, WA, 98112, United States, 1 4125677720, jmankoff@acm.org %K reviews %K physician-patient relationship %K gender %K soft-skills %D 2020 %7 30.7.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Online physician reviews are an important source of information for prospective patients. In addition, they represent an untapped resource for studying the effects of gender on the doctor-patient relationship. Understanding gender differences in online reviews is important because it may impact the value of those reviews to patients. Documenting gender differences in patient experience may also help to improve the doctor-patient relationship. This is the first large-scale study of physician reviews to extensively investigate gender bias in online reviews or offer recommendations for improvements to online review systems to correct for gender bias and aid patients in selecting a physician. Objective: This study examines 154,305 reviews from across the United States for all medical specialties. Our analysis includes a qualitative and quantitative examination of review content and physician rating with regard to doctor and reviewer gender. Methods: A total of 154,305 reviews were sampled from Google Place reviews. Reviewer and doctor gender were inferred from names. Reviews were coded for overall patient experience (negative or positive) by collapsing a 5-star scale and coded for general categories (process, positive/negative soft skills), which were further subdivided into themes. Computational text processing methods were employed to apply this codebook to the entire data set, rendering it tractable to quantitative methods. Specifically, we estimated binary regression models to examine relationships between physician rating, patient experience themes, physician gender, and reviewer gender). Results: Female reviewers wrote 60% more reviews than men. Male reviewers were more likely to give negative reviews (odds ratio [OR] 1.15, 95% CI 1.10-1.19; P<.001). Reviews of female physicians were considerably more negative than those of male physicians (OR 1.99, 95% CI 1.94-2.14; P<.001). Soft skills were more likely to be mentioned in the reviews written by female reviewers and about female physicians. Negative reviews of female doctors were more likely to mention candor (OR 1.61, 95% CI 1.42-1.82; P<.001) and amicability (OR 1.63, 95% CI 1.47-1.90; P<.001). Disrespect was associated with both female physicians (OR 1.42, 95% CI 1.35-1.51; P<.001) and female reviewers (OR 1.27, 95% CI 1.19-1.35; P<.001). Female patients were less likely to report disrespect from female doctors than expected from the base ORs (OR 1.19, 95% CI 1.04-1.32; P=.008), but this effect overrode only the effect for female reviewers. Conclusions: This work reinforces findings in the extensive literature on gender differences and gender bias in patient-physician interaction. Its novel contribution lies in highlighting gender differences in online reviews. These reviews inform patients’ choice of doctor and thus affect both patients and physicians. The evidence of gender bias documented here suggests review sites may be improved by providing information about gender differences, controlling for gender when presenting composite ratings for physicians, and helping users write less biased reviews. %M 32729844 %R 10.2196/14455 %U https://www.jmir.org/2020/7/e14455 %U https://doi.org/10.2196/14455 %U http://www.ncbi.nlm.nih.gov/pubmed/32729844 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 8 %N 7 %P e18599 %T Role of Artificial Intelligence in Patient Safety Outcomes: Systematic Literature Review %A Choudhury,Avishek %A Asan,Onur %+ School of Systems and Enterprises, Stevens Institute of Technology, 1 Castle Point Terrace, Hoboken, NJ, 07030, United States, 1 2012168901 ext 2012168901, oasan@stevens.edu %K artificial intelligence %K patient safety %K drug safety %K clinical error %K report analysis %K natural language processing %K drug %K review %D 2020 %7 24.7.2020 %9 Review %J JMIR Med Inform %G English %X Background: Artificial intelligence (AI) provides opportunities to identify the health risks of patients and thus influence patient safety outcomes. Objective: The purpose of this systematic literature review was to identify and analyze quantitative studies utilizing or integrating AI to address and report clinical-level patient safety outcomes. Methods: We restricted our search to the PubMed, PubMed Central, and Web of Science databases to retrieve research articles published in English between January 2009 and August 2019. We focused on quantitative studies that reported positive, negative, or intermediate changes in patient safety outcomes using AI apps, specifically those based on machine-learning algorithms and natural language processing. Quantitative studies reporting only AI performance but not its influence on patient safety outcomes were excluded from further review. Results: We identified 53 eligible studies, which were summarized concerning their patient safety subcategories, the most frequently used AI, and reported performance metrics. Recognized safety subcategories were clinical alarms (n=9; mainly based on decision tree models), clinical reports (n=21; based on support vector machine models), and drug safety (n=23; mainly based on decision tree models). Analysis of these 53 studies also identified two essential findings: (1) the lack of a standardized benchmark and (2) heterogeneity in AI reporting. Conclusions: This systematic review indicates that AI-enabled decision support systems, when implemented correctly, can aid in enhancing patient safety by improving error detection, patient stratification, and drug management. Future work is still needed for robust validation of these systems in prospective and real-world clinical environments to understand how well AI can predict safety outcomes in health care settings. %M 32706688 %R 10.2196/18599 %U http://medinform.jmir.org/2020/7/e18599/ %U https://doi.org/10.2196/18599 %U http://www.ncbi.nlm.nih.gov/pubmed/32706688 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 7 %P e18652 %T Assessing Patient Experience and Healthcare Quality of Dental Care Using Patient Online Reviews in the United States: Mixed Methods Study %A Lin,Ye %A Hong,Y Alicia %A Henson,Bradley S %A Stevenson,Robert D %A Hong,Simon %A Lyu,Tianchu %A Liang,Chen %+ Arnold School of Public Health, University of South Carolina, Suite 347, 915 Greene Street, Columbia, SC, 29208, United States, 1 803 777 8139, cliang@mailbox.sc.edu %K dental care %K healthcare quality %K consumer health informatics %K patient online reviews %K patient review websites %K natural language processing %D 2020 %7 7.7.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Over the last two decades, patient review websites have emerged as an essential online platform for doctor ratings and reviews. Recent studies suggested the significance of such websites as a data source for patients to choose doctors for healthcare providers to learn and improve from patient feedback and to foster a culture of trust and transparency between patients and healthcare providers. However, as compared to other medical specialties, studies of online patient reviews that focus on dentists in the United States remain absent. Objective: This study sought to understand to what extent online patient reviews can provide performance feedbacks that reflect dental care quality and patient experience. Methods: Using mixed informatics methods incorporating statistics, natural language processing, and domain expert evaluation, we analyzed the online patient reviews of 204,751 dentists extracted from HealthGrades with two specific aims. First, we examined the associations between patient ratings and a variety of dentist characteristics. Second, we identified topics from patient reviews that can be mapped to the national assessment of dental patient experience measured by the Patient Experience Measures from the Consumer Assessment of Healthcare Providers and Systems (CAHPS) Dental Plan Survey. Results: Higher ratings were associated with female dentists (t71881=2.45, P<.01, g=0.01), dentists at a younger age (F7, 107128=246.97, P<.001, g=0.11), and those whose patients experienced a short wait time (F4, 150055=10417.77, P<0.001, g=0.18). We also identified several topics that corresponded to CAHPS measures, including discomfort (eg, painful/painless root canal or deep cleaning), and ethics (eg, high-pressure sales, and unnecessary dental work). Conclusions: These findings suggest that online patient reviews could be used as a data source for understanding the patient experience and healthcare quality in dentistry. %M 32673240 %R 10.2196/18652 %U https://www.jmir.org/2020/7/e18652 %U https://doi.org/10.2196/18652 %U http://www.ncbi.nlm.nih.gov/pubmed/32673240 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 6 %P e18203 %T The Impact of Digital-First Consultations on Workload in General Practice: Modeling Study %A Salisbury,Chris %A Murphy,Mairead %A Duncan,Polly %+ Centre for Academic Primary Care, Department of Population Health Sciences, Bristol Medical School, University of Bristol, Canynge Hall, 39 Whatley Road, Bristol, BS8 2PS, United Kingdom, 44 1173314530, c.salisbury@bristol.ac.uk %K general practice %K family practice %K electronic consultations %K remote consultation %K telemedicine %K telephone consultation %K video %K access to health care %K health care quality, access, and evaluation %D 2020 %7 16.6.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Health services in many countries are promoting digital-first models of access to general practice based on offering online, video, or telephone consultations before a face-to-face consultation. It is claimed that this will improve access for patients and moderate the workload of doctors. However, improved access could also potentially increase doctors’ workload. Objective: The aim of this study was to explore whether and under what circumstances digital-first access to general practice is likely to decrease or increase general practice workload. Methods: A process map to delineate primary care access pathways was developed and a model to estimate general practice workload constructed in Microsoft Excel (Microsoft Corp). The model was populated using estimates of key variables obtained from a systematic review of published studies. A MEDLINE search was conducted for studies published in English between January 1, 2000, and September 30, 2019. Included papers provided quantitative data about online, telephone, or video consultations for unselected patients requesting a general practice in-hours consultation for any problem. We excluded studies of general practitioners consulting specialists, consultations not conducted by doctors, and consultations conducted after hours, in secondary care, in specialist services, or for a specific health care problem. Data about the following variables were extracted from the included papers to form the model inputs: the proportion of consultations managed digitally, the proportion of digital consultations completed without a subsequent consultation, the proportion of subsequent consultations conducted by telephone rather than face-to-face, consultation duration, and the proportion of digital consultations that represent new demand. The outcome was general practice workload. The model was used to test the likely impact of different digital-first scenarios, based on the best available evidence and the plausible range of estimates from the published studies. The model allows others to test the impact on workload of varying assumptions about model inputs. Results: Digital-first approaches are likely to increase general practice workload unless they are shorter, and a higher proportion of patients are managed without a subsequent consultation than observed in most published studies. In our base-case scenarios (based on the best available evidence), digital-first access models using online, telephone, or video consultations are likely to increase general practitioner workload by 25%, 3%, and 31%, respectively. An important determinant of workload is whether the availability of digital-first approaches changes the demand for general practice consultations, but there is little robust evidence to answer this question. Conclusions: Digital-first approaches to primary care could increase general practice workload unless stringent conditions are met. Justification for these approaches should be based on evidence about the benefits in relation to the costs, rather than assumptions about reductions in workload. Given the potential increase in workload, which in due course could worsen problems of access, these initiatives should be implemented in a staged way alongside careful evaluation. %M 32543441 %R 10.2196/18203 %U http://www.jmir.org/2020/6/e18203/ %U https://doi.org/10.2196/18203 %U http://www.ncbi.nlm.nih.gov/pubmed/32543441 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 6 %P e16849 %T Metrics for Outpatient Portal Use Based on Log File Analysis: Algorithm Development %A Di Tosto,Gennaro %A McAlearney,Ann Scheck %A Fareed,Naleef %A Huerta,Timothy R %+ CATALYST: Center for the Advancement of Team Science, Analytics, and Systems Thinking in Health Services and Implementation Science Research, College of Medicine, The Ohio State University, 460 Medical Center Drive, Suite 515, Columbus, OH, 43210, United States, 1 6142938973, gennaro.ditosto@osumc.edu %K patient portals %K health records, personal %K health information technology %K electronic health record %D 2020 %7 12.6.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Web-based outpatient portals help patients engage in the management of their health by allowing them to access their medical information, schedule appointments, track their medications, and communicate with their physicians and care team members. Initial studies have shown that portal adoption positively affects health outcomes; however, early studies typically relied on survey data. Using data from health portal applications, we conducted systematic assessments of patients’ use of an outpatient portal to examine how patients engage with the tool. Objective: This study aimed to document the functionality of an outpatient portal in the context of outpatient care by mining portal usage data and to provide insights into how patients use this tool. Methods: Using audit log files from the outpatient portal associated with the electronic health record system implemented at a large multihospital academic medical center, we investigated the behavioral traces of a study population of 2607 patients who used the portal between July 2015 and February 2019. Patient portal use was defined as having an active account and having accessed any portal function more than once during the study time frame. Results: Through our analysis of audit log file data of the number and type of user interactions, we developed a taxonomy of functions and actions and computed analytic metrics, including frequency and comprehensiveness of use. We additionally documented the computational steps required to diagnose artifactual data and arrive at valid usage metrics. Of the 2607 patients in our sample, 2511 were active users of the patients portal where the median number of sessions was 94 (IQR 207). Function use was comprehensive at the patient level, while each session was instead limited to the use of one specific function. Only 17.45% (78,787/451,762) of the sessions were linked to activities involving more than one portal function. Conclusions: In discussing the full methodological choices made in our analysis, we hope to promote the replicability of our study at other institutions and contribute to the establishment of best practices that can facilitate the adoption of behavioral metrics that enable the measurement of patient engagement based on the outpatient portal use. %M 32530435 %R 10.2196/16849 %U https://www.jmir.org/2020/6/e16849 %U https://doi.org/10.2196/16849 %U http://www.ncbi.nlm.nih.gov/pubmed/32530435 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 6 %P e11839 %T Enhancing Patient Experience With Internet Protocol Addressable Digital Light-Emitting Diode Lighting in Imaging Environments: A Phase I Study %A Knopp,Melanie U %A Binzel,Katherine %A Wright,Chadwick L %A Zhang,Jun %A Knopp,Michael V %+ Department of Radiology, Wright Center of Innovation, The Ohio State University, 395 W 12th Avenue, Suite 430, Columbus, OH, 43210, United States, 1 6142939998, knopp.16@osu.edu %K ambient lighting %K patient comfort %K medical imaging %K color perception %K health care environment %K internet protocol–based light-emitting diode lighting %D 2020 %7 12.6.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Conventional approaches to improve the quality of clinical patient imaging studies focus predominantly on updating or replacing imaging equipment; however, it is often not considered that patients can also highly influence the diagnostic quality of clinical imaging studies. Patient-specific artifacts can limit the diagnostic image quality, especially when patients are uncomfortable, anxious, or agitated. Imaging facility or environmental conditions can also influence the patient’s comfort and willingness to participate in diagnostic imaging studies, especially when performed in visually unesthetic, anxiety-inducing, and technology-intensive imaging centers. When given the opportunity to change a single aspect of the environmental or imaging facility experience, patients feel much more in control of the otherwise unfamiliar and uncomfortable setting. Incorporating commercial, easily adaptable, ambient lighting products within clinical imaging environments allows patients to individually customize their environment for a more personalized and comfortable experience. Objective: The aim of this pilot study was to use a customizable colored light-emitting diode (LED) lighting system within a clinical imaging environment and demonstrate the feasibility and initial findings of enabling healthy subjects to customize the ambient lighting and color. Improving the patient experience within clinical imaging environments with patient-preferred ambient lighting and color may improve overall patient comfort, compliance, and participation in the imaging study and indirectly contribute to improving diagnostic image quality. Methods: We installed consumer-based internet protocol addressable LED lights using the ZigBee standard in different imaging rooms within a clinical imaging environment. We recruited healthy volunteers (n=35) to generate pilot data in order to develop a subsequent clinical trial. The visual perception assessment procedure utilized questionnaires with preprogrammed light/color settings and further assessed how subjects preferred ambient light and color within a clinical imaging setting. Results: Technical implementation using programmable LED lights was performed without any hardware or electrical modifications to the existing clinical imaging environment. Subject testing revealed substantial variabilities in color perception; however, clear trends in subject color preference were noted. In terms of the color hue of the imaging environment, 43% (15/35) found blue and 31% (11/35) found yellow to be the most relaxing. Conversely, 69% (24/35) found red, 17% (6/35) found yellow, and 11% (4/35) found green to be the least relaxing. Conclusions: With the majority of subjects indicating that colored lighting within a clinical imaging environment would contribute to an improved patient experience, we predict that enabling patients to customize environmental factors like lighting and color to individual preferences will improve patient comfort and patient satisfaction. Improved patient comfort in clinical imaging environments may also help to minimize patient-specific imaging artifacts that can otherwise limit diagnostic image quality. Trial Registration: ClinicalTrials.gov NCT03456895; https://clinicaltrials.gov/ct2/show/NCT03456895 %M 32530434 %R 10.2196/11839 %U http://www.jmir.org/2020/6/e11839/ %U https://doi.org/10.2196/11839 %U http://www.ncbi.nlm.nih.gov/pubmed/32530434 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 4 %N 3 %P e15158 %T Improving Quality of Care in Rheumatoid Arthritis Through Mobile Patient-Reported Outcome Measurement: Focus Group Study %A Desai,Sonali %A Stevens,Emma %A Emani,Srinivas %A Meyers,Peter %A Iversen,Maura %A Solomon,Daniel H %+ Brigham & Women's Hospital, 60 Fenwood Road, Hale Building for Transformative Medicine, Boston, MA, Rheumatology, 3rd fl, United States, 1 6177326758, sdesai5@bwh.harvard.edu %K quality improvement %K rheumatoid arthritis %D 2020 %7 27.5.2020 %9 Original Paper %J JMIR Form Res %G English %X Background: Patient-reported outcomes (PROs) for chronic disease management can be integrated into the routine workflow by leveraging mobile technology. Objective: The objective of our study was to describe the process of our quality improvement (QI) efforts using tablets for PRO collection in a busy, academic rheumatology practice to support a treat-to-target (TTT) approach for rheumatoid arthritis (RA) management. Methods: Our QI team designed a process for routine collection of PROs for RA patients at the Arthritis Center, employing information technology and an electronic medical record (EMR) system. Patients received a tablet at the clinic check-in desk to complete the Routine Assessment of Patient Index Data 3 (RAPID3) survey, a validated RA PRO. RAPID3 scores were uploaded to the EMR in real time and available for use in shared decision making during routine office visits. Weekly data were collected on RAPID3 completion rates and shared with front desk staff and medical assistants to drive improvement. Patients in our patient family advisory council and focus groups provided informal feedback on the process. Results: From May 1, 2017, to January 31, 2019, a total of 4233 RAPID3 surveys were completed by 1691 patients. The mean age of patients was 63 (SD 14) years; 84.00% (1420/1691) of the patients were female, and 83.00% (1403/1691) of the patients were white. The rates of RAPID3 completion increased from 14.3% (58/405) in May 2017 to 68.00% (254/376) in September 2017 and were sustained over time through January 2019. Informal feedback from patients was positive and negative, relating to the usability of the tablet and the way rheumatologists used and explained the RAPID3 data in shared decision making during the office visit. Conclusions: We designed a sustainable and reliable process for collecting PROs from patients with RA in the waiting room and integrated these data through the EMR during office visits. %M 32459179 %R 10.2196/15158 %U http://formative.jmir.org/2020/3/e15158/ %U https://doi.org/10.2196/15158 %U http://www.ncbi.nlm.nih.gov/pubmed/32459179 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 8 %N 5 %P e15762 %T Mobile App to Improve House Officers’ Adherence to Advanced Cardiac Life Support Guidelines: Quality Improvement Study %A Hejjaji,Vittal %A Malik,Ali O %A Peri-Okonny,Poghni A %A Thomas,Merrill %A Tang,Yuanyuan %A Wooldridge,David %A Spertus,John A %A Chan,Paul S %+ Department of Cardiovascular Medicine, Saint Luke's Mid America Heart Institute, University of Missouri Kansas City, 4401 Wornall Rd, Kansas City, MO, United States, 1 2162781685, hejjajiv@umkc.edu %K cardiac arrest %K advanced cardiac life support %K mHealth %K quality improvement %K medical education %D 2020 %7 19.5.2020 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: Effective and timely delivery of cardiac arrest interventions during in-hospital cardiac arrest resuscitation is associated with greater survival. Whether a mobile app that provides timely reminders of critical interventions improves adherence to Advanced Cardiovascular Life Support (ACLS) guidelines among house officers, who may lack experience in leading resuscitations, remains unknown. Objective: The aim of this study was to assess the impact of a commercially available, dynamic mobile app on house officers’ adherence to ACLS guidelines. Methods: As part of a quality improvement initiative, internal medicine house officers were invited to participate and randomized to lead 2 consecutive cardiac arrest simulations, one with a novel mobile app and one without a novel mobile app. All simulations included 4 cycles of cardiopulmonary resuscitation with different cardiac arrest rhythms and were video recorded. The coprimary end points were chest compression fraction and number of correct interventions in each simulation. The secondary end point was incorrect interventions, defined as interventions not indicated by the 2015 ACLS guidelines. Paired t tests compared performance with and without the mobile app. Results: Among 53 house officers, 26 house officers were randomized to lead the first simulation with the mobile app, and 27 house officers were randomized to do so without the app. Use of the mobile app was associated with a higher number of correct ACLS interventions (out of 7; mean 6.2 vs 5.1; absolute difference 1.1 [95% CI 0.6 to 1.6]; P<.001) as well as fewer incorrect ACLS interventions (mean 0.3 vs 1.0; absolute difference –0.7 [95% CI –0.3 to –1.0]; P<.001). Simulations with the mobile app also had a marginally higher chest compression fraction (mean 90.9% vs 89.0%; absolute difference 1.9% [95% CI 0.6% to 3.4%]; P=.007). Conclusions: This proof-of-concept study suggests that this novel mobile app may improve adherence to ACLS protocols, but its effectiveness on survival in real-world resuscitations remains unknown. %M 32427115 %R 10.2196/15762 %U https://mhealth.jmir.org/2020/5/e15762 %U https://doi.org/10.2196/15762 %U http://www.ncbi.nlm.nih.gov/pubmed/32427115 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 5 %P e16708 %T Association Between Web-Based Physician Ratings and Physician Disciplinary Convictions: Retrospective Observational Study %A Liu,Jessica Janine %A Goldberg,Hanna R %A Lentz,Eric JM %A Matelski,John Justin %A Alam,Asim %A Bell,Chaim M %+ Division of General Internal Medicine, Department of Medicine, University of Toronto, Toronto General Hospital, 200 Elizabeth Street, Room 14EN213, Toronto, ON, M5G 2C4, Canada, 1 4163403111, jessica.liu@uhn.ca %K quality improvement %K patient satisfaction %K patient-centered care %D 2020 %7 14.5.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Physician rating websites are commonly used by the public, yet the relationship between web-based physician ratings and health care quality is not well understood. Objective: The objective of our study was to use physician disciplinary convictions as an extreme marker for poor physician quality and to investigate whether disciplined physicians have lower ratings than nondisciplined matched controls. Methods: This was a retrospective national observational study of all disciplined physicians in Canada (751 physicians, 2000 to 2013). We searched ratings (2005-2015) from the country’s leading online physician rating website for this group, and for 751 matched controls according to gender, specialty, practice years, and location. We compared overall ratings (out of a score of 5) as well as mean ratings by the type of misconduct. We also compared ratings for each type of misconduct and punishment. Results: There were 62.7% (471/751) of convicted and disciplined physicians (cases) with web-based ratings and 64.6% (485/751) of nondisciplined physicians (controls) with ratings. Of 312 matched case-control pairs, disciplined physicians were rated lower than controls overall (3.62 vs 4.00; P<.001). Disciplined physicians had lower ratings for all types of misconduct and punishment—except for physicians disciplined for sexual offenses (n=90 pairs; 3.83 vs 3.86; P=.81). Sexual misconduct was the only category in which mean ratings for physicians were higher than those for other disciplined physicians (3.63 vs 3.35; P=.003) Conclusions: Physicians convicted for disciplinary misconduct generally had lower web-based ratings. Physicians convicted of sexual misconduct did not have lower ratings and were rated higher than other disciplined physicians. These findings may have future implications for the identification of physicians providing poor-quality care. %M 32406851 %R 10.2196/16708 %U https://www.jmir.org/2020/5/e16708 %U https://doi.org/10.2196/16708 %U http://www.ncbi.nlm.nih.gov/pubmed/32406851 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 9 %N 5 %P e16039 %T Evaluation and Dissemination of a Checklist to Improve Implementation of Work Environment Initiatives in the Eldercare Sector: Protocol for a Prospective Observational Study %A Rasmussen,Charlotte Diana Nørregaard %A Højberg,Helene %A Larsen,Anne Konring %A Munch,Pernille Kold %A Osborne,Richard %A Kwak,Lydia %A Jensen,Irene %A Linnan,Laura %A Jørgensen,Marie Birk %+ The National Research Centre for the Working Environment, Lersø Parkalle 105, København Ø, Denmark, 45 39 16 54 66, cnr@nfa.dk %K RE-AIM %K implementation %K workplace %K digital %D 2020 %7 13.5.2020 %9 Protocol %J JMIR Res Protoc %G English %X Background: To measure sustainable improvements in the work environment, a flexible and highly responsive tool is needed that will give important focus to the implementation process. A digital checklist was developed in collaboration with key stakeholders to document the implementation of changes in eldercare sector workplaces. Objective: This paper describes the study protocol of a dissemination study that aims to examine when, why, and how the digital checklist is spread to the Danish eldercare sector following a national campaign particularly targeting nursing homes and home care. Methods: This prospective observational study will use quantitative data from Google Analytics describing use of the checklist as documented website engagement, a survey among members in the largest union in the sector, information from a central business register, and monitoring of campaign activities. The evaluation will be guided by the five elements of the RE-AIM framework: reach, effectiveness, adoption, implementation, and maintenance. Results: The study was approved in June 2016 and began in October 2018. The campaign that is the foundation for the evaluation began in 2017 and ended in 2018. However, the webpage where we collect data is still running. Results are expected in 2020. Conclusions: This protocol provides a working example of how to evaluate dissemination of a checklist to improve implementation of work environment initiatives in the eldercare sector in Denmark. To our knowledge, implementation in a nationwide Danish work environment has not been previously undertaken. Given that the checklist is sector-specific for work environment initiatives and developed through systematic collaboration between research and practice, it is likely to have high utility and impact; however, the proposed evaluation will determine this. This study will advance dissemination research and, in particular, the evaluation of the impact of these types of studies. Finally, this study advances the field through digital tools that can be used for evaluation of dissemination efforts (eg, Google Analytics associated with website) in the context of a rigorous research design activity. International Registered Report Identifier (IRRID): DERR1-10.2196/16039 %M 32401212 %R 10.2196/16039 %U https://www.researchprotocols.org/2020/5/e16039 %U https://doi.org/10.2196/16039 %U http://www.ncbi.nlm.nih.gov/pubmed/32401212 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 5 %P e14412 %T Patients' Experiences and Attitudes of Using a Secure Mobile Phone App for Medical Photography: Qualitative Survey Study %A Wyatt,Kirk D %A Finley,Anissa %A Uribe,Richard %A Pallagi,Peter %A Willaert,Brian %A Ommen,Steve %A Yiannias,James %A Hellmich,Thomas %+ Division of Pediatric Hematology/Oncology, Department of Pediatric and Adolescent Medicine, Mayo Clinic, 200 First Street Southwest, Rochester, MN, 55905, United States, 1 507 284 2695, wyatt.kirk@mayo.edu %K photography %K mobile apps %K telemedicine %K electronic health records %K mobile phone %K digital imaging %K dermatology %K vascular medicine %K family medicine %D 2020 %7 12.5.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Point-of-care clinical photography using mobile devices is coming of age as a new standard of care for clinical documentation. High-quality cameras in modern smartphones facilitate faithful reproduction of clinical findings in photographs; however, clinical photographs captured on mobile devices are often taken using the native camera app on the device and transmitted using relatively insecure methods (eg, SMS text message and email) that do not preserve images as part of the electronic medical records. Native camera apps lack robust security features and direct integration with electronic health records (EHRs), which may limit patient acceptability and usefulness to clinicians. In March 2015, Mayo Clinic overcame these barriers by launching an internally developed mobile app that allows health care providers to securely capture clinical photographs and upload them to the EHR in a manner that is compliant with patient privacy and confidentiality regulations. Objective: The study aimed to understand the perceptions, attitudes, and experiences of patients who were photographed using a mobile point-of-care clinical image capture app. Methods: The study included a mail-out survey sent to 292 patients in Rochester, Minnesota, who were photographed using a mobile point-of-care clinical image capture app within a preceding 2-week period. Results: The surveys were completed by 71 patients who recalled being photographed. Patients were seen in 18 different departments, with the most common departments being dermatology (19/71, 27%), vascular medicine (17/71, 24%), and family medicine (10/71, 14%). Most patients (49/62, 79%) reported that photographs were taken to simply document the appearance of a clinical finding for future reference. Only 16% (10/62) of patients said the photographs were used to obtain advice from a specialist. Furthermore, 74% (51/69) of the patients said they would recommend medical photography to others and 67% (46/69) of them thought the photos favorably affected their care. Patients were largely indifferent about the device used for photography (mobile device vs professional camera; 40/69, 58%) or the identity of the photographer (provider vs professional photographer; 52/69, 75%). In addition, 90% (64/71) of patients found reuse of photographs for one-on-one learner education to be acceptable. Acceptability for other uses declined as the size of the audience increased, with only 42% (30/71) of patients deeming reuse on social media for medical education as appropriate. Only 3% (2/71) of patients expressed privacy or confidentiality concerns. Furthermore, 52% (33/63) of patients preferred to provide consent verbally, and 21% (13/63) of them did not think a specific consent process was necessary. Conclusions: Patient attitudes regarding medical photography using a secure EHR-integrated app were favorable. Patients perceived that photography improved their care despite the most common reason for photography being to simply document the appearance of a clinical finding for future reference. Whenever possible, health care providers should utilize secure EHR-integrated apps for point-of-care medical photography using mobile devices. %M 32396127 %R 10.2196/14412 %U http://www.jmir.org/2020/5/e14412/ %U https://doi.org/10.2196/14412 %U http://www.ncbi.nlm.nih.gov/pubmed/32396127 %0 Journal Article %@ 2562-0959 %I JMIR Publications %V 3 %N 1 %P e17171 %T Assessment of Patient Satisfaction With Dermatology Clinics According to Clinic Type: Mixed Methods Study %A Costigan,Jennifer %A Feldman,Sue S %A Lemak,Mark %+ Department of Health Services Research, School of Health Professions, University of Alabama at Birmingham, 1716 9th Avenue South, SHPB #590K, Birmingham, AL, 35294, United States, 1 205 975 0809, suefeldman1009@gmail.com %K Consumer Assessment of Healthcare Providers and Systems survey scores %K patient satisfaction %K dermatology %K private dermatology clinic %K rapid access dermatology clinic %K wait time %K patient resource stewardship %K communication %D 2020 %7 12.5.2020 %9 Original Paper %J JMIR Dermatol %G English %X Background: Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey responses are considered significant indicators of the quality of care and patient satisfaction. There is a pressing need to improve patient satisfaction rates as CAHPS survey responses are considered when determining the amount a facility will be reimbursed by the Centers of Medicare and Medicaid each year. Low overall CAHPS scores for an academic medical center’s dermatology clinics were anecdotally attributed to clinic type. However, it was unclear whether clinic type was contributing to the low scores or whether there were other factors. Objective: This study aimed to determine where the efforts of patient satisfaction improvement should be focused for two different types of dermatology clinics (private and rapid access clinics). Methods: This study used a concurrent mixed methods design. Secondary data derived from the University of Alabama at Birmingham Hospital’s Press Ganey website were analyzed for clinic type comparisons and unstructured data were qualitatively analyzed to further enrich the quantitative findings. The University of Alabama at Birmingham Hospital is an academic medical center. The data were analyzed to determine the contributors responsible for each clinic not meeting national benchmarks. Thereafter, a review of these contributing factors was further performed to assess the difference in CAHPS scores between the private and rapid access clinics to determine if clinic type was a contributing factor to the overall scores. Results: The data sample included 821 responses from May 2017 to May 2018. Overall, when both private clinics and rapid access clinics were viewed collectively, majority of the patients reported stewardship of patient resources as the most poorly rated factor (367/549, 66.8%) and physician communication quality as the most positively rated factor (581/638, 91.0%). However, when private clinics and rapid access clinics were viewed individually, rapid access clinics contributed slightly to the overall lower dermatology scores at the academic medical center. Conclusions: This study determined that different factors were responsible for lower CAHPS scores for the two different dermatology clinics. Some of the contributing factors were associated with the mission of the clinic. It was suspected that the mission had not been properly communicated to patients, leading to misaligned expectations of care at each clinic. %R 10.2196/17171 %U http://derma.jmir.org/2020/1/e17171/ %U https://doi.org/10.2196/17171 %0 Journal Article %@ 2561-9128 %I JMIR Publications %V 3 %N 1 %P e17669 %T A Redesigned Order Entry System for Reducing Low-Value Preprocedural Cardiology Consultations: Quality-Improvement Cohort Study %A Winchester,David E %A Cagino,Leigh %+ Malcom Randall Veterans Affairs Medical Center, 1601 SW Archer Rd 111-D, Gainesville, FL, 32608, United States, 1 3525466000, david.winchester@va.gov %K quality improvement %K preoperative care %K medical order entry systems %D 2020 %7 1.5.2020 %9 Original Paper %J JMIR Perioper Med %G English %X Background: Preprocedural cardiac evaluation is a common reason for outpatient cardiology visits. Many patients who are referred to cardiology clinics for preprocedural evaluation are at low risk of perioperative events and do not require any further management. Our facility treats patients over a large geographic area; avoiding low-value consultations reduces time and travel burdens for patients. Objective: Our study objective was to assess the impact of a novel algorithm in the electronic order entry system aimed to guide clinicians toward patients who may benefit from cardiovascular referral. Methods: We retrospectively reviewed in-person consultations and electronic consultations (e-consults) to our cardiology service before and after implementation of the novel algorithm to assess changes in patterns of care. Data were stored in a custom electronic database on internal servers. Results: We reviewed 603 consultations to our cardiology clinic and found that 89 (14.7%) were sent for preprocedural evaluation. Of these, 39 (43.8% of preprocedural consultations) were e-consults. After implementation, we reviewed 360 consultations. The proportion of consultations for preprocedural evaluation did not decrease (n=47, 13.0%; P=.39). We observed an absolute increase of 13.6% in the proportion of consultations ordered as e-consults (27/47, 57.4%). During the postintervention period, we received no remarks, concerns, or criticisms from ordering clinicians about the process change and no reports of adverse events. Conclusions: Implementation of an ordering algorithm to reduce low-value preprocedural cardiology evaluations did not lead to a reduction in the number of overall preprocedural cardiology consultations. The number of patients seen electronically increased, potentially improving clinic access and reducing travel burden for patients. %M 33393916 %R 10.2196/17669 %U https://periop.jmir.org/2020/1/e17669 %U https://doi.org/10.2196/17669 %U http://www.ncbi.nlm.nih.gov/pubmed/33393916 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 4 %P e16541 %T Measures of Patient Dissatisfaction With Health Care in Polycystic Ovary Syndrome: Retrospective Analysis %A Hoyos,Luis R %A Putra,Manesha %A Armstrong,Abigail A %A Cheng,Connie Y %A Riestenberg,Carrie K %A Schooler,Tery A %A Dumesic,Daniel A %+ Department of Obstetrics and Gynecology, University of California, 10833 Le Conte Avenue, Room 22-178 CHS, Los Angeles, CA, United States, 1 3107945542, ddumesic@mednet.ucla.edu %K PCOS %K fibroid %K Google %K healthcare quality %K infoveillance %K infodemiology %K medical education %K health care %K internet %K satisfaction %D 2020 %7 21.4.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Polycystic ovary syndrome (PCOS) is a common reproductive and metabolic disorder in women; however, many clinicians may not be well versed in scientific advances that aid understanding of the associated reproductive, metabolic, and psychological abnormalities. Women with PCOS are dissatisfied with health care providers, the diagnostic process, and the initial treatment of PCOS and seek information through alternative sources. This has affected the patient-physician relationship by allowing medical information acquired through the internet, whether correct or not, to become accessible to patients and reshape their health care perspective. Patient dissatisfaction with health care providers regarding PCOS raises questions about the responsibilities of academic institutions to adequately train and maintain the competence of clinicians and government agencies to sufficiently support scientific investigation in this field. Objective: The primary aim was to examine internet searching behaviors of the public regarding PCOS vs another highly prevalent gynecologic disorder. The secondary aim was to explore satisfaction with health care among patients with PCOS and their internet use. The tertiary aim was to examine medical education in reproductive endocrinology and infertility (REI) during obstetrics and gynecology (Ob/Gyn) residency as a proxy for physician knowledge in this field. Methods: Google search trends and StoryBase quantified monthly Google absolute search volumes for search terms related to PCOS and fibroids (January 2004 to December 2017; United States). The reproductive disorder, fibroids, was selected as a comparison group because of its high prevalence among women. Between female groups, monthly absolute search volumes and their trends were compared. A Web-based questionnaire (June 2015 to March 2018) explored health care experiences and the internet use of women with PCOS. REI rotation information during Ob/Gyn residency in the United States was obtained from the Association of Professors of Gynecology and Obstetrics website. Results: For PCOS (R=0.89; P<.01), but not fibroids (R=0.09; P=.25), monthly absolute search volumes increased significantly. PCOS-related monthly absolute search volumes (mean 384,423 searches, SD 88,756) were significantly greater than fibroid-related monthly absolute search volumes (mean 348,502 searches, SD 37,317; P<.05). PCOS was diagnosed by an Ob/Gyn in 60.9% (462/759) of patients, and 57.3% (435/759) of patients were dissatisfied with overall care. Among patients with PCOS, 98.2% (716/729) searched for PCOS on the Web but only 18.8% (143/729) of patients joined an online PCOS support group or forum. On average, Ob/Gyn residencies dedicated only 4% (2/43) of total block time to REI, whereas 5.5% (11/200) of such residencies did not offer any REI rotations. Conclusions: Over time, PCOS has been increasingly searched on the Web compared with another highly prevalent gynecologic disorder. Patients with PCOS are dissatisfied with their health care providers, who would benefit from an improved understanding of PCOS during Ob/Gyn residency training. %M 32314967 %R 10.2196/16541 %U http://www.jmir.org/2020/4/e16541/ %U https://doi.org/10.2196/16541 %U http://www.ncbi.nlm.nih.gov/pubmed/32314967 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 8 %N 4 %P e16400 %T Low-Density Lipoprotein Cholesterol Target Attainment in Patients With Established Cardiovascular Disease: Analysis of Routine Care Data %A Groenhof,T Katrien J %A Kofink,Daniel %A Bots,Michiel L %A Nathoe,Hendrik M %A Hoefer,Imo E %A Van Solinge,Wouter W %A Lely,A Titia %A Asselbergs,Folkert W %A Haitjema,Saskia %+ Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, 3584CX, Netherlands, 31 887569308, t.k.j.groenhof@umcutrecht.nl %K learning health care system %K routine clinical data %K cardiovascular risk management %K LDL-c %D 2020 %7 2.4.2020 %9 Original Paper %J JMIR Med Inform %G English %X Background: Direct feedback on quality of care is one of the key features of a learning health care system (LHS), enabling health care professionals to improve upon the routine clinical care of their patients during practice. Objective: This study aimed to evaluate the potential of routine care data extracted from electronic health records (EHRs) in order to obtain reliable information on low-density lipoprotein cholesterol (LDL-c) management in cardiovascular disease (CVD) patients referred to a tertiary care center. Methods: We extracted all LDL-c measurements from the EHRs of patients with a history of CVD referred to the University Medical Center Utrecht. We assessed LDL-c target attainment at the time of referral and per year. In patients with multiple measurements, we analyzed LDL-c trajectories, truncated at 6 follow-up measurements. Lastly, we performed a logistic regression analysis to investigate factors associated with improvement of LDL-c at the next measurement. Results: Between February 2003 and December 2017, 250,749 LDL-c measurements were taken from 95,795 patients, of whom 23,932 had a history of CVD. At the time of referral, 51% of patients had not reached their LDL-c target. A large proportion of patients (55%) had no follow-up LDL-c measurements. Most of the patients with repeated measurements showed no change in LDL-c levels over time: the transition probability to remain in the same category was up to 0.84. Sequence clustering analysis showed more women (odds ratio 1.18, 95% CI 1.07-1.10) in the cluster with both most measurements off target and the most LDL-c measurements furthest from the target. Timing of drug prescription was difficult to determine from our data, limiting the interpretation of results regarding medication management. Conclusions: Routine care data can be used to provide feedback on quality of care, such as LDL-c target attainment. These routine care data show high off-target prevalence and little change in LDL-c over time. Registrations of diagnosis; follow-up trajectory, including primary and secondary care; and medication use need to be improved in order to enhance usability of the EHR system for adequate feedback. %M 32238333 %R 10.2196/16400 %U https://medinform.jmir.org/2020/4/e16400 %U https://doi.org/10.2196/16400 %U http://www.ncbi.nlm.nih.gov/pubmed/32238333 %0 Journal Article %@ 2561-6722 %I JMIR Publications %V 3 %N 1 %P e17517 %T Families’ Degree of Satisfaction With Pediatric Telehomecare: Interventional Prospective Pilot Study in Catalonia %A López Seguí,Francesc %A Batlle Boada,Astrid %A García García,Juan José %A López Ulldemolins,Ana %A Achotegui del Arco,Ane %A Adroher Mas,Cristina %A García Cuyàs,Francesc %+ Sant Joan de Déu Hospital, Catalan Ministry of Health, Passeig de Sant Joan de Déu, 2, Barcelona, 08950, Spain, 34 932 53 21 00, fgarciac@sjdhospitalbarcelona.org %K home health monitoring %K pediatrics %K telehomecare %K videoconferencing %K satisfaction with care %K remote sensing technology %K telemedicine %K telehealth %D 2020 %7 26.3.2020 %9 Original Paper %J JMIR Pediatr Parent %G English %X Background: Pediatric home hospitalization improves the quality of life of children and their families, involving them in their children’s care, while favoring the work-life balance of the family. In this context, technology guarantees accessibility to assistance, which provides security to users. From the perspective of the health care system, this could lower the demand for hospital services and reduce hospitalization costs. Objective: This study aimed to assess families’ degree of satisfaction and acceptability of pediatric telehomecare and explore the clinical characteristics of children benefiting from the program. Methods: A total of 95 children and their families participated in the home-hospitalization pilot program operated by Sant Joan de Déu Hospital in Barcelona, Spain. Families were visited once a day and patients were monitored using a kit consisting of a scale, a thermometer, a pulse oximeter, and a blood pressure monitor. Data on parental experience, satisfaction, safety, and preference for care was collected by means of a questionnaire. Data about the children’s characteristics were collected from medical records. Descriptive and comparative statistics were used to analyze the data. Results: A total of 65 survey respondents expressed very high levels of satisfaction. Families reported their experiences as being very positive, preferring home hospitalization in 94% (61/65) of cases, and gave high scores regarding the use of telemonitoring devices. The program did not record any readmissions after 72 hours and reported a very low number of adverse incidents. The user profile was very heterogeneous, highlighting a large number of respiratory patients and patients with infections that required endovenous antibiotic therapy. Conclusions: Pediatric home hospitalization through telemonitoring is a feasible and desirable alternative to traditional hospitalization, both from the perspective of families and the hospital. The results of this analysis showed a very high degree of satisfaction with the care received and that the home-based telemonitoring system resulted in few adverse incidents. %M 32213471 %R 10.2196/17517 %U http://pediatrics.jmir.org/2020/1/e17517/ %U https://doi.org/10.2196/17517 %U http://www.ncbi.nlm.nih.gov/pubmed/32213471 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 9 %N 1 %P e13029 %T Perceived Treatment Satisfaction and Effectiveness Facilitators Among Patients With Chronic Health Conditions: A Self-Reported Survey %A Volpicelli Leonard,Kathryn %A Robertson,Courtney %A Bhowmick,Amrita %A Herbert,Leslie Beth %+ Health Union LLC, 1 International Plaza Dr, #550, Philadelphia, PA, , United States, 1 4849859715, Kate.Leonard@health-union.com %K treatment effectiveness %K patient satisfaction %K migraine %K multiple sclerosis %K rheumatoid arthritis %D 2020 %7 6.3.2020 %9 Original Paper %J Interact J Med Res %G English %X Background: Approximately 50% of patients are nonadherent to prescribed medications. Patient perception regarding medication effectiveness has been linked to improved adherence. However, how patients perceive effectiveness is poorly understood. Objective: The aim of this study was to elucidate factors associated with perceived treatment satisfaction and effectiveness among patients with chronic health conditions. Methods: We conducted a descriptive study using a cross-sectional survey design. We administered a Web-based survey to participants with migraine, multiple sclerosis (MS), or rheumatoid arthritis (RA). Patients were recruited from established online communities of Health Union. Descriptive statistics, correlations, and comparison tests were used to examine outcomes. Results: Data were collected from 1820 patients: 567 with migraine, 717 with MS, and 536 with RA. The majority of participants were female (1644/1820, 90.33%), >40 years old (1462/1820, 80.33%), and diagnosed >5 years ago (1189/1820, 65.33%). Treatment satisfaction and perceived medication effectiveness were highly correlated (r=0.90, P<.01). Overall, three temporal factors were positively correlated with satisfaction or perceived effectiveness: time on current medication (satisfaction rs=0.22, P<.01; effectiveness rs=0.25, P<.01), time since diagnosis (satisfaction rs=0.07, P<.01; effectiveness rs=0.09, P<.01), and time on treatment (effectiveness rs=0.08, P<.01). Conclusions: Findings validated the strong relationship between treatment satisfaction and perceived effectiveness. Understanding the (1) positive relationship between time and treatment satisfaction and effectiveness and (2) factors associated with determining medication effectiveness can help clinicians better understand the mindset of patients regarding treatment. Clinicians may be better prepared to elicit patient beliefs, which influence medication adherence, for people diagnosed with chronic health conditions. %M 32141836 %R 10.2196/13029 %U http://www.i-jmr.org/2020/1/e13029/ %U https://doi.org/10.2196/13029 %U http://www.ncbi.nlm.nih.gov/pubmed/32141836 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 3 %P e15002 %T Improvement of the Efficiency and Completeness of Neuro-Oncology Patient Referrals to a Tertiary Center Through the Implementation of an Electronic Referral System: Retrospective Cohort Study %A Fernández-Méndez,Rocío %A Wong,Mei Yin %A Rastall,Rebecca J %A Rebollo-Díaz,Samuel %A Oberg,Ingela %A Price,Stephen J %A Joannides,Alexis J %+ Department of Clinical Neurosciences, University of Cambridge, Box 165, A Block, Level 3, B Spur, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, United Kingdom, 44 1223746466, rociofmendez.inv@gmail.com %K quality improvement %K electronic health records %K hospital referral %K hospital oncology services %D 2020 %7 5.3.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Quality referrals to specialist care are key for prompt, optimal decisions about the management of patients with brain tumors. Objective: This study aimed to determine the impact of introducing a Web-based, electronic referral (eReferral) system to a specialized neuro-oncology center, using a service-developed proforma, in terms of waiting times and information completeness. Methods: We carried out a retrospective cohort study based on the review of medical records of referred adult patients, excluding follow-ups. Primary outcome measures were durations of three key phases within the referral pathway and completion rates of six referral fields. Results: A total of 248 patients were referred to the specialist center during the study period. Median (IQR) diagnostic imaging to referral intervals were 3 (1-5) days with eReferrals, and 9 (4-19), 19 (14-49), and 8 (4-23) days with paper proforma, paper letter, and internal referrals, respectively (P<.001). Median (IQR) referral to multidisciplinary team decision intervals were 3 (2-7), 2 (1-3), 8 (2-24), and 3 (2-6) days respectively (P=.01). For patients having surgery, median (IQR) diagnostic imaging to surgery intervals were 28 (21-41), 34 (27-51), 104 (69-143), and 32 (15-89) days, respectively (P<.001). Proportions of complete fields differed significantly by referral type in all study fields (all with Ps <.001) except for details of presentation, which were present in all referrals. All study fields were always present in eReferrals, as these are compulsory for referral submission. Depending on the data field, level of completeness in the remaining referral types ranged within 69% (65/94) to 87% (82/94), 15% (3/20) to 65% (13/20), and 22% (8/41) to 63% (26/41) in paper proforma, paper letter, and internal referrals, respectively. Conclusions: An electronic, Web-based, service-developed specific proforma for neuro-oncology referrals performs significantly better, with shorter waiting times and greater completeness of information than other referral types. A wider application of eReferrals is an important first step to streamlining specialist care pathways and providing excellent care. International Registered Report Identifier (IRRID): RR2-10.2196/10.2196/15002 %M 32134389 %R 10.2196/15002 %U https://www.jmir.org/2020/3/e15002 %U https://doi.org/10.2196/15002 %U http://www.ncbi.nlm.nih.gov/pubmed/32134389 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 3 %P e13120 %T The Association Between Health Information Seeking on the Internet and Physician Visits (The Seventh Tromsø Study - Part 4): Population-Based Questionnaire Study %A Yigzaw,Kassaye Yitbarek %A Wynn,Rolf %A Marco-Ruiz,Luis %A Budrionis,Andrius %A Oyeyemi,Sunday Oluwafemi %A Fagerlund,Asbjørn Johansen %A Bellika,Johan Gustav %+ Department of Clinical Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Postboks 6050 Langnes, Tromsø, 9037, Norway, 47 95748049, johan.gustav.bellika@ehealthresearch.no %K eHealth %K internet %K health care service %K physician visit %K Tromsø study %K health information seeking %K Web search engine %K health app %K social media %K video search engine %D 2020 %7 5.3.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: The internet is being widely used for seeking health information. However, there is no consensus on the association between health information seeking on the internet and the use of health care services. Objective: We examined the association between health information seeking via the internet and physician visits. In addition, we investigated the association between online health information seeking and the decisions to visit and not to visit a physician. Methods: We used the cross-sectional electronic health (eHealth) data of 18,197 participants from the seventh survey of the Tromsø Study (Tromsø 7). The participants were aged ≥40 years and living in Tromsø, Norway. We used logistic regression models to examine the association between online health information seeking and physician visits, the decision to visit a physician, and the decision not to visit a physician, with adjustment for the demographic status, socioeconomic status, and health status of the participants. Results: The use of Web search engines was associated with a physician visit. However, the association was moderated by age, and the OR decreased as age increased. The ORs for the use of Web search engines were 1.99 (95% CI 1.94-2.02) and 1.07 (95% CI 1.03-1.12) at ages 40 and 80 years, respectively. The decision to visit a physician was associated with the use of Web search engines (OR 2.95, 95% CI 2.03-4.46), video search engines (OR 1.43, 95% CI 1.21-1.70), and health apps (OR 1.26, 95% CI 1.13-1.42). The association between social media use and the decision to visit a physician was moderated by gender. Women who used social media had 1.42 (95% CI 1.31-1.55) times higher odds of deciding to visit a physician, whereas the decision to visit a physician was not different between men who used social media and those who did not use social media. Conversely, the decision not to visit a physician was associated with the use of Web search engines (OR 2.78, 95% CI 1.92-4.18), video search engines (OR 1.27, 95% CI 1.07-1.51), social media (OR 1.28, 95% CI 1.10-1.49), and health apps (OR 1.20, 95% CI 1.07-1.35). Conclusions: Health information found on the internet was positively associated with both the decision to visit a physician and the decision not to visit a physician. However, the association of health information seeking with the decision to visit a physician was slightly stronger than the association with the decision not to visit a physician. This could imply that the use of eHealth services is associated with a resultant increase in physician visits. In summary, our findings suggest that the internet serves as a supplement to health care services rather than as a replacement. %M 32134387 %R 10.2196/13120 %U https://www.jmir.org/2020/3/e13120 %U https://doi.org/10.2196/13120 %U http://www.ncbi.nlm.nih.gov/pubmed/32134387 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 8 %N 2 %P e14436 %T Just Because (Most) Hospitals Are Publishing Charges Does Not Mean Prices Are More Transparent %A Mullens,Cody Lendon %A Hernandez,J Andres %A Anderson,Evan D %A Allen,Lindsay %+ Center for Public Health Initiatives, University of Pennsylvania, 3620 Hamilton Walk, Philadelphia, PA, , United States, 1 3047238039, cmullen3@mix.wvu.edu %K health care costs %K delivery of health care %K health policy %D 2020 %7 6.2.2020 %9 Original Paper %J JMIR Med Inform %G English %X Background: The Centers for Medicare and Medicaid Services (CMS) recently mandated that all hospitals publish their charge description masters (CDMs) online, in a machine-readable format, by January 1, 2019. In addition, CMS recommended that CDM data be made available in a manner that was consumer friendly and accessible to patients. Objective: This study aimed to (1) examine all hospitals across the state of Pennsylvania to understand policy compliance and (2) use established metrics to measure accessibility and consumer friendliness of posted CDM data. Methods: A cross-sectional analysis was conducted to quantify hospital website compliance with the recent CMS policies requiring hospitals to publish their CDM. Data were collected from all Pennsylvania hospital websites. Consumer friendliness was assessed based on searchability, number of website clicks to data, and supplemental educational materials accompanying CDMs such as videos or text. Results: Most hospitals (189/234, 80.1%) were compliant, but significant variation in data presentation was observed. The mean number of website clicks to the CDM was 3.7 (SD 1.3; range: 1-8). A total of 23.1% of compliant hospitals provided no supplemental educational material with their CDM. Conclusions: Although disclosure of charges has improved, the data may not be sufficient to meaningfully influence patient decision making. %R 10.2196/14436 %U http://medinform.jmir.org/2020/2/e14436/ %U https://doi.org/10.2196/14436 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 22 %N 2 %P e13830 %T What Patients Value in Physicians: Analyzing Drivers of Patient Satisfaction Using Physician-Rating Website Data %A Bidmon,Sonja %A Elshiewy,Ossama %A Terlutter,Ralf %A Boztug,Yasemin %+ Department of Marketing and International Management, Alpen-Adria-Universitaet Klagenfurt, Universitaetsstrasse 65-67, Klagenfurt am Woerthersee, 9020, Austria, 43 463 2700 4048, sonja.bidmon@aau.at %K online physician ratings %K patient satisfaction %K multiattribute models %K health care management %D 2020 %7 3.2.2020 %9 Original Paper %J J Med Internet Res %G English %X Background: Customer-oriented health care management and patient satisfaction have become important for physicians to attract patients in an increasingly competitive environment. Satisfaction influences patients’ choice of physician and leads to higher patient retention and higher willingness to engage in positive word of mouth. In addition, higher satisfaction has positive effects on patients’ willingness to follow the advice given by the physician. In recent years, physician-rating websites (PRWs) have emerged in the health care sector and are increasingly used by patients. Patients’ usage includes either posting an evaluation to provide feedback to others about their own experience with a physician or reading evaluations of other patients before choosing a physician. The emergence of PRWs offers new avenues to analyze patient satisfaction and its key drivers. PRW data enable both satisfaction analyses and implications on the level of the individual physician as well as satisfaction analyses and implications on an overall level. Objective: This study aimed to identify linear and nonlinear effects of patients’ perceived quality of physician appointment service attributes on the overall evaluation measures that are published on PRWs. Methods: We analyzed large-scale survey data from a German PRW containing 84,680 surveys of patients rating a total of 7038 physicians on 24 service attributes and 4 overall evaluation measures. Elasticities are estimated from regression models with perceived attribute quality as explanatory variables and overall evaluation measures as dependent variables. Depending on the magnitude of the elasticity, service attributes are classified into 3 categories: attributes with diminishing, constant, or increasing returns to overall evaluation. Results: The proposed approach revealed new insights into what patients value when visiting physicians and what they take for granted. Improvements in the physicians’ pleasantness and friendliness have increasing returns to the publicly available overall evaluation (b=1.26). The practices’ cleanliness (b=1.05) and the communication behavior of a physician during a visit (b level between .97 and 1.03) have constant returns. Indiscretion in the waiting rooms, extended waiting times, and a lack of modernity of the medical equipment (b level between .46 and .59) have the strongest diminishing returns to overall evaluation. Conclusions: The categorization of the service attributes supports physicians in identifying potential for improvements and prioritizing resource allocation to improve the publicly available overall evaluation ratings on PRWs. Thus, the study contributes to patient-centered health care management and, furthermore, promotes the utility of PRWs through large-scale data analysis. %M 32012063 %R 10.2196/13830 %U https://www.jmir.org/2020/2/e13830 %U https://doi.org/10.2196/13830 %U http://www.ncbi.nlm.nih.gov/pubmed/32012063 %0 Journal Article %@ 2561-1011 %I JMIR Publications %V 3 %N 2 %P e9815 %T Outsourcing the Remote Management of Cardiac Implantable Electronic Devices: Medical Care Quality Improvement Project %A Giannola,Gabriele %A Torcivia,Riccardo %A Airò Farulla,Riccardo %A Cipolla,Tommaso %+ Ospedale San Raffaele Giglio, Contrada Pietra Pollastra, Cefalù, 90015, Italy, 39 0921 920111, cardiologia@hsrgiglio.it %K remote monitoring %K telemonitoring %K cardiac implantable electronic devices %K implantable defibrillators %K pacemaker %K implantable cardioverter defibrillator %K triage outsourcing %K follow-up %D 2019 %7 18.12.2019 %9 Original Paper %J JMIR Cardio %G English %X Background: Remote management is partially replacing routine follow-up in patients implanted with cardiac implantable electronic devices (CIEDs). Although it reduces clinical staff time compared with standard in-office follow-up, a new definition of roles and responsibilities may be needed to review remote transmissions in an effective, efficient, and timely manner. Whether remote triage may be outsourced to an external remote monitoring center (ERMC) is still unclear. Objective: The aim of this health care quality improvement project was to evaluate the feasibility of outsourcing remote triage to an ERMC to improve patient care and health care resource utilization. Methods: Patients (N=153) with implanted CIEDs were followed up for 8 months. An ERMC composed of nurses and physicians reviewed remote transmissions daily following a specific remote monitoring (RM) protocol. A 6-month benchmarking phase where patients’ transmissions were managed directly by hospital staff was evaluated as a term of comparison. Results: A total of 654 transmissions were recorded in the RM system and managed by the ERMC team within 2 working days, showing a significant time reduction compared with standard RM management (100% vs 11%, respectively, within 2 days; P<.001). A total of 84.3% (551/654) of the transmissions did not include a prioritized event and did not require escalation to the hospital clinician. High priority was assigned to 2.3% (15/654) of transmissions, which were communicated to the hospital team by email within 1 working day. Nonurgent device status events occurred in 88 cases and were communicated to the hospital within 2 working days. Of these, 11% (10/88) were followed by a hospitalization. Conclusions: The outsourcing of RM management to an ERMC safely provides efficacy and efficiency gains in patients’ care compared with a standard in-hospital management. Moreover, the externalization of RM management could be a key tool for saving dedicated staff and facility time with possible positive economic impact. Trial Registration: ClinicalTrials.gov NCT01007474; http://clinicaltrials.gov/ct2/show/NCT01007474 %M 31845898 %R 10.2196/cardio.9815 %U https://cardio.jmir.org/2019/2/e9815 %U https://doi.org/10.2196/cardio.9815 %U http://www.ncbi.nlm.nih.gov/pubmed/31845898 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 7 %N 4 %P e13053 %T Measuring Regional Quality of Health Care Using Unsolicited Online Data: Text Analysis Study %A Hendrikx,Roy Johannus Petrus %A Drewes,Hanneke Wil-Trees %A Spreeuwenberg,Marieke %A Ruwaard,Dirk %A Baan,Caroline %+ Tranzo Scientific Center for Care and Welfare, Tilburg University, Warandelaan 2, Tilburg, 5000 LE, Netherlands, 31 611647091, roy.hendrikx@rivm.nl %K text mining %K population health management %K regional care %K quality of care %K online data %K big data %K patient-reported experience measures %D 2019 %7 16.12.2019 %9 Original Paper %J JMIR Med Inform %G English %X Background: Regional population management (PM) health initiatives require insight into experienced quality of care at the regional level. Unsolicited online provider ratings have shown potential for this use. This study explored the addition of comments accompanying unsolicited online ratings to regional analyses. Objective: The goal was to create additional insight for each PM initiative as well as overall comparisons between these initiatives by attempting to determine the reasoning and rationale behind a rating. Methods: The Dutch Zorgkaart database provided the unsolicited ratings from 2008 to 2017 for the analyses. All ratings included both quantitative ratings as well as qualitative text comments. Nine PM regions were used to aggregate ratings geographically. Sentiment analyses were performed by categorizing ratings into negative, neutral, and positive ratings. Per category, as well as per PM initiative, word frequencies (ie, unigrams and bigrams) were explored. Machine learning—naïve Bayes and random forest models—was applied to identify the most important predictors for rating overall sentiment and for identifying PM initiatives. Results: A total of 449,263 unsolicited ratings were available in the Zorgkaart database: 303,930 positive ratings, 97,739 neutral ratings, and 47,592 negative ratings. Bigrams illustrated that feeling like not being “taken seriously” was the dominant bigram in negative ratings, while bigrams in positive ratings were mostly related to listening, explaining, and perceived knowledge. Comparing bigrams between PM initiatives showed a lot of overlap but several differences were identified. Machine learning was able to predict sentiments of comments but was unable to distinguish between specific PM initiatives. Conclusions: Adding information from text comments that accompany online ratings to regional evaluations provides insight for PM initiatives into the underlying reasons for ratings. Text comments provide useful overarching information for health care policy makers but due to a lot of overlap, they add little region-specific information. Specific outliers for some PM initiatives are insightful. %M 31841116 %R 10.2196/13053 %U http://medinform.jmir.org/2019/4/e13053/ %U https://doi.org/10.2196/13053 %U http://www.ncbi.nlm.nih.gov/pubmed/31841116 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 12 %P e13025 %T Understanding the Function Constitution and Influence Factors on Communication for the WeChat Official Account of Top Tertiary Hospitals in China: Cross-Sectional Study %A Shen,Lining %A Wang,Shimin %A Chen,Wenqiang %A Fu,Qiang %A Evans,Richard %A Lan,Fuqiang %A Li,Wei %A Xu,Juan %A Zhang,Zhiguo %+ School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science & Technology, No 13 Hangkong Road, Wuhan, 430030, China, 86 27 83692730, zhangzhiguo@hust.edu.cn %K WeChat official account %K WeChat service account %K social media %K function constitution %K tertiary hospital %K tertiary care centers %K health care %K WeChat communication index %K mobile health %K telemedicine %D 2019 %7 9.12.2019 %9 Original Paper %J J Med Internet Res %G English %X Background: Widespread adoption and continued developments in mobile health care technologies have led to the improved accessibility and quality of medical services. In China, WeChat, an instant messaging and social networking app released by the company Tencent, has developed a specific type of user account called WeChat official account (WOA), which is now widely adopted by hospitals in China. It enables health care providers to connect with local citizens, allowing them to, among other actions, send regular updates through mass circulation. However, with the diversity in function provided by WOA, little is known about its major constitution as well as the influence factors on the WeChat communication index (WCI). The WCI has been widely used in social media impact ranking with various types of WeChat content to fully reflect the dissemination and coverage of tweets as well as the maturity and impact of WOA. Objective: There are two typical WOAs available to users, namely, WeChat subscription account (WSSA) and WeChat service account (WSVA). The biggest difference between them is the frequency of messages transmitted. This study aimed to explore the function constitution of WSVA adopted by top tertiary hospitals in China and the major contributors of the WCI score. Methods: A total of 681 top tertiary hospitals were selected from the Hospital Quality Monitoring System; the WOA of every top tertiary hospital was retrieved in the WeChat app. We divided core functional items of WSVAs using categorical principal component analysis. To elicit the factors that influenced the use of WSVA, quantile regression was employed to analyze the WCI score. Results: From the 668 WOAs identified, adoption of WSVAs (543/668, 81.3%) was more than that of WSSAs (125/668, 18.7%). Functional items of WSVAs were categorized into four clusters: (1) hospital introduction, (2) medical services, (3) visiting assistants, and (4) others. With regard to the influence factors on the WCI, the impact of the activity index of WSVA and the total visiting number of outpatients and emergencies on WCI were statistically significant and positive in all quantiles. However, the year of certification, the type of hospital, the year of public hospital reform, and the number of beds merely affected the WCI at some quantiles. Conclusions: Our findings are considered helpful to tertiary hospitals in developing in-depth functional items that improve patient experience. The tertiary hospitals should take full advantage of times of posting and provide high-quality tweets to meet the various needs of patients. %M 31815674 %R 10.2196/13025 %U https://www.jmir.org/2019/12/e13025 %U https://doi.org/10.2196/13025 %U http://www.ncbi.nlm.nih.gov/pubmed/31815674 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 7 %N 4 %P e16185 %T How Online Reviews and Services Affect Physician Outpatient Visits: Content Analysis of Evidence From Two Online Health Care Communities %A Lu,Wei %A Wu,Hong %+ School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Qiaokou District, Hubei Province, Wuhan, 430060, China, 86 132 7794 2186, wuhong634214924@163.com %K online health care communities %K online reviews %K online services %K outpatient care %K channel effect %K patient choice %D 2019 %7 2.12.2019 %9 Original Paper %J JMIR Med Inform %G English %X Background: Online healthcare communities are changing the ways of physician-patient communication and how patients choose outpatient care physicians. Although a majority of empirical work has examined the role of online reviews in consumer decisions, less research has been done in health care, and endogeneity of online reviews has not been fully considered. Moreover, the important factor of physician online services has been neglected in patient decisions. Objective: In this paper, we addressed the endogeneity of online reviews and examined the impact of online reviews and services on outpatient visits based on theories of reviews and channel effects. Methods: We used a difference-in-difference approach to account for physician- and website-specific effects by collecting information from 474 physician homepages on two online health care communities. Results: We found that the number of reviews was more effective in influencing patient decisions compared with the overall review rating. An improvement in reviews leads to a relative increase in physician outpatient visits on that website. There are channel effects in health care: online services complement offline services (outpatient care appointments). Results further indicate that online services moderate the relationship between online reviews and physician outpatient visits. Conclusions: This study investigated the effect of reviews and channel effects in health care by conducting a difference-in-difference analysis on two online health care communities. Our findings provide basic research on online health care communities. %M 31789597 %R 10.2196/16185 %U http://medinform.jmir.org/2019/4/e16185/ %U https://doi.org/10.2196/16185 %U http://www.ncbi.nlm.nih.gov/pubmed/31789597 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 9 %P e14135 %T Health Care Professionals’ Perspectives on the Secondary Use of Health Records to Improve Quality and Safety of Care in England: Qualitative Study %A Neves,Ana Luísa %A Poovendran,Dilkushi %A Freise,Lisa %A Ghafur,Saira %A Flott,Kelsey %A Darzi,Ara %A Mayer,Erik K %+ Patient Safety Translational Research Centre, Institute of Global Health Innovation, Imperial College London, St Mary’s Campus, Queen Elizabeth Queen Mother Wing, London, W2 1NY, United Kingdom, 44 (0)20 7589 5111, ana.luisa.neves14@ic.ac.uk %K electronic health records %K information technology %K health policy %K safety culture %D 2019 %7 26.9.2019 %9 Original Paper %J J Med Internet Res %G English %X Background: Health care professionals (HCPs) are often patients’ first point of contact in what concerns the communication of the purposes, benefits, and risks of sharing electronic health records (EHRs) for nondirect care purposes. Their engagement is fundamental to ensure patients’ buy-in and a successful implementation of health care data sharing schemes. However, their views on this subject are seldom evaluated. Objective: This study aimed to explore HCPs’ perspectives on the secondary uses of health care data in England. Specifically, we aimed to assess their knowledge on its purposes and the main concerns about data sharing processes. Methods: A total of 30 interviews were conducted between March 27, 2017, and April 7, 2017, using a Web-based interview platform and following a topic guide with open-ended questions. The participants represented a variety of geographic locations across England (London, West Midlands, East of England, North East England, and Yorkshire and the Humber), covering both primary and secondary care services. The transcripts were compiled verbatim and systematically reviewed by 2 independent reviewers using the framework analysis method to identify emerging themes. Results: HCPs were knowledgeable about the possible secondary uses of data and highlighted its importance for patient profiling and tailored care, research, quality assurance, public health, and service delivery planning purposes. Main concerns toward data sharing included data accuracy, patients’ willingness to share their records, challenges on obtaining free and informed consent, data security, lack of adequacy or understanding of current policies, and potential patient exposure and exploitation. Conclusions: These results suggest a high level of HCPs’ understanding about the purposes of data sharing for secondary purposes; however, some concerns still remain. A better understanding of HCPs’ knowledge and concerns could inform national communication policies and improve tailoring to maximize efficiency and improve patients’ buy-in. %M 31573898 %R 10.2196/14135 %U https://www.jmir.org/2019/9/e14135 %U https://doi.org/10.2196/14135 %U http://www.ncbi.nlm.nih.gov/pubmed/31573898 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 7 %N 3 %P e14192 %T Implementation and Effectiveness of a Bar Code–Based Transfusion Management System for Transfusion Safety in a Tertiary Hospital: Retrospective Quality Improvement Study %A Chou,Shin-Shang %A Chen,Ying-Ju %A Shen,Yu-Te %A Yen,Hsiu-Fang %A Kuo,Shu-Chen %+ Department of Nursing, Taipei Veterans General Hospital, No 201, Section 2, Shipai Road, Beitou District, Taipei City, 112, Taiwan, 886 2 28587000 ext 7105, shinshang.chou@gmail.com %K blood transfusion safety %K barcode technology %K quality improvement %D 2019 %7 26.08.2019 %9 Original Paper %J JMIR Med Inform %G English %X Background: Large-scale and long-term studies are not sufficient to determine the efficiency that IT solutions can bring to transfusion safety. Objective: This quality-improvement report describes our continuous efforts to implement and upgrade a bar code–based transfusion management (BCTM) system since 2011 and examines its effectiveness and sustainability in reducing blood transfusion errors, in a 3000-bed tertiary hospital, where more than 60,000 prescriptions of blood transfusion are covered by 2500 nurses each year. Methods: The BCTM system uses barcodes for patient identification, onsite labeling, and blood product verification, through wireless connection to the hospital information systems. Plan-Do-Study-Act (PDSA) cycles were used to improve the process. Process maps before and after implementation of the BCTM system in 2011 were drawn to highlight the changes. The numbers of incorrect labeling or wrong blood in tube incidents that occurred quarterly were plotted on a run chart to monitor the quality changes of each intervention introduced. The annual occurrences of error events from 2011 to 2017 were compared with the mean occurrence of 2008-2010 to determine whether implementation of the BCTM system could effectively reduce the number of errors in 2016 and whether this reduction could persist in 2017. Results: The error rate decreased from 0.03% in 2008-2010 to 0.002% in 2016 (P<.001) and 0.001% in 2017 (P<.001) after implementation of the BTCM system. Only one incorrect labeling incident was noted among the 68,324 samples for blood typing, and no incorrect transfusions occurred among 67,423 transfusion orders in 2017. Conclusions: This report demonstrates that continuous efforts to upgrade the existing process is critical to reduce errors in transfusion therapy, with support from information technology. %M 31452517 %R 10.2196/14192 %U http://medinform.jmir.org/2019/3/e14192/ %U https://doi.org/10.2196/14192 %U http://www.ncbi.nlm.nih.gov/pubmed/31452517 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 21 %N 8 %P e14634 %T What Do Patients Complain About Online: A Systematic Review and Taxonomy Framework Based on Patient Centeredness %A Liu,Jing %A Hou,Shengchao %A Evans,Richard %A Xia,Chenxi %A Xia,Weidong %A Ma,Jingdong %+ School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, No 13 Hangkong Road, Qiaokou District, Wuhan,, China, 86 27 83692826, jdma@hust.edu.cn %K patient-centered care %K delivery of health care %K systematic review %K taxonomy %D 2019 %7 07.08.2019 %9 Review %J J Med Internet Res %G English %X Background: Complaints made online by patients about their health care experiences are becoming prevalent because of widespread worldwide internet connectivity. An a priori framework, based on patient centeredness, may be useful in identifying the types of issues patients complain about online across multiple settings. It may also assist in examining whether the determinants of patient-centered care (PCC) mirror the determinants of patient experiences. Objective: The objective of our study was to develop a taxonomy framework for patient complaints online based on patient centeredness and to examine whether the determinants of PCC mirror the determinants of patient experiences. Methods: First, the best fit framework synthesis technique was applied to develop the proposed a priori framework. Second, electronic databases, including Web of Science, Scopus, and PubMed, were searched for articles published between 2000 and June 2018. Studies were only included if they collected primary quantitative data on patients’ online complaints. Third, a deductive and inductive thematic analysis approach was adopted to code the themes of recognized complaints into the framework. Results: In total, 17 studies from 5 countries were included in this study. Patient complaint online taxonomies and theme terms varied. According to our framework, patients expressed most dissatisfaction with patient-centered processes (101,586/204,363, 49.71%), followed by prerequisites (appropriate skills and knowledge of physicians; 50,563, 24.74%) and the care environment (48,563/204,363, 23.76%). The least dissatisfied theme was expected outcomes (3651/204,363, 1.79%). People expressed little dissatisfaction with expanded PCC dimensions, such as involvement of family and friends (591/204,363, 0.29%). Variation in the concerns across different countries’ patients were also observed. Conclusions: Online complaints made by patients are of major value to health care providers, regulatory bodies, and patients themselves. Our PCC framework can be applied to analyze them under a wide range of conditions, treatments, and countries. This review has shown significant heterogeneity of patients’ online complaints across different countries. %M 31392961 %R 10.2196/14634 %U https://www.jmir.org/2019/8/e14634/ %U https://doi.org/10.2196/14634 %U http://www.ncbi.nlm.nih.gov/pubmed/31392961 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 6 %N 4 %P e44 %T A Computerized Method for Measuring Computed Tomography Pulmonary Angiography Yield in the Emergency Department: Validation Study %A Richardson,Safiya %A Solomon,Philip %A O'Connell,Alexander %A Khan,Sundas %A Gong,Jonathan %A Makhnevich,Alex %A Qiu,Guang %A Zhang,Meng %A McGinn,Thomas %+ Department of Medicine, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, 500 Hofstra University, Hempstead, NY, 11549, United States, 1 4046957883, srichard12@northwell.edu %K health informatics %K pulmonary embolism %K electronic health record %K quality improvement %K clinical decision support systems %D 2018 %7 25.10.2018 %9 Original Paper %J JMIR Med Inform %G English %X Background: Use of computed tomography pulmonary angiography (CTPA) in the assessment of pulmonary embolism (PE) has markedly increased over the past two decades. While this technology has improved the accuracy of radiological testing for PE, CTPA also carries the risk of substantial iatrogenic harm. Each CTPA carries a 14% risk of contrast-induced nephropathy and a lifetime malignancy risk that can be as high as 2.76%. The appropriate use of CTPA can be estimated by monitoring the CTPA yield, the percentage of tests positive for PE. This is the first study to propose and validate a computerized method for measuring the CTPA yield in the emergency department (ED). Objective: The objective of our study was to assess the validity of a novel computerized method of calculating the CTPA yield in the ED. Methods: The electronic health record databases at two tertiary care academic hospitals were queried for CTPA orders completed in the ED over 1-month periods. These visits were linked with an inpatient admission with a discharge diagnosis of PE based on the International Classification of Diseases codes. The computerized the CTPA yield was calculated as the number of CTPA orders with an associated inpatient discharge diagnosis of PE divided by the total number of orders for completed CTPA. This computerized method was then validated by 2 independent reviewers performing a manual chart review, which included reading the free-text radiology reports for each CTPA. Results: A total of 349 CTPA orders were completed during the 1-month periods at the two institutions. Of them, acute PE was diagnosed on CTPA in 28 studies, with a CTPA yield of 7.7%. The computerized method correctly identified 27 of 28 scans positive for PE. The one discordant scan was tied to a patient who was discharged directly from the ED and, as a result, never received an inpatient discharge diagnosis. Conclusions: This is the first successful validation study of a computerized method for calculating the CTPA yield in the ED. This method for data extraction allows for an accurate determination of the CTPA yield and is more efficient than manual chart review. With this ability, health care systems can monitor the appropriate use of CTPA and the effect of interventions to reduce overuse and decrease preventable iatrogenic harm. %M 30361200 %R 10.2196/medinform.9957 %U http://medinform.jmir.org/2018/4/e44/ %U https://doi.org/10.2196/medinform.9957 %U http://www.ncbi.nlm.nih.gov/pubmed/30361200 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 20 %N 7 %P e240 %T Evaluating Doctor Performance: Ordinal Regression-Based Approach %A Shi,Yong %A Li,Peijia %A Yu,Xiaodan %A Wang,Huadong %A Niu,Lingfeng %+ Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, 80 Zhongguancun East Road, Haidian District, Beijing, 100190, China, 86 15600616246, niulf@ucas.ac.cn %K performance evaluation %K ordinal regression %K mHealth %K support vector machines %K ordinal partitioning %D 2018 %7 18.07.2018 %9 Original Paper %J J Med Internet Res %G English %X Background: Doctor’s performance evaluation is an important task in mobile health (mHealth), which aims to evaluate the overall quality of online diagnosis and patient outcomes so that customer satisfaction and loyalty can be attained. However, most patients tend not to rate doctors’ performance, therefore, it is imperative to develop a model to make doctor’s performance evaluation automatic. When evaluating doctors’ performance, we rate it into a score label that is as close as possible to the true one. Objective: This study aims to perform automatic doctor’s performance evaluation from online textual consultations between doctors and patients by way of a novel machine learning method. Methods: We propose a solution that models doctor’s performance evaluation as an ordinal regression problem. In doing so, a support vector machine combined with an ordinal partitioning model (SVMOP), along with an innovative predictive function will be developed to capture the hidden preferences of the ordering labels over doctor’s performance evaluation. When engineering the basic text features, eight customized features (extracted from over 70,000 medical entries) were added and further boosted by the Gradient Boosting Decision Tree algorithm. Results: Real data sets from one of the largest mobile doctor/patient communication platforms in China are used in our study. Statistically, 64% of data on mHealth platforms lack the evaluation labels from patients. Experimental results reveal that our approach can support an automatic doctor performance evaluation. Compared with other auto-evaluation models, SVMOP improves mean absolute error (MAE) by 0.1, mean square error (MSE) by 0.5, pairwise accuracy (PAcc) by 5%; the suggested customized features improve MAE by 0.1, MSE by 0.2, PAcc by 3%. After boosting, performance is further improved. Based on SVMOP, predictive features like politeness and sentiment words can be mined, which can be further applied to guide the development of mHealth platforms. Conclusions: The initial modelling of doctor performance evaluation is an ordinal regression problem. Experiments show that the performance of our proposed model with revised prediction function is better than many other machine learning methods on MAE, MSE, as well as PAcc. With this model, the mHealth platform could not only make an online auto-evaluation of physician performance, but also obtain the most effective features, thereby guiding physician performance and the development of mHealth platforms. %M 30021708 %R 10.2196/jmir.9300 %U http://www.jmir.org/2018/7/e240/ %U https://doi.org/10.2196/jmir.9300 %U http://www.ncbi.nlm.nih.gov/pubmed/30021708 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 6 %N 2 %P e40 %T The Impact of Implementation of a Clinically Integrated Problem-Based Neonatal Electronic Health Record on Documentation Metrics, Provider Satisfaction, and Hospital Reimbursement: A Quality Improvement Project %A Liu,William %A Walsh,Thomas %+ Neonatology, Golisano Children's Hospital of Southwest Florida, Lee Health, 9981 South HealthPark Drive, Suite NICU, 3rd Floor, Fort Myers, FL, 33908, United States, 1 2393436684, william.liu.md@leehealth.org %K electronic health record %K neonatal intensive care unit %K NICU %K physician documentation %K Epic %K SOI %K ROM %K CMI %K APR-DRG %K informatics %D 2018 %7 20.06.2018 %9 Original Paper %J JMIR Med Inform %G English %X Background: A goal of effective electronic health record provider documentation platforms is to provide an efficient, concise, and comprehensive notation system that will effectively reflect the clinical course, including the diagnoses, treatments, and interventions. Objective: The aim is to fully redesign and standardize the provider documentation process, seeking improvement in documentation based on ongoing All Patient Refined Diagnosis Related Group–based coding records, while maintaining noninferiority comparing provider satisfaction to our existing documentation process. We estimated the fiscal impact of improved documentation based on changes in expected hospital payments. Methods: Employing a multidisciplinary collaborative approach, we created an integrated clinical platform that captures data entry from the obstetrical suite, delivery room, neonatal intensive care unit (NICU) nursing and respiratory therapy staff. It provided the sole source for hospital provider documentation in the form of a history and physical exam, daily progress notes, and discharge summary. Health maintenance information, follow-up appointments, and running contemporaneous updated hospital course information have selected shared entry and common viewing by the NICU team. The interventions were to (1) improve provider awareness of appropriate documentation through a provider education handout and follow-up group discussion and (2) fully redesign and standardize the provider documentation process building from the native Epic-based software. The measures were (1) hospital coding department review of all NICU admissions and 3M All Patient Refined Diagnosis Related Group–based calculations of severity of illness, risk of mortality, and case mix index scores; (2) balancing measure: provider time utilization case study and survey; and (3) average expected hospital payment based on acuity-based clinical logic algorithm and payer mix. Results: We compared preintervention (October 2015-October 2016) to postintervention (November 2016-May 2017) time periods and saw: (1) significant improvement in All Patient Refined Diagnosis Related Group–derived severity of illness, risk of mortality, and case mix index (monthly average severity of illness scores increased by 11.1%, P=.008; monthly average risk of mortality scores increased by 13.5%, P=.007; and monthly average case mix index scores increased by 7.7%, P=.009); (2) time study showed increased time to complete history and physical and progress notes and decreased time to complete discharge summary (history and physical exam: time allocation increased by 47%, P=.05; progress note: time allocation increased by 91%, P<.001; discharge summary: time allocation decreased by 41%, P=.03); (3) survey of all providers: overall there was positive provider perception of the new documentation process based on a survey of the provider group; (4) significantly increased hospital average expected payments: comparing the preintervention and postintervention study periods, there was a US $14,020 per month per patient increase in average expected payment for hospital charges (P<.001). There was no difference in payer mix during this time period. Conclusions: A problem-based NICU documentation electronic health record more effectively improves documentation without dissatisfaction by the participating providers and improves hospital estimations of All Patient Refined Diagnosis Related Group–based revenue. %M 29925495 %R 10.2196/medinform.9776 %U http://medinform.jmir.org/2018/2/e40/ %U https://doi.org/10.2196/medinform.9776 %U http://www.ncbi.nlm.nih.gov/pubmed/29925495 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 6 %N 2 %P e10264 %T Health Information Technology in Healthcare Quality and Patient Safety: Literature Review %A Feldman,Sue S %A Buchalter,Scott %A Hayes,Leslie W %+ Department of Health Services Administration, The University of Alabama at Birmingham, 1716 9th Avenue, SHPB #590K, Birmingham, AL, 35294, United States, 1 6616188805, suefeldman1009@gmail.com %K Health Information Technology %K Healthcare Quality %K Patient Safety %D 2018 %7 04.06.2018 %9 Review %J JMIR Med Inform %G English %X Background: The area of healthcare quality and patient safety is starting to use health information technology to prevent reportable events, identify them before they become issues, and act on events that are thought to be unavoidable. As healthcare organizations begin to explore the use of health information technology in this realm, it is often unclear where fiscal and human efforts should be focused. Objective: The purpose of this study was to provide a foundation for understanding where to focus health information technology fiscal and human resources as well as expectations for the use of health information technology in healthcare quality and patient safety. Methods: A literature review was conducted to identify peer-reviewed publications reporting on the actual use of health information technology in healthcare quality and patient safety. Inductive thematic analysis with open coding was used to categorize a total of 41 studies. Three pre-set categories were used: prevention, identification, and action. Three additional categories were formed through coding: challenges, outcomes, and location. Results: This study identifies five main categories across seven study settings. A majority of the studies used health IT for identification and prevention of healthcare quality and patient safety issues. In this realm, alerts, clinical decision support, and customized health IT solutions were most often implemented. Implementation, interface design, and culture were most often noted as challenges. Conclusions: This study provides valuable information as organizations determine where they stand to get the most “bang for their buck” relative to health IT for quality and patient safety. Knowing what implementations are being effectivity used by other organizations helps with fiscal and human resource planning as well as managing expectations relative to cost, scope, and outcomes. The findings from this scan of the literature suggest that having organizational champion leaders that can shepherd implementation, impact culture, and bridge knowledge with developers would be a valuable resource allocation to consider. %R 10.2196/10264 %U http://medinform.jmir.org/2018/2/e10264/ %U https://doi.org/10.2196/10264 %0 Journal Article %@ 2292-9495 %I JMIR Publications %V 5 %N 2 %P e22 %T The Impact of Visualization Dashboards on Quality of Care and Clinician Satisfaction: Integrative Literature Review %A Khairat,Saif Sherif %A Dukkipati,Aniesha %A Lauria,Heather Alico %A Bice,Thomas %A Travers,Debbie %A Carson,Shannon S %+ University of North Carolina at Chapel Hill, 428 Carrington Hall, Chapel Hill, NC, 27514, United States, 1 919843514, saif@unc.edu %K intensive care unit %K visualization, Dashboard %K cognitive load %K information overload %K usability %K user interface design %K health information technology %K electronic health record %D 2018 %7 31.05.2018 %9 Review %J JMIR Hum Factors %G English %X Background: Intensive Care Units (ICUs) in the United States admit more than 5.7 million people each year. The ICU level of care helps people with life-threatening illness or injuries and involves close, constant attention by a team of specially-trained health care providers. Delay between condition onset and implementation of necessary interventions can dramatically impact the prognosis of patients with life-threatening diagnoses. Evidence supports a connection between information overload and medical errors. A tool that improves display and retrieval of key clinical information has great potential to benefit patient outcomes. The purpose of this review is to synthesize research on the use of visualization dashboards in health care. Objective: The purpose of conducting this literature review is to synthesize previous research on the use of dashboards visualizing electronic health record information for health care providers. A review of the existing literature on this subject can be used to identify gaps in prior research and to inform further research efforts on this topic. Ultimately, this evidence can be used to guide the development, testing, and implementation of a new solution to optimize the visualization of clinical information, reduce clinician cognitive overload, and improve patient outcomes. Methods: Articles were included if they addressed the development, testing, implementation, or use of a visualization dashboard solution in a health care setting. An initial search was conducted of literature on dashboards only in the intensive care unit setting, but there were not many articles found that met the inclusion criteria. A secondary follow-up search was conducted to broaden the results to any health care setting. The initial and follow-up searches returned a total of 17 articles that were analyzed for this literature review. Results: Visualization dashboard solutions decrease time spent on data gathering, difficulty of data gathering process, cognitive load, time to task completion, errors, and improve situation awareness, compliance with evidence-based safety guidelines, usability, and navigation. Conclusions: Researchers can build on the findings, strengths, and limitations of the work identified in this literature review to bolster development, testing, and implementation of novel visualization dashboard solutions. Due to the relatively few studies conducted in this area, there is plenty of room for researchers to test their solutions and add significantly to the field of knowledge on this subject. %R 10.2196/humanfactors.9328 %U http://humanfactors.jmir.org/2018/2/e22/ %U https://doi.org/10.2196/humanfactors.9328 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 6 %N 2 %P e35 %T Perspectives of Nurses Toward Telehealth Efficacy and Quality of Health Care: Pilot Study %A Bashir,Ayisha %A Bastola,Dhundy R %+ Department of Clinical and Translational Science, Creighton University, 2500 California Plaza, Omaha, NE, 68178, United States, 1 4027407394, abashir@unomaha.edu %K telehealth %K survey %K telemedicine %K telenursing %D 2018 %7 25.05.2018 %9 Original Paper %J JMIR Med Inform %G English %X Background: Telehealth nursing, or the delivery, management, and coordination of nursing care services provided via telecommunications technology, is one of the methods of delivering health care to patients in the United States. It is important to assess the service quality of the involved health professionals as well as the telehealth nursing process. The focus of this study is the innovative model of telehealth care delivery by nurses for managing patients with chronic disease while they are living in their own residence. Objective: The primary objective of this pilot study was to examine whether telehealth technology impacts the perceived level of internal service quality delivered by nurses within a telehealth organization. To address this research goal, the notion of telehealth nursing service quality (TNSQ) is empirically tested and validated with a survey instrument. Methods: Data were collected from nurses belonging to a home care agency based on interview questions inquiring about facilitators and inhibitors to TNSQ. A survey to measure TNSQ based on the SERVQUAL instrument was completed by adjusting descriptions of the original instrument to suit the context. Follow-up interviews were conducted to validate questions on the revised instrument. Results: The findings of this survey research were positive, based on mean differences between expectations and perceptions of TNSQ. This indicates satisfaction with TNSQ and shows that the quality of the service is higher than what the respondents expect. The Wilcoxon signed-rank test using the P value for the test, which is .35, did not show a statistically significant change between the median differences of perception and expectation. The total number of respondents was 13. Results indicate that overall perceived service quality is a positive value (0.05332). This means the perceptions of the level of service are slightly higher than what they expect, indicating there is satisfaction with TNSQ. Conclusions: The responses to the interview questions and data gathered from the survey showed overall satisfaction with TNSQ. The SERVQUAL instrument was a good framework to assess TNSQ. In a nutshell, the study highlighted how the telehealth process provides daily monitoring of patient health, leading to the benefits of immediate feedback for patients, family, and caregivers as well as convenience of scheduling. %M 29802089 %R 10.2196/medinform.9080 %U http://medinform.jmir.org/2018/2/e35/ %U https://doi.org/10.2196/medinform.9080 %U http://www.ncbi.nlm.nih.gov/pubmed/29802089 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 20 %N 5 %P e176 %T Differences in Online Consumer Ratings of Health Care Providers Across Medical, Surgical, and Allied Health Specialties: Observational Study of 212,933 Providers %A Daskivich,Timothy %A Luu,Michael %A Noah,Benjamin %A Fuller,Garth %A Anger,Jennifer %A Spiegel,Brennan %+ Division of Urology, Cedars-Sinai Medical Center, 8635 West 3rd Street, Suite 1070W, Los Angeles, CA, 90048, United States, 1 310 423 4700, timothy.daskivich@csmc.edu %K online ratings %K consumer ratings %K patient satisfaction %K digital health %K telemedicine %D 2018 %7 09.05.2018 %9 Original Paper %J J Med Internet Res %G English %X Background: Health care consumers are increasingly using online ratings to select providers, but differences in the distribution of scores across specialties and skew of the data have the potential to mislead consumers about the interpretation of ratings. Objective: The objective of our study was to determine whether distributions of consumer ratings differ across specialties and to provide specialty-specific data to assist consumers and clinicians in interpreting ratings. Methods: We sampled 212,933 health care providers rated on the Healthgrades consumer ratings website, representing 29 medical specialties (n=128,678), 15 surgical specialties (n=72,531), and 6 allied health (nonmedical, nonnursing) professions (n=11,724) in the United States. We created boxplots depicting distributions and tested the normality of overall patient satisfaction scores. We then determined the specialty-specific percentile rank for scores across groupings of specialties and individual specialties. Results: Allied health providers had higher median overall satisfaction scores (4.5, interquartile range [IQR] 4.0-5.0) than physicians in medical specialties (4.0, IQR 3.3-4.5) and surgical specialties (4.2, IQR 3.6-4.6, P<.001). Overall satisfaction scores were highly left skewed (normal between –0.5 and 0.5) for all specialties, but skewness was greatest among allied health providers (–1.23, 95% CI –1.280 to –1.181), followed by surgical (–0.77, 95% CI –0.787 to –0.755) and medical specialties (–0.64, 95% CI –0.648 to –0.628). As a result of the skewness, the percentages of overall satisfaction scores less than 4 were only 23% for allied health, 37% for surgical specialties, and 50% for medical specialties. Percentile ranks for overall satisfaction scores varied across specialties; percentile ranks for scores of 2 (0.7%, 2.9%, 0.8%), 3 (5.8%, 16.6%, 8.1%), 4 (23.0%, 50.3%, 37.3%), and 5 (63.9%, 89.5%, 86.8%) differed for allied health, medical specialties, and surgical specialties, respectively. Conclusions: Online consumer ratings of health care providers are highly left skewed, fall within narrow ranges, and differ by specialty, which precludes meaningful interpretation by health care consumers. Specialty-specific percentile ranks may help consumers to more meaningfully assess online physician ratings. %M 29743150 %R 10.2196/jmir.9160 %U http://www.jmir.org/2018/5/e176/ %U https://doi.org/10.2196/jmir.9160 %U http://www.ncbi.nlm.nih.gov/pubmed/29743150 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 20 %N 1 %P e16 %T Evaluation Criteria of Noninvasive Telemonitoring for Patients With Heart Failure: Systematic Review %A Farnia,Troskah %A Jaulent,Marie-Christine %A Steichen,Olivier %+ Department of Internal Medicine, Hôpital Tenon, Assistance Publique-Hôpitaux de Paris, 4 Rue de la Chine, Paris,, France, 33 1 56 01 78 31, olivier.steichen@aphp.fr %K telemedicine %K outcome and process assessment (health care) %K program evaluation %K heart failure %D 2018 %7 16.01.2018 %9 Review %J J Med Internet Res %G English %X Background: Telemonitoring can improve heart failure (HF) management, but there is no standardized evaluation framework to comprehensively evaluate its impact. Objective: Our objectives were to list the criteria used in published evaluations of noninvasive HF telemonitoring projects, describe how they are used in the evaluation studies, and organize them into a consistent scheme. Methods: Articles published from January 1990 to August 2015 were obtained through MEDLINE, Web of Science, and EMBASE. Articles were eligible if they were original reports of a noninvasive HF telemonitoring evaluation study in the English language. Studies of implantable telemonitoring devices were excluded. Each selected article was screened to extract the description of the telemonitoring project and the evaluation process and criteria. A qualitative synthesis was performed. Results: We identified and reviewed 128 articles leading to 52 evaluation criteria classified into 6 dimensions: clinical, economic, user perspective, educational, organizational, and technical. The clinical and economic impacts were evaluated in more than 70% of studies, whereas the educational, organizational, and technical impacts were studied in fewer than 15%. User perspective was the most frequently covered dimension in the development phase of telemonitoring projects, whereas clinical and economic impacts were the focus of later phases. Conclusions: Telemonitoring evaluation frameworks should cover all 6 dimensions appropriately distributed along the telemonitoring project lifecycle. Our next goal is to build such a comprehensive evaluation framework for telemonitoring and test it on an ongoing noninvasive HF telemonitoring project. %M 29339348 %R 10.2196/jmir.7873 %U http://www.jmir.org/2018/1/e16/ %U https://doi.org/10.2196/jmir.7873 %U http://www.ncbi.nlm.nih.gov/pubmed/29339348 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 6 %N 1 %P e5 %T Automating Quality Measures for Heart Failure Using Natural Language Processing: A Descriptive Study in the Department of Veterans Affairs %A Garvin,Jennifer Hornung %A Kim,Youngjun %A Gobbel,Glenn Temple %A Matheny,Michael E %A Redd,Andrew %A Bray,Bruce E %A Heidenreich,Paul %A Bolton,Dan %A Heavirland,Julia %A Kelly,Natalie %A Reeves,Ruth %A Kalsy,Megha %A Goldstein,Mary Kane %A Meystre,Stephane M %+ Health Information Management and Systems Division, School of Health and Rehabilitation Sciences, The Ohio State University, 453 W 10th Ave, Columbus, OH, 43210, United States, 1 2156203390, jennifer.garvin@hsc.utah.edu %K natural language processing (NLP) %K heart failure %K left ventricular ejection fraction (EF) %K informatics %K quality measures %D 2018 %7 15.01.2018 %9 Original Paper %J JMIR Med Inform %G English %X Background: We developed an accurate, stakeholder-informed, automated, natural language processing (NLP) system to measure the quality of heart failure (HF) inpatient care, and explored the potential for adoption of this system within an integrated health care system. Objective: To accurately automate a United States Department of Veterans Affairs (VA) quality measure for inpatients with HF. Methods: We automated the HF quality measure Congestive Heart Failure Inpatient Measure 19 (CHI19) that identifies whether a given patient has left ventricular ejection fraction (LVEF) <40%, and if so, whether an angiotensin-converting enzyme inhibitor or angiotensin-receptor blocker was prescribed at discharge if there were no contraindications. We used documents from 1083 unique inpatients from eight VA medical centers to develop a reference standard (RS) to train (n=314) and test (n=769) the Congestive Heart Failure Information Extraction Framework (CHIEF). We also conducted semi-structured interviews (n=15) for stakeholder feedback on implementation of the CHIEF. Results: The CHIEF classified each hospitalization in the test set with a sensitivity (SN) of 98.9% and positive predictive value of 98.7%, compared with an RS and SN of 98.5% for available External Peer Review Program assessments. Of the 1083 patients available for the NLP system, the CHIEF evaluated and classified 100% of cases. Stakeholders identified potential implementation facilitators and clinical uses of the CHIEF. Conclusions: The CHIEF provided complete data for all patients in the cohort and could potentially improve the efficiency, timeliness, and utility of HF quality measurements. %M 29335238 %R 10.2196/medinform.9150 %U http://medinform.jmir.org/2018/1/e5/ %U https://doi.org/10.2196/medinform.9150 %U http://www.ncbi.nlm.nih.gov/pubmed/29335238 %0 Journal Article %@ 2291-5222 %I JMIR Publications %V 5 %N 12 %P e188 %T The Swedish Web Version of the Quality of Recovery Scale Adapted for Use in a Mobile App: Prospective Psychometric Evaluation Study %A Nilsson,Ulrica %A Dahlberg,Karuna %A Jaensson,Maria %+ School of Health Sciences, Faculty of Medicine and Health, Örebro University, Fakultetsgatan, Örebro, 70182, Sweden, 46 762132685, ulrica.nilsson@oru.se %K psychometric evaluation %K postoperative recovery %K Web version %K evaluation studies %K mobile application %K Quality of Recovery scale %D 2017 %7 3.12.2017 %9 Original Paper %J JMIR Mhealth Uhealth %G English %X Background: The 40-item Quality of Recovery (QoR-40) questionnaire is well validated for measuring self-assessed postoperative recovery. The Swedish version of the 40-item Quality of Recovery (QoR-40) has been developed into a Web-based questionnaire, the Swedish Web version of the Quality of Recovery (SwQoR) questionnaire, adapted for use in a mobile app, Recovery Assessment by Phone Points, or RAPP. Objective: The aim of this study was to test the validity, reliability, responsiveness, and clinical acceptability and feasibility of SwQoR. Methods: We conducted a prospective psychometric evaluation study including 494 patients aged ≥18 years undergoing day surgery at 4 different day-surgery departments in Sweden. SwQoR was completed daily on postoperative days 1 to 14. Results: All a priori hypotheses were confirmed, supporting convergent validity. There was excellent internal consistency (Cronbach alpha range .91-.93), split-half reliability (coefficient range .87-.93), and stability (ri=.99, 95% CI .96-.99; P<.001). Cohen d effect size was 1.00, with a standardized response mean of 1.2 and a percentage change from baseline of 59.1%. An exploratory factor analysis found 5 components explaining 57.8% of the total variance. We noted a floor effect only on postoperative day 14; we found no ceiling effect. Conclusions: SwQoR is valid, has excellent reliability and high responsiveness, and is clinically feasible for the systematic follow-up of patients’ postoperative recovery. %M 29229590 %R 10.2196/mhealth.9061 %U http://mhealth.jmir.org/2017/12/e188/ %U https://doi.org/10.2196/mhealth.9061 %U http://www.ncbi.nlm.nih.gov/pubmed/29229590 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 6 %N 2 %P e22 %T “A Phenomenal Person and Doctor”: Thank You Letters to Medical Care Providers %A Miron-Shatz,Talya %A Becker,Stefan %A Zaromb,Franklin %A Mertens,Alexander %A Tsafrir,Avi %+ Center for Medical Decision Making, Faculty of Business Administration, Ono Academic College, 104 Zahal St., Kiryat Ono, 55000, Israel, 972 0523304417, talyam@ono.ac.il %K quality of health care %K doctor-patient relationship %K content analysis %K decision making %K doctor-patient communication %K clinical encounter %K patient satisfaction %K online reviews %K patient-centered care %D 2017 %7 02.11.2017 %9 Original Paper %J Interact J Med Res %G English %X Background: Thank you letters to physicians and medical facilities are an untapped resource, providing an invaluable glimpse into what patients notice and appreciate in their care. Objective: The aim of this study was to analyze such thank you letters as posted on the Web by medical institutions to find what patients and families consider to be good care. In an age of patient-centered care, it is pivotal to see what metrics patients and families apply when assessing their care and whether they grasp specific versus general qualities in their care. Methods: Our exploratory inquiry covered 100 thank you letters posted on the Web by 26 medical facilities in the United States and the United Kingdom. We systematically coded and descriptively presented the aspects of care that patients and their families thanked doctors and medical facilities for. We relied on previous work outlining patient priorities and satisfaction (Anderson et al, 2007), to which we added a distinction between global and specific evaluations for each of the already existing categories with two additional categories: general praise and other, and several subcategories, such as treatment outcome, to the category of medical care. Results: In 73% of the letters (73/100), physicians were primarily thanked for their medical treatment. In 71% (71/100) of the letters, they were thanked for their personality and demeanor. In 52% cases (52/100), these two aspects were mentioned together, suggesting that from the perspective of patient as well as the family member, both are deemed necessary in positive evaluation of medical care. Only 8% (8/100) of the letters lacked reference to medical care, personality or demeanor, or communication. No statistically significant differences were observed in the number of letters that expressed gratitude for the personality or demeanor of medical care providers versus the quality of medical care (χ21, N=200=0.1, not statistically significant). Letters tended to express more specific praise for personality or demeanor, such as being supportive, understanding, humane and caring (48/71, 68%) but more general praise for medical care (χ21, N=424=63.9, P<.01). The most often mentioned specific quality of medical care were treatment outcomes (30/73, 41%), followed by technical competence (15/73, 21%) and treatment approach (14/73, 19%). A limitation of this inquiry is that we analyzed the letters that medical centers chose to post on the Web. These are not necessarily a representative sample of all thank you letters as are sent to health care institutions but are still indicative of what centers choose to showcase on the Web. Conclusions: Physician demeanor and quality of interaction with patients are pivotal in how laymen perceive good care, no less so than medical care per se. This inquiry can inform care providers and medical curricula, leading to an improvement in the perceived quality of care. %M 29097353 %R 10.2196/ijmr.7107 %U http://www.i-jmr.org/2017/2/e22/ %U https://doi.org/10.2196/ijmr.7107 %U http://www.ncbi.nlm.nih.gov/pubmed/29097353 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 19 %N 5 %P e181 %T Evaluating the Social Media Performance of Hospitals in Spain: A Longitudinal and Comparative Study %A Martinez-Millana,Antonio %A Fernandez-Llatas,Carlos %A Basagoiti Bilbao,Ignacio %A Traver Salcedo,Manuel %A Traver Salcedo,Vicente %+ ITACA, Universitat Politècnica de València, Buildign 8G Access B 1st Fl, Camino de Vera s/n. 46022, Valencia,, Spain, 34 963877606, anmarmil@itaca.upv.es %K public health %K delivery of health care %K Internet %K social media %K hospitals %D 2017 %7 23.05.2017 %9 Original Paper %J J Med Internet Res %G English %X Background: Social media is changing the way in which citizens and health professionals communicate. Previous studies have assessed the use of Health 2.0 by hospitals, showing clear evidence of growth in recent years. In order to understand if this happens in Spain, it is necessary to assess the performance of health care institutions on the Internet social media using quantitative indicators. Objectives: The study aimed to analyze how hospitals in Spain perform on the Internet and social media networks by determining quantitative indicators in 3 different dimensions: presence, use, and impact and assess these indicators on the 3 most commonly used social media - Facebook, Twitter, YouTube. Further, we aimed to find out if there was a difference between private and public hospitals in their use of the aforementioned social networks. Methods: The evolution of presence, use, and impact metrics is studied over the period 2011- 2015. The population studied accounts for all the hospitals listed in the National Hospitals Catalog (NHC). The percentage of hospitals having Facebook, Twitter, and YouTube profiles has been used to show the presence and evolution of hospitals on social media during this time. Usage was assessed by analyzing the content published on each social network. Impact evaluation was measured by analyzing the trend of subscribers for each social network. Statistical analysis was performed using a lognormal transformation and also using a nonparametric distribution, with the aim of comparing t student and Wilcoxon independence tests for the observed variables. Results: From the 787 hospitals identified, 69.9% (550/787) had an institutional webpage and 34.2% (269/787) had at least one profile in one of the social networks (Facebook, Twitter, and YouTube) in December 2015. Hospitals’ Internet presence has increased by more than 450.0% (787/172) and social media presence has increased ten times since 2011. Twitter is the preferred social network for public hospitals, whereas private hospitals showed better performance on Facebook and YouTube. The two-sided Wilcoxon test and t student test at a CI of 95% show that the use of Twitter distribution is higher (P<.001) for private and public hospitals in Spain, whereas other variables show a nonsignificant different distribution. Conclusions: The Internet presence of Spanish hospitals is high; however, their presence on the 3 main social networks is still not as high compared to that of hospitals in the United States and Western Europe. Public hospitals are found to be more active on Twitter, whereas private hospitals show better performance on Facebook and YouTube. This study suggests that hospitals, both public and private, should devote more effort to and be more aware of social media, with a clear strategy as to how they can foment new relationships with patients and citizens. %M 28536091 %R 10.2196/jmir.6763 %U http://www.jmir.org/2017/5/e181/ %U https://doi.org/10.2196/jmir.6763 %U http://www.ncbi.nlm.nih.gov/pubmed/28536091 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 19 %N 3 %P e65 %T Supervised Machine Learning Algorithms Can Classify Open-Text Feedback of Doctor Performance With Human-Level Accuracy %A Gibbons,Chris %A Richards,Suzanne %A Valderas,Jose Maria %A Campbell,John %+ The Psychometrics Centre, University of Cambridge, 16 Mill Lane, Cambridge, CB2 1RH, United Kingdom, 44 1223 765 203, cg598@cam.ac.uk %K machine learning %K surveys and questionnaires %K feedback %K data mining %K work performance %D 2017 %7 15.03.2017 %9 Original Paper %J J Med Internet Res %G English %X Background: Machine learning techniques may be an effective and efficient way to classify open-text reports on doctor’s activity for the purposes of quality assurance, safety, and continuing professional development. Objective: The objective of the study was to evaluate the accuracy of machine learning algorithms trained to classify open-text reports of doctor performance and to assess the potential for classifications to identify significant differences in doctors’ professional performance in the United Kingdom. Methods: We used 1636 open-text comments (34,283 words) relating to the performance of 548 doctors collected from a survey of clinicians’ colleagues using the General Medical Council Colleague Questionnaire (GMC-CQ). We coded 77.75% (1272/1636) of the comments into 5 global themes (innovation, interpersonal skills, popularity, professionalism, and respect) using a qualitative framework. We trained 8 machine learning algorithms to classify comments and assessed their performance using several training samples. We evaluated doctor performance using the GMC-CQ and compared scores between doctors with different classifications using t tests. Results: Individual algorithm performance was high (range F score=.68 to .83). Interrater agreement between the algorithms and the human coder was highest for codes relating to “popular” (recall=.97), “innovator” (recall=.98), and “respected” (recall=.87) codes and was lower for the “interpersonal” (recall=.80) and “professional” (recall=.82) codes. A 10-fold cross-validation demonstrated similar performance in each analysis. When combined together into an ensemble of multiple algorithms, mean human-computer interrater agreement was .88. Comments that were classified as “respected,” “professional,” and “interpersonal” related to higher doctor scores on the GMC-CQ compared with comments that were not classified (P<.05). Scores did not vary between doctors who were rated as popular or innovative and those who were not rated at all (P>.05). Conclusions: Machine learning algorithms can classify open-text feedback of doctor performance into multiple themes derived by human raters with high performance. Colleague open-text comments that signal respect, professionalism, and being interpersonal may be key indicators of doctor’s performance. %M 28298265 %R 10.2196/jmir.6533 %U http://www.jmir.org/2017/3/e65/ %U https://doi.org/10.2196/jmir.6533 %U http://www.ncbi.nlm.nih.gov/pubmed/28298265 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 18 %N 9 %P e257 %T Design and Testing of BACRA, a Web-Based Tool for Middle Managers at Health Care Facilities to Lead the Search for Solutions to Patient Safety Incidents %A Carrillo,Irene %A Mira,José Joaquín %A Vicente,Maria Asuncion %A Fernandez,Cesar %A Guilabert,Mercedes %A Ferrús,Lena %A Zavala,Elena %A Silvestre,Carmen %A Pérez-Pérez,Pastora %+ Health Psychology Department, Miguel Hernández University, Universidad s/n, Elche, 03202, Spain, 34 966658984, icarrillo@umh.es %K patient safety %K risk management %K root cause analysis %K hospital %K primary care %K frontline health professionals %K middle managers %D 2016 %7 27.09.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: Lack of time, lack of familiarity with root cause analysis, or suspicion that the reporting may result in negative consequences hinder involvement in the analysis of safety incidents and the search for preventive actions that can improve patient safety. Objective: The aim was develop a tool that enables hospitals and primary care professionals to immediately analyze the causes of incidents and to propose and implement measures intended to prevent their recurrence. Methods: The design of the Web-based tool (BACRA) considered research on the barriers for reporting, review of incident analysis tools, and the experience of eight managers from the field of patient safety. BACRA’s design was improved in successive versions (BACRA v1.1 and BACRA v1.2) based on feedback from 86 middle managers. BACRA v1.1 was used by 13 frontline professionals to analyze incidents of safety; 59 professionals used BACRA v1.2 and assessed the respective usefulness and ease of use of both versions. Results: BACRA contains seven tabs that guide the user through the process of analyzing a safety incident and proposing preventive actions for similar future incidents. BACRA does not identify the person completing each analysis since the password introduced to hide said analysis only is linked to the information concerning the incident and not to any personal data. The tool was used by 72 professionals from hospitals and primary care centers. BACRA v1.2 was assessed more favorably than BACRA v1.1, both in terms of its usefulness (z=2.2, P=.03) and its ease of use (z=3.0, P=.003). Conclusions: BACRA helps to analyze incidents of safety and to propose preventive actions. BACRA guarantees anonymity of the analysis and reduces the reluctance of professionals to carry out this task. BACRA is useful and easy to use. %M 27678308 %R 10.2196/jmir.5942 %U http://www.jmir.org/2016/9/e257/ %U https://doi.org/10.2196/jmir.5942 %U http://www.ncbi.nlm.nih.gov/pubmed/27678308 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 18 %N 7 %P e180 %T The Effect of a Freely Available Flipped Classroom Course on Health Care Worker Patient Safety Culture: A Prospective Controlled Study %A Ling,Lowell %A Gomersall,Charles David %A Samy,Winnie %A Joynt,Gavin Matthew %A Leung,Czarina CH %A Wong,Wai-Tat %A Lee,Anna %+ The Chinese University of Hong Kong, Department of Anaesthesia and Intensive Care, 4th Floor, Main Clinical Block and Trauma Centre, Prince of Wales Hospital, Shatin,, China (Hong Kong), 852 2632 2735, annalee@cuhk.edu.hk %K patient safety %K critical care %K education, professional %K education, distance %K safety culture %D 2016 %7 05.07.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: Patient safety culture is an integral aspect of good standard of care. A good patient safety culture is believed to be a prerequisite for safe medical care. However, there is little evidence on whether general education can enhance patient safety culture. Objective: Our aim was to assess the impact of a standardized patient safety course on health care worker patient safety culture. Methods: Health care workers from Intensive Care Units (ICU) at two hospitals (A and B) in Hong Kong were recruited to compare the changes in safety culture before and after a patient safety course. The BASIC Patient Safety course was administered only to staff from Hospital A ICU. Safety culture was assessed in both units at two time points, one before and one after the course, by using the Hospital Survey on Patient Safety Culture questionnaire. Responses were coded according to the Survey User’s Guide, and positive response percentages for each patient safety domain were compared to the 2012 Agency for Healthcare Research and Quality ICU sample of 36,120 respondents. Results: We distributed 127 questionnaires across the two hospitals with an overall response rate of 74.8% (95 respondents). After the safety course, ICU A significantly improved on teamwork within hospital units (P=.008) and hospital management support for patient safety (P<.001), but decreased in the frequency of reporting mistakes compared to the initial survey (P=.006). Overall, ICU A staff showed significantly greater enhancement in positive responses in five domains than staff from ICU B. Pooled data indicated that patient safety culture was poorer in the two ICUs than the average ICU in the Agency for Healthcare Research and Quality database, both overall and in every individual domain except hospital management support for patient safety and hospital handoffs and transitions. Conclusions: Our study demonstrates that a structured, reproducible short course on patient safety may be associated with an enhancement in several domains in ICU patient safety culture. %M 27381876 %R 10.2196/jmir.5378 %U http://www.jmir.org/2016/7/e180/ %U https://doi.org/10.2196/jmir.5378 %U http://www.ncbi.nlm.nih.gov/pubmed/27381876 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 18 %N 5 %P e125 %T Patient-Reported Safety Events in Chronic Kidney Disease Recorded With an Interactive Voice-Inquiry Dial-Response System: Monthly Report Analysis %A Fink,Jeffrey C %A Doerfler,Rebecca M %A Yoffe,Marni R %A Diamantidis,Clarissa J %A Blumenthal,Jacob B %A Siddiqui,Tariq %A Gardner,James F %A Snitker,Soren %A Zhan,Min %+ University of Maryland School of Medicine, Department of Medicine, 22 S Greene St, Baltimore, MD, 21201, United States, 1 4107066563, jfink@medicine.umaryland.edu %K patient-reported outcomes %K CKD %K interactive voice-response system %K patient safety %D 2016 %7 26.05.2016 %9 Original Paper %J J Med Internet Res %G English %X Background: Monitoring patient-reported outcomes (PROs) may improve safety of chronic kidney disease (CKD) patients. Objective: Evaluate the performance of an interactive voice-inquiry dial-response system (IVRDS) in detecting CKD-pertinent adverse safety events outside of the clinical environment and compare the incidence of events using the IVDRS to that detected by paper diary. Methods: This was a 6-month study of Stage III-V CKD patients in the Safe Kidney Care (SKC) study. Participants crossed over from a paper diary to the IVDRS for recording patient-reported safety events defined as symptoms or events attributable to medications or care. The IVDRS was adapted from the SKC paper diary to record event frequency and remediation. Participants were auto-called weekly and permitted to self-initiate calls. Monthly reports were reviewed by two physician adjudicators for their clinical significance. Results: 52 participants were followed over a total of 1384 weeks. 28 out of 52 participants (54%) reported events using the IVDRS versus 8 out of 52 (15%) with the paper diary; hypoglycemia was the most common event for both methods. All IVDRS menu options were selected at least once except for confusion and rash. Events were reported on 121 calls, with 8 calls reporting event remediation by ambulance or emergency room (ER) visit. The event rate with the IVDRS and paper diary, with and without hypoglycemia, was 26.7 versus 4.7 and 18.3 versus 0.8 per 100 person weeks, respectively (P=.002 and P<.001). The frequent users (ie, >10 events) largely differed by method, and event rates excluding the most frequent user of each were 16.9 versus 2.5 per 100 person weeks, respectively (P<.001). Adjudicators found approximately half the 80 reports clinically significant, with about a quarter judged as actionable. Hypoglycemia was often associated with additional reports of fatigue and falling. Participants expressed favorable satisfaction with the IVDRS. Conclusions: Use of the IVDRS among CKD patients reveals a high frequency of clinically significant safety events and has the potential to be used as an important supplement to clinical care for improving patient safety. %M 27230267 %R 10.2196/jmir.5203 %U http://www.jmir.org/2016/5/e125/ %U https://doi.org/10.2196/jmir.5203 %U http://www.ncbi.nlm.nih.gov/pubmed/27230267 %0 Journal Article %@ 2291-9694 %I Gunther Eysenbach %V 4 %N 1 %P e8 %T Improving Inpatient Surveys: Web-Based Computer Adaptive Testing Accessed via Mobile Phone QR Codes %A Chien,Tsair-Wei %A Lin,Weir-Sen %+ Chia-Nan University of Pharmacy and Science, Department of Hospital and Health Care Administration, Number 60, Section 1, Erren Road, Rende District, Tainan City 71710, Taiwan (R.O.C.), 886 +886 6 2664911, weirsen@mail.cnu.edu.tw %K computer adaptive testing %K patients’ experience %K partial credit model %K consultation experience and perception %K smart phone %D 2016 %7 02.03.2016 %9 Original Paper %J JMIR Med Inform %G English %X Background: The National Health Service (NHS) 70-item inpatient questionnaire surveys inpatients on their perceptions of their hospitalization experience. However, it imposes more burden on the patient than other similar surveys. The literature shows that computerized adaptive testing (CAT) based on item response theory can help shorten the item length of a questionnaire without compromising its precision. Objective: Our aim was to investigate whether CAT can be (1) efficient with item reduction and (2) used with quick response (QR) codes scanned by mobile phones. Methods: After downloading the 2008 inpatient survey data from the Picker Institute Europe website and analyzing the difficulties of this 70-item questionnaire, we used an author-made Excel program using the Rasch partial credit model to simulate 1000 patients’ true scores followed by a standard normal distribution. The CAT was compared to two other scenarios of answering all items (AAI) and the randomized selection method (RSM), as we investigated item length (efficiency) and measurement accuracy. The author-made Web-based CAT program for gathering patient feedback was effectively accessed from mobile phones by scanning the QR code. Results: We found that the CAT can be more efficient for patients answering questions (ie, fewer items to respond to) than either AAI or RSM without compromising its measurement accuracy. A Web-based CAT inpatient survey accessed by scanning a QR code on a mobile phone was viable for gathering inpatient satisfaction responses. Conclusions: With advances in technology, patients can now be offered alternatives for providing feedback about hospitalization satisfaction. This Web-based CAT is a possible option in health care settings for reducing the number of survey items, as well as offering an innovative QR code access. %M 26935793 %R 10.2196/medinform.4313 %U http://medinform.jmir.org/2016/1/e8/ %U https://doi.org/10.2196/medinform.4313 %U http://www.ncbi.nlm.nih.gov/pubmed/26935793 %0 Journal Article %@ 1438-8871 %I JMIR Publications Inc. %V 17 %N 4 %P e90 %T Identifying Key Hospital Service Quality Factors in Online Health Communities %A Jung,Yuchul %A Hur,Cinyoung %A Jung,Dain %A Kim,Minki %+ Korea Advanced Institute of Science and Technology, College of Business, S304, KAIST Business School, 85 Hoegiro, Dongdaemun-gu, Seoul, 130-722, Republic Of Korea, 82 29583512, minki.kim@kaist.ac.kr %K hospital service factors %K online health communities %K social media-based key quality factors for hospitals %K recommendation type classification %K quality factor analysis %K healthcare policy %D 2015 %7 07.04.2015 %9 Original Paper %J J Med Internet Res %G English %X Background: The volume of health-related user-created content, especially hospital-related questions and answers in online health communities, has rapidly increased. Patients and caregivers participate in online community activities to share their experiences, exchange information, and ask about recommended or discredited hospitals. However, there is little research on how to identify hospital service quality automatically from the online communities. In the past, in-depth analysis of hospitals has used random sampling surveys. However, such surveys are becoming impractical owing to the rapidly increasing volume of online data and the diverse analysis requirements of related stakeholders. Objective: As a solution for utilizing large-scale health-related information, we propose a novel approach to identify hospital service quality factors and overtime trends automatically from online health communities, especially hospital-related questions and answers. Methods: We defined social media–based key quality factors for hospitals. In addition, we developed text mining techniques to detect such factors that frequently occur in online health communities. After detecting these factors that represent qualitative aspects of hospitals, we applied a sentiment analysis to recognize the types of recommendations in messages posted within online health communities. Korea’s two biggest online portals were used to test the effectiveness of detection of social media–based key quality factors for hospitals. Results: To evaluate the proposed text mining techniques, we performed manual evaluations on the extraction and classification results, such as hospital name, service quality factors, and recommendation types using a random sample of messages (ie, 5.44% (9450/173,748) of the total messages). Service quality factor detection and hospital name extraction achieved average F1 scores of 91% and 78%, respectively. In terms of recommendation classification, performance (ie, precision) is 78% on average. Extraction and classification performance still has room for improvement, but the extraction results are applicable to more detailed analysis. Further analysis of the extracted information reveals that there are differences in the details of social media–based key quality factors for hospitals according to the regions in Korea, and the patterns of change seem to accurately reflect social events (eg, influenza epidemics). Conclusions: These findings could be used to provide timely information to caregivers, hospital officials, and medical officials for health care policies. %M 25855612 %R 10.2196/jmir.3646 %U http://www.jmir.org/2015/4/e90/ %U https://doi.org/10.2196/jmir.3646 %U http://www.ncbi.nlm.nih.gov/pubmed/25855612 %0 Journal Article %@ 2291-9694 %I Gunther Eysenbach %V 3 %N 1 %P e13 %T Real-Time Patient Survey Data During Routine Clinical Activities for Rapid-Cycle Quality Improvement %A Wofford,James Lucius %A Campos,Claudia L %A Jones,Robert E %A Stevens,Sheila F %+ Wake Forest University, Medical Center Boulevard, Winston-Salem, NC, 27157, United States, 1 336 713 9602, jwofford@wakehealth.edu %K quality improvement %K patient-centered care %K information management/informatics %K office practice issues/practice reengineering %D 2015 %7 12.03.2015 %9 Original Paper %J JMIR Med Inform %G English %X Background: Surveying patients is increasingly important for evaluating and improving health care delivery, but practical survey strategies during routine care activities have not been available. Objective: We examined the feasibility of conducting routine patient surveys in a primary care clinic using commercially available technology (Web-based survey creation, deployment on tablet computers, cloud-based management of survey data) to expedite and enhance several steps in data collection and management for rapid quality improvement cycles. Methods: We used a Web-based data management tool (survey creation, deployment on tablet computers, real-time data accumulation and display of survey results) to conduct four patient surveys during routine clinic sessions over a one-month period. Each survey consisted of three questions and focused on a specific patient care domain (dental care, waiting room experience, care access/continuity, Internet connectivity). Results: Of the 727 available patients during clinic survey days, 316 patients (43.4%) attempted the survey, and 293 (40.3%) completed the survey. For the four 3-question surveys, the average time per survey was overall 40.4 seconds, with a range of 5.4 to 20.3 seconds for individual questions. Yes/No questions took less time than multiple choice questions (average 9.6 seconds versus 14.0). Average response time showed no clear pattern by order of questions or by proctor strategy, but monotonically increased with number of words in the question (<20 words, 21-30 words, >30 words)—8.0, 11.8, 16.8, seconds, respectively. Conclusions: This technology-enabled data management system helped capture patient opinions, accelerate turnaround of survey data, with minimal impact on a busy primary care clinic. This new model of patient survey data management is feasible and sustainable in a busy office setting, supports and engages clinicians in the quality improvement process, and harmonizes with the vision of a learning health care system. %M 25768807 %R 10.2196/medinform.3697 %U http://medinform.jmir.org/2015/1/e13/ %U https://doi.org/10.2196/medinform.3697 %U http://www.ncbi.nlm.nih.gov/pubmed/25768807