TY - JOUR AU - Chin, Harvey Yen Po AU - Song, Wenyu AU - Lien, En Chia AU - Yoon, Ho Chang AU - Wang, Wei-Chen AU - Liu, Jennifer AU - Nguyen, Anh Phung AU - Feng, Ting Yi AU - Zhou, Li AU - Li, Jack Yu Chuan AU - Bates, Westfall David PY - 2021/1/27 TI - Assessing the International Transferability of a Machine Learning Model for Detecting Medication Error in the General Internal Medicine Clinic: Multicenter Preliminary Validation Study JO - JMIR Med Inform SP - e23454 VL - 9 IS - 1 KW - electronic health records KW - patient safety KW - clinical decision support KW - medication alert systems KW - machine learning N2 - Background: Although most current medication error prevention systems are rule-based, these systems may result in alert fatigue because of poor accuracy. Previously, we had developed a machine learning (ML) model based on Taiwan?s local databases (TLD) to address this issue. However, the international transferability of this model is unclear. Objective: This study examines the international transferability of a machine learning model for detecting medication errors and whether the federated learning approach could further improve the accuracy of the model. Methods: The study cohort included 667,572 outpatient prescriptions from 2 large US academic medical centers. Our ML model was applied to build the original model (O model), the local model (L model), and the hybrid model (H model). The O model was built using the data of 1.34 billion outpatient prescriptions from TLD. A validation set with 8.98% (60,000/667,572) of the prescriptions was first randomly sampled, and the remaining 91.02% (607,572/667,572) of the prescriptions served as the local training set for the L model. With a federated learning approach, the H model used the association values with a higher frequency of co-occurrence among the O and L models. A testing set with 600 prescriptions was classified as substantiated and unsubstantiated by 2 independent physician reviewers and was then used to assess model performance. Results: The interrater agreement was significant in terms of classifying prescriptions as substantiated and unsubstantiated (?=0.91; 95% CI 0.88 to 0.95). With thresholds ranging from 0.5 to 1.5, the alert accuracy ranged from 75%-78% for the O model, 76%-78% for the L model, and 79%-85% for the H model. Conclusions: Our ML model has good international transferability among US hospital data. Using the federated learning approach with local hospital data could further improve the accuracy of the model. UR - http://medinform.jmir.org/2021/1/e23454/ UR - http://dx.doi.org/10.2196/23454 UR - http://www.ncbi.nlm.nih.gov/pubmed/33502331 ID - info:doi/10.2196/23454 ER - TY - JOUR AU - Chen, Zhuo-Jia AU - Liang, Wei-Ting AU - Liu, Qing AU - He, Rong AU - Chen, Qian-Chao AU - Li, Qiu-Feng AU - Zhang, Yao AU - Du, Xiao-Dong AU - Pan, Ying AU - Liu, Shu AU - Li, Xiao-Yan AU - Wei, Xue AU - Huang, He AU - Huang, Hong-Bing AU - Liu, Tao PY - 2021/1/21 TI - Use of a Remote Oncology Pharmacy Service Platform for Patients With Cancer During the COVID-19 Pandemic: Implementation and User Acceptance Evaluation JO - J Med Internet Res SP - e24619 VL - 23 IS - 1 KW - COVID-19 KW - cancer patients KW - remote pharmacy KW - service platform KW - implementation KW - oncology KW - pharmacy KW - online platform KW - cancer KW - health management KW - app KW - online hospital KW - acceptance KW - impact N2 - Background: The COVID-19 outbreak has increased challenges associated with health management, especially cancer management. In an effort to provide continuous pharmaceutical care to cancer patients, Sun Yat-sen University Cancer Center (SYSUCC) implemented a remote pharmacy service platform based on its already existing web-based hospital app known as Cloud SYSUCC. Objective: The aim of this study was to investigate the characteristics, acceptance, and initial impact of the Cloud SYSUCC app during a COVID-19 outbreak in a tertiary cancer hospital in China. Methods: The total number of online prescriptions and detailed information on the service were obtained during the first 6 months after the remote service platform was successfully set up. The patients? gender, age, residence, primary diagnosis, drug classification, weekly number of prescriptions, and prescribed drugs were analyzed. In addition, a follow-up telephonic survey was conducted to evaluate patients? satisfaction in using the remote prescription service. Results: A total of 1718 prescriptions, including 2022 drugs for 1212 patients, were delivered to 24 provinces and municipalities directly under the Central Government of China between February 12, 2020, and August 11, 2020. The majority of patients were female (841/1212, 69.39%), and 90.18% (1093/1212) of them were aged 31-70 years old. The top 3 primary diagnoses for which remote medical prescriptions were made included breast cancer (599/1212, 49.42%), liver cancer (249/1212, 20.54%), and thyroid cancer (125/1212, 10.31%). Of the 1718 prescriptions delivered, 1435 (83.5%) were sent to Guangdong Province and 283 (16.5%) were sent to other provinces in China. Of the 2022 drugs delivered, 1012 (50.05%) were hormonal drugs. The general trend in the use of the remote prescription service declined since the 10th week. A follow-up telephonic survey found that 88% (88/100) of the patients were very satisfied, and 12% (12/100) of the patients were somewhat satisfied with the remote pharmacy service platform. Conclusions: The remote pharmacy platform Cloud SYSUCC is efficient and convenient for providing continuous pharmaceutical care to patients with cancer during the COVID-19 crisis. The widespread use of this platform can help to reduce person-to-person transmission as well as infection risk for these patients. Further efforts are needed to improve the quality and acceptance of the Cloud SYSUCC platform, as well as to regulate and standardize the management of this novel service. UR - http://www.jmir.org/2021/1/e24619/ UR - http://dx.doi.org/10.2196/24619 UR - http://www.ncbi.nlm.nih.gov/pubmed/33395398 ID - info:doi/10.2196/24619 ER - TY - JOUR AU - Sragow, Michael Howard AU - Bidell, Eileen AU - Mager, Douglas AU - Grannis, Shaun PY - 2020/11/20 TI - Universal Patient Identifier and Interoperability for Detection of Serious Drug Interactions: Retrospective Study JO - JMIR Med Inform SP - e23353 VL - 8 IS - 11 KW - patient identification KW - pharmacy benefit manager KW - interoperability KW - adverse drug event KW - identity management KW - identifier KW - pharmacy KW - pharmaceuticals KW - drug N2 - Background: The United States, unlike other high-income countries, currently has no national unique patient identifier to facilitate health information exchange. Because of security and privacy concerns, Congress, in 1998, prevented the government from promulgating a unique patient identifier. The Health and Human Services funding bill that was enacted in 2019 requires that Health and Human Services report their recommendations on patient identification to Congress. While there are anecdotes of incomplete health care data due to patient misidentification, to date there have been insufficient large-scale analyses measuring improvements to patient care that a unique patient identifier might provide. This lack of measurement has made it difficult for policymakers to balance security and privacy concerns against the value of potential improvements. Objective: We sought to determine the frequency of serious drug-drug interaction alerts discovered because a pharmacy benefits manager uses a universal patient identifier and estimate undiscovered serious drug-drug interactions because pharmacy benefit managers do not yet fully share patient records. Methods: We conducted a retrospective study of serious drug-drug interaction alerts provided from September 1, 2016 to August 31, 2019 to retail pharmacies by a national pharmacy benefit manager that uses a unique patient identifier. We compared each alert to the contributing prescription and determined whether the unique patient identifier was necessary in order to identify the crossover alert. We classified each alert?s disposition as override, abandonment, or replacement. Using the crossover alert rate and sample population size, we inferred a rate of missing serious drug-drug interaction alerts for the United States. We performed logistic regression in order to identify factors correlated with crossover and alert outcomes. Results: Among a population of 49.7 million patients, 242,646 serious drug-drug interaction alerts occurred in 3 years. Of these, 2388 (1.0%) crossed insurance and were discovered because the pharmacy benefit manager used a unique patient identifier. We estimate that up to 10% of serious drug-drug alerts in the United States go undetected by pharmacy benefit managers because of unexchanged information or pharmacy benefit managers that do not use a unique patient identifier. These information gaps may contribute, annually, to up to 6000 patients in the United States receiving a contraindicated medication. Conclusions: Comprehensive patient identification across disparate data sources can help protect patients from serious drug-drug interactions. To better safeguard patients, providers should (1) adopt a comprehensive patient identification strategy and (2) share patient prescription history to improve clinical decision support. UR - http://medinform.jmir.org/2020/11/e23353/ UR - http://dx.doi.org/10.2196/23353 UR - http://www.ncbi.nlm.nih.gov/pubmed/33216009 ID - info:doi/10.2196/23353 ER - TY - JOUR AU - Fung, To Eunice Wing AU - Au-Yeung, Fung Gordon Tsz AU - Tsoi, Mei Lo AU - Qu, Lili AU - Cheng, Wa Tommy Kwan AU - Chong, Wing-Kit Donald AU - Lam, Ning Teddy Tai AU - Cheung, Ting Yin PY - 2020/11/10 TI - Pharmacists? Perceptions of the Benefits and Challenges of Electronic Product Information System Implementation in Hong Kong: Mixed-Method Study JO - J Med Internet Res SP - e20765 VL - 22 IS - 11 KW - electronic product information KW - drug information system KW - electronic health information KW - health care professionals KW - retrieval of health information N2 - Background: With the advancement of technology, more countries are now adopting the use of electronic product information (ePI), which refer to an electronic version of physical product inserts in a semistructured format optimized for electronic manipulation. The successful implementation of ePI has led to advantages and convenience to patients, health care professionals, and pharmaceutical companies in many regions and countries. In the Hong Kong Special Administrative Region (SAR), there is currently no citywide implementation of ePI. The SAR exhibits conditions that would favor the implementation of an ePI system, as well as existing barriers hindering its implementation. However, no study has been performed to examine the specific situation in Hong Kong. Objective: The objective of this study is to explore working pharmacists? overall perception of ePI and to identify potential challenges to the implementation of an ePI system in Hong Kong. Methods: This mixed-method study involved a structured survey and interview with practicing pharmacists in Hong Kong. Pharmacists were eligible if they were licensed to practice in Hong Kong, and currently working locally in any pharmacy-related sectors and institutions. Respondents completed a survey to indicate their level of agreement with statements regarding the potential advantages of ePI over paper PI. A structured interview was conducted to gather respondents? perceived advantages of ePI over paper PI in different aspects, such as professionalism, usability, presentation, and environment, as well as challenges of citywide ePI implementation in Hong Kong. Thematic analysis was adopted to analyze the qualitative data. Grounded theory was used to generate themes and identify specific outcomes. Results: A total of 16 pharmacists were recruited, comprising 4 community pharmacists, 5 hospital pharmacists, and 7 industrial pharmacists. All of them used electronic platforms at least once per month on average. Respondents identified many flaws in physical package inserts that can potentially be mitigated using ePI. The speed with which drug information can be retrieved and the degree to which the drug information can be readily updated and disseminated were considered the greatest strengths of ePI. The clarity with which ePI present drug information to patients was considered as the weakest aspect of ePI. Many respondents highlighted concerns about the security risks and high cost associated with system maintenance and that certain subpopulations may not be sufficiently computer literate to navigate the ePI system. Respondents also voiced many concerns about the implementation and maintenance of a local ePI system. Conclusions: We conclude that an ePI system is generally supported by pharmacists but concerns about implementation process and maintenance of the system has been raised. The perceived benefits of ePI gathered from this study, as well as collective evidence from other countries with mature ePI systems, confirm that more efforts should be made to promote optimized development and implementation of an ePI system in Hong Kong. UR - http://www.jmir.org/2020/11/e20765/ UR - http://dx.doi.org/10.2196/20765 UR - http://www.ncbi.nlm.nih.gov/pubmed/33170130 ID - info:doi/10.2196/20765 ER - TY - JOUR AU - Ding, Liang AU - She, Qiuru AU - Chen, Fengxian AU - Chen, Zitong AU - Jiang, Meifang AU - Huang, Huasi AU - Li, Yujin AU - Liao, Chaofeng PY - 2020/8/6 TI - The Internet Hospital Plus Drug Delivery Platform for Health Management During the COVID-19 Pandemic: Observational Study JO - J Med Internet Res SP - e19678 VL - 22 IS - 8 KW - internet hospital KW - drug delivery KW - internet hospital plus drug delivery KW - IHDD KW - health management KW - COVID-19 N2 - Background: Widespread access to the internet has boosted the emergence of online hospitals. A new outpatient service called ?internet hospital plus drug delivery? (IHDD) has been developed in China, but little is known about this platform. Objective: The aim of this study is to investigate the characteristics, acceptance, and initial impact of IHDD during the outbreak of COVID-19 in a tertiary hospital in South China Methods: The total number of and detailed information on online prescriptions during the first 2 months after work resumption were obtained. Patients? gender, age, residence, associated prescription department, time of prescription, payment, and drug delivery region were included in the analysis. Results: A total of 1380 prescriptions were picked up or delivered between March 2 and April 20, 2020. The largest group of patients were 36-59 years old (n=680, 49.3%), followed by the 18-35 years age category (n=573, 41.5%). In total, 39.4% (n=544) of the patients chose to get their medicine by self-pickup, while 60.6% (n=836) preferred to receive their medicine via drug delivery service. The top five online prescription departments were infectious diseases (n=572, 41.4%), nephrology (n=264, 19.1%), endocrinology (n=145, 10.5%), angiocardiopathy (n=107, 7.8%), and neurology (n=42, 3%). Of the 836 delivered prescriptions, 440 (52.6%) were sent to Guangdong Province (including 363 [43.4%] to Shenzhen), and 396 (47.4%) were sent to other provinces in China. Conclusions: The IHDD platform is efficient and convenient for various types of patients during the COVID-19 crisis. Although offline visits are essential for patients with severe conditions, IHDD can help to relieve pressure on hospitals by reducing an influx of patients with mild symptoms. Further efforts need to be made to improve the quality and acceptance of IHDD, as well as to regulate and standardize the management of this novel service. UR - http://www.jmir.org/2020/8/e19678/ UR - http://dx.doi.org/10.2196/19678 UR - http://www.ncbi.nlm.nih.gov/pubmed/32716892 ID - info:doi/10.2196/19678 ER - TY - JOUR AU - Poly, Nasrin Tahmina AU - Islam, Md.Mohaimenul AU - Yang, Hsuan-Chia AU - Li, (Jack) Yu-Chuan PY - 2020/7/20 TI - Appropriateness of Overridden Alerts in Computerized Physician Order Entry: Systematic Review JO - JMIR Med Inform SP - e15653 VL - 8 IS - 7 KW - clinical decision system KW - computerized physician order entry KW - alert fatigue KW - override KW - patient safety N2 - Background: The clinical decision support system (CDSS) has become an indispensable tool for reducing medication errors and adverse drug events. However, numerous studies have reported that CDSS alerts are often overridden. The increase in override rates has raised questions about the appropriateness of CDSS application along with concerns about patient safety and quality of care. Objective: The aim of this study was to conduct a systematic review to examine the override rate, the reasons for the alert override at the time of prescribing, and evaluate the appropriateness of overrides. Methods: We searched electronic databases, including Google Scholar, PubMed, Embase, Scopus, and Web of Science, without language restrictions between January 1, 2000 and March 31, 2019. Two authors independently extracted data and crosschecked the extraction to avoid errors. The quality of the included studies was examined following Cochrane guidelines. Results: We included 23 articles in our systematic review. The range of average override alerts was 46.2%-96.2%. An average of 29.4%-100% of the overrides alerts were classified as appropriate, and the rate of appropriateness varied according to the alert type (drug-allergy interaction 63.4%-100%, drug-drug interaction 0%-95%, dose 43.9%-88.8%, geriatric 14.3%-57%, renal 27%-87.5%). The interrater reliability for the assessment of override alerts appropriateness was excellent (kappa=0.79-0.97). The most common reasons given for the override were ?will monitor? and ?patients have tolerated before.? Conclusions: The findings of our study show that alert override rates are high, and certain categories of overrides such as drug-drug interaction, renal, and geriatric were classified as inappropriate. Nevertheless, large proportions of drug duplication, drug-allergy, and formulary alerts were appropriate, suggesting that these groups of alerts can be primary targets to revise and update the system for reducing alert fatigue. Future efforts should also focus on optimizing alert types, providing clear information, and explaining the rationale of the alert so that essential alerts are not inappropriately overridden. UR - https://medinform.jmir.org/2020/7/e15653 UR - http://dx.doi.org/10.2196/15653 UR - http://www.ncbi.nlm.nih.gov/pubmed/32706721 ID - info:doi/10.2196/15653 ER - TY - JOUR AU - KC, Bhuvan AU - Lim, Dorothy AU - Low, Chia Chia AU - Chew, Connie AU - Blebil, Qais Ali AU - Dujaili, Abdulelah Juman AU - Alrasheedy, A. Alian PY - 2020/7/8 TI - Positioning and Utilization of Information and Communication Technology in Community Pharmacies of Selangor, Malaysia: Cross-Sectional Study JO - JMIR Med Inform SP - e17982 VL - 8 IS - 7 KW - information and communication technology KW - community pharmacy KW - Malaysia KW - pharmacy services N2 - Background: Information and communication technology (ICT) is an essential element of modern ?smart? cities. These smart cities have integrated housing, marketplace, public amenities, services, business, and transportation via ICT. ICT is also now widely used in urban health care delivery. Objective: The aim of this study was to determine the positioning and roles of ICT in community pharmacies in the state of Selangor, Malaysia. Methods: A cross-sectional study was conducted from November 2018 to January 2019 across 9 different subdistricts in the state of Selangor, including Subang Jaya, Cheras, Puchong, Port Klang, Kota Kemuning, Selayang, Chow Kit, Ampang, and Seri Kembangan. A total of 90 community pharmacists were approached from the 9 subdistricts and invited to participate in the study. Results: Of the 90 community pharmacies approached, 60 agreed to participate in the study, representing a response rate of 67%. The majority (36/60, 60%) of the respondents were women, and more than half (32/60, 53%) of the community pharmacies were run by young adults (ie, 30 years old and younger). More than three-quarters of the community pharmacies (46/60, 77%) used electronic health records. Half of the community pharmacies used online social media platforms for advertising and promoting their pharmacies. The vast majority of the community pharmacies (55/60, 92%) were using modern electronic payment systems, and some were also using other new electronic payment methods. Moreover, most of the community pharmacies (41/60, 68%) were using software and programs for accounting and logistics purposes. In addition, 47/60 (78%) of the community pharmacies used a barcode reading system for medicines/health products, and 16/60 (27%) of the pharmacies had online stores, and consumers could buy medicines and health products from these pharmacies via their online portal. In addition, 20/60 (33%) of the community pharmacies used at least one of the common online business platforms available in Southeast Asia to sell products/medicines. The telephone was the most commonly used means of communication with patients, although some pharmacies also used email, WhatsApp, SMS text messaging, and other communication platforms. Conclusions: This study showed that the majority of community pharmacies in Selangor, Malaysia are using ICT for different purposes. However, there is still limited use of mobile apps to provide health services. Overall, community pharmacies have been adopting ICT apps for pharmacy services but the rate of adoption is relatively slower than that in other sectors of Malaysia. UR - https://medinform.jmir.org/2020/7/e17982 UR - http://dx.doi.org/10.2196/17982 UR - http://www.ncbi.nlm.nih.gov/pubmed/32463787 ID - info:doi/10.2196/17982 ER - TY - JOUR AU - Downie, Simon Aron AU - Hancock, Mark AU - Abdel Shaheed, Christina AU - McLachlan, J. Andrew AU - Kocaballi, Baki Ahmet AU - Williams, M. Christopher AU - Michaleff, A. Zoe AU - Maher, G. Chris PY - 2020/5/11 TI - An Electronic Clinical Decision Support System for the Management of Low Back Pain in Community Pharmacy: Development and Mixed Methods Feasibility Study JO - JMIR Med Inform SP - e17203 VL - 8 IS - 5 KW - low back pain KW - community pharmacy KW - decision support systems, clinical N2 - Background: People with low back pain (LBP) in the community often do not receive evidence-based advice and management. Community pharmacists can play an important role in supporting people with LBP as pharmacists are easily accessible to provide first-line care. However, previous research suggests that pharmacists may not consistently deliver advice that is concordant with guideline recommendations and may demonstrate difficulty determining which patients require prompt medical review. A clinical decision support system (CDSS) may enhance first-line care of LBP, but none exists to support the community pharmacist?client consultation. Objective: This study aimed to develop a CDSS to guide first-line care of LBP in the community pharmacy setting and to evaluate the pharmacist-reported usability and acceptance of the prototype system. Methods: A cross-platform Web app for the Apple iPad was developed in conjunction with academic and clinical experts using an iterative user-centered design process during interface design, clinical reasoning, program development, and evaluation. The CDSS was evaluated via one-to-one user-testing with 5 community pharmacists (5 case vignettes each). Data were collected via video recording, screen capture, survey instrument (system usability scale), and direct observation. Results: Pharmacists? agreement with CDSS-generated self-care recommendations was 90% (18/20), with medicines recommendations was 100% (25/25), and with referral advice was 88% (22/25; total 70 recommendations). Pharmacists expressed uncertainty when screening for serious pathology in 40% (10/25) of cases. Pharmacists requested more direction from the CDSS in relation to automated prompts for user input and page navigation. Overall system usability was rated as excellent (mean score 92/100, SD 6.5; 90th percentile compared with similar systems), with acceptance rated as good to excellent. Conclusions: A novel CDSS (high-fidelity prototype) to enhance pharmacist care of LBP was developed, underpinned by clinical practice guidelines and informed by a multidisciplinary team of experts. User-testing revealed a high level of usability and acceptance of the prototype system, with suggestions to improve interface prompts and information delivery. The small study sample limits the generalizability of the findings but offers important insights to inform the next stage of system development. UR - https://medinform.jmir.org/2020/5/e17203 UR - http://dx.doi.org/10.2196/17203 UR - http://www.ncbi.nlm.nih.gov/pubmed/32390593 ID - info:doi/10.2196/17203 ER - TY - JOUR AU - Ramirez, Magaly AU - Chen, Kimberly AU - Follett, W. Robert AU - Mangione, M. Carol AU - Moreno, Gerardo AU - Bell, S. Douglas PY - 2020/4/17 TI - Impact of a ?Chart Closure? Hard Stop Alert on Prescribing for Elevated Blood Pressures Among Patients With Diabetes: Quasi-Experimental Study JO - JMIR Med Inform SP - e16421 VL - 8 IS - 4 KW - decision support systems, clinical KW - diabetes mellitus KW - hypertension KW - drug prescriptions N2 - Background: University of California at Los Angeles Health implemented a Best Practice Advisory (BPA) alert for the initiation of an angiotensin-converting enzyme inhibitor (ACEI) or angiotensin-receptor blocker (ARB) for individuals with diabetes. The BPA alert was configured with a ?chart closure? hard stop, which demanded a response before closing the chart. Objective: The aim of the study was to evaluate whether the implementation of the BPA was associated with changes in ACEI and ARB prescribing during primary care encounters for patients with diabetes. Methods: We defined ACEI and ARB prescribing opportunities as primary care encounters in which the patient had a diabetes diagnosis, elevated blood pressure in recent encounters, no active ACEI or ARB prescription, and no contraindications. We used a multivariate logistic regression model to compare the change in the probability of an ACEI or ARB prescription during opportunity encounters before and after BPA implementation in primary care sites that did (n=30) and did not (n=31) implement the BPA. In an additional subgroup analysis, we compared ACEI and ARB prescribing in BPA implementation sites that had also implemented a pharmacist-led medication management program. Results: We identified a total of 2438 opportunity encounters across 61 primary care sites. The predicted probability of an ACEI or ARB prescription increased significantly from 11.46% to 22.17% during opportunity encounters in BPA implementation sites after BPA implementation. However, in the subgroup analysis, we only observed a significant improvement in ACEI and ARB prescribing in BPA implementation sites that had also implemented the pharmacist-led program. Overall, the change in the predicted probability of an ACEI or ARB prescription from before to after BPA implementation was significantly greater in BPA implementation sites compared with nonimplementation sites (difference-in-differences of 11.82; P<.001). Conclusions: A BPA with a ?chart closure? hard stop is a promising tool for the treatment of patients with comorbid diabetes and hypertension with an ACEI or ARB, especially when implemented within the context of team-based care, wherein clinical pharmacists support the work of primary care providers. UR - http://medinform.jmir.org/2020/4/e16421/ UR - http://dx.doi.org/10.2196/16421 UR - http://www.ncbi.nlm.nih.gov/pubmed/32301741 ID - info:doi/10.2196/16421 ER - TY - JOUR AU - Lester, A. Corey AU - Tu, Liyun AU - Ding, Yuting AU - Flynn, J. Allen PY - 2020/3/11 TI - Detecting Potential Medication Selection Errors During Outpatient Pharmacy Processing of Electronic Prescriptions With the RxNorm Application Programming Interface: Retrospective Observational Cohort Study JO - JMIR Med Inform SP - e16073 VL - 8 IS - 3 KW - patient safety KW - RxNorm KW - electronic prescription KW - pharmacy KW - pharmacists KW - automation N2 - Background: Medication errors are pervasive. Electronic prescriptions (e-prescriptions) convey secure and computer-readable prescriptions from clinics to outpatient pharmacies for dispensing. Once received, pharmacy staff perform a transcription task to select the medications needed to process e-prescriptions within their dispensing software. Later, pharmacists manually double-check medications selected to fulfill e-prescriptions before dispensing to the patient. Although pharmacist double-checks are mostly effective for catching medication selection mistakes, the cognitive process of medication selection in the computer is still prone to error because of heavy workload, inattention, and fatigue. Leveraging health information technology to identify and recover from medication selection errors can improve patient safety. Objective: This study aimed to determine the performance of an automated double-check of pharmacy prescription records to identify potential medication selection errors made in outpatient pharmacies with the RxNorm application programming interface (API). Methods: We conducted a retrospective observational analysis of 537,710 pairs of e-prescription and dispensing records from a mail-order pharmacy for the period January 2017 to October 2018. National Drug Codes (NDCs) for each pair were obtained from the National Library of Medicine?s (NLM?s) RxNorm API. The API returned RxNorm concept unique identifier (RxCUI) semantic clinical drug (SCD) identifiers associated with every NDC. The SCD identifiers returned for the e-prescription NDC were matched against the corresponding SCD identifiers from the pharmacy dispensing record NDC. An error matrix was created based on the hand-labeling of mismatched SCD pairs. Performance metrics were calculated for the e-prescription-to-dispensing record matching algorithm for both total pairs and unique pairs of NDCs in these data. Results: We analyzed 527,881 e-prescription and pharmacy dispensing record pairs. Four clinically significant cases of mismatched RxCUI identifiers were detected (ie, three different ingredient selections and one different strength selection). A total of 546 less significant cases of mismatched RxCUIs were found. Nearly all of the NDC pairs had matching RxCUIs (28,787/28,817, 99.90%-525,270/527,009, 99.67%). The RxNorm API had a sensitivity of 1, a false-positive rate of 0.00104 to 0.00312, specificity of 0.99896 to 0.99688, precision of 0.00727 to 0.04255, and F1 score of 0.01444 to 0.08163. We found 872 pairs of records without an RxCUI. Conclusions: The NLM?s RxNorm API can perform an independent and automatic double-check of correct medication selection to verify e-prescription processing at outpatient pharmacies. RxNorm has near-comprehensive coverage of prescribed medications and can be used to recover from medication selection errors. In the future, tools such as this may be able to perform automated verification of medication selection accurately enough to free pharmacists from having to perform manual double-checks of the medications selected within pharmacy dispensing software to fulfill e-prescriptions. UR - http://medinform.jmir.org/2020/3/e16073/ UR - http://dx.doi.org/10.2196/16073 UR - http://www.ncbi.nlm.nih.gov/pubmed/32044760 ID - info:doi/10.2196/16073 ER - TY - JOUR AU - Monteiro, Luís AU - Maricoto, Tiago AU - Solha, Isabel AU - Ribeiro-Vaz, Inês AU - Martins, Carlos AU - Monteiro-Soares, Matilde PY - 2019/11/14 TI - Reducing Potentially Inappropriate Prescriptions for Older Patients Using Computerized Decision Support Tools: Systematic Review JO - J Med Internet Res SP - e15385 VL - 21 IS - 11 KW - deprescriptions KW - medical informatics applications KW - potentially inappropriate prescription KW - potentially inappropriate medication KW - computerized decision support N2 - Background: Older adults are more vulnerable to polypharmacy and prescriptions of potentially inappropriate medications. There are several ways to address polypharmacy to prevent its occurrence. We focused on computerized decision support tools. Objective: The available literature was reviewed to understand whether computerized decision support tools reduce potentially inappropriate prescriptions or potentially inappropriate medications in older adult patients and affect health outcomes. Methods: Our systematic review was conducted by searching the literature in the MEDLINE, CENTRAL, EMBASE, and Web of Science databases for interventional studies published through February 2018 to assess the impact of computerized decision support tools on potentially inappropriate medications and potentially inappropriate prescriptions in people aged 65 years and older. Results: A total of 3756 articles were identified, and 16 were included. More than half (n=10) of the studies were randomized controlled trials, one was a crossover study, and five were pre-post intervention studies. A total of 266,562 participants were included; of those, 233,144 participants were included and assessed in randomized controlled trials. Intervention designs had several different features. Computerized decision support tools consistently reduced the number of potentially inappropriate prescriptions started and mean number of potentially inappropriate prescriptions per patient. Computerized decision support tools also increased potentially inappropriate prescriptions discontinuation and drug appropriateness. However, in several studies, statistical significance was not achieved. A meta-analysis was not possible due to the significant heterogeneity among the systems used and the definitions of outcomes. Conclusions: Computerized decision support tools may reduce potentially inappropriate prescriptions and potentially inappropriate medications. More randomized controlled trials assessing the impact of computerized decision support tools that could be used both in primary and secondary health care are needed to evaluate the use of medication targets defined by the Beers or STOPP (Screening Tool of Older People?s Prescriptions) criteria, adverse drug reactions, quality of life measurements, patient satisfaction, and professional satisfaction with a reasonable follow-up, which could clarify the clinical usefulness of these tools. Trial Registration: International Prospective Register of Systematic Reviews (PROSPERO) CRD42017067021; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42017067021 UR - https://www.jmir.org/2019/11/e15385 UR - http://dx.doi.org/10.2196/15385 UR - http://www.ncbi.nlm.nih.gov/pubmed/31724956 ID - info:doi/10.2196/15385 ER - TY - JOUR AU - Li, Yan AU - Guo, Xitong AU - Hsu, Carol AU - Liu, Xiaoxiao AU - Vogel, Doug PY - 2019/6/14 TI - Exploring the Impact of the Prescription Automatic Screening System in Health Care Services: Quasi-Experiment JO - JMIR Med Inform SP - e11663 VL - 7 IS - 2 KW - prescription drug monitoring programs KW - hospital information system KW - quality of health care KW - medical errors N2 - Background: Hospitals have deployed various types of technologies to alleviate the problem of high medical costs. The cost of pharmaceuticals is one of the main drivers of medical costs. The Prescription Automatic Screening System (PASS) aims to monitor physicians? prescribing behavior, which has the potential to decrease prescription errors and medical treatment costs. However, a substantial number of cases with unsatisfactory results related to the effects of PASS have been noted. Objective: The objectives of this study were to systematically explore the imperative role of PASS on hospitals? prescription errors and medical treatment costs and examine its contingency factors to clarify the various factors associated with the effective use of PASS. Methods: To systematically examine the various effects of PASS, we adopted a quasi-experiment methodology by using a 2-year observation dataset from 2 hospitals in China. We then analyzed the data related to physicians? prescriptions both before and after the deployment of PASS and eliminated influences from a variety of perplexing factors by utilizing a control hospital that did not use a PASS system. In total, 754 physicians were included in this experiment comprising 11,054 patients: 400 physicians in the treatment group and 354 physicians in the control group. This study was also preceded by a series of interviews, which were employed to identify moderators. Thereafter, we adopted propensity score matching integrated with difference-in-differences to isolate the effects of PASS. Results: The effects of PASS on prescription errors and medical treatment costs were all significant (error: 95% CI ?0.40 to ?0.11, P=.001; costs: 95% CI ?0.75 to ?0.12, P=.007). Pressure from organizational rules and workload decreased the effect of PASS on prescription errors (95% CI 0.18-0.39; P<.001) and medical treatment costs (95% CI 0.07-0.55; P=.01), respectively. We also suspected that other pressures (eg, clinical title and risk categories of illness) also impaired physicians? attention to alerts from PASS. However, the effects of PASS did not change among physicians with a higher clinical title or when treating diseases demonstrating high risk. This may be attributed to the fact that these physicians will focus more on their patients in these situations, regardless of having access to an intelligent system. Conclusions: Although implementation of PASS decreases prescription errors and medical treatment costs, workload and organizational rules remain problematic, as they tend to impair the positive effects of auxiliary diagnosis systems on performance. This again highlights the importance of considering both technical and organizational issues to obtain the highest level of effectiveness when deploying information technology in hospitals. UR - http://medinform.jmir.org/2019/2/e11663/ UR - http://dx.doi.org/10.2196/11663 UR - http://www.ncbi.nlm.nih.gov/pubmed/31199314 ID - info:doi/10.2196/11663 ER - TY - JOUR AU - Kuipers, Esther AU - Poot, C. Charlotte AU - Wensing, Michel AU - Chavannes, H. Niels AU - de Smet, AGM Peter AU - Teichert, Martina PY - 2019/05/30 TI - Self-Management Maintenance Inhalation Therapy With eHealth (SELFIE): Observational Study on the Use of an Electronic Monitoring Device in Respiratory Patient Care and Research JO - J Med Internet Res SP - e13551 VL - 21 IS - 5 KW - eHealth KW - pharmacy KW - inhalation therapy KW - asthma KW - COPD KW - pharmacy practice research N2 - Background: Electronic inhalation monitoring devices (EIMDs) are available to remind patients with respiratory diseases to take their medication and register inhalations for feedback to patients and health care providers as well as for data collection in research settings. Objective: This study aimed to assess the validity as well as the patient-reported usability and acceptability of an EIMD. Methods: This observational study planned to include 21 community pharmacies in the Netherlands. Patient-reported inhalations were collected and compared to EIMD registrations to evaluate the positive predictive value of these registrations as actual patient inhalations. Patients received questionnaires on their experiences and acceptance. Results: A convenience sample of 32 patients was included from across 18 pharmacies, and 932 medication doses were validated. Of these, 796 registrations matched with patient-reported use (true-positive, 85.4%), and 33 inhalation registrations did not match with patient-reported use (false-positive, 3.5%). The positive predictive value was 96.0%, and 103 patient-reported inhalations were not recorded in the database (false-negative, 11.1%). Overall, patients considered the EIMD to be acceptable and easy to use, but many hesitated to continue its use. Reminders and motivational messages were not appreciated by all users, and more user-tailored features in the app were desired. Conclusions: Patients? interaction with the device in real-world settings is critical for objective measurement of medication adherence. The positive predictive value of this EIMD was found to be acceptable. However, patients reported false-negative registrations and a desire to include more user-tailored features to increase the usability and acceptability of the EIMD. UR - http://www.jmir.org/2019/5/e13551/ UR - http://dx.doi.org/10.2196/13551 UR - http://www.ncbi.nlm.nih.gov/pubmed/31148542 ID - info:doi/10.2196/13551 ER - TY - JOUR AU - Fleming, N. James AU - Treiber, Frank AU - McGillicuddy, John AU - Gebregziabher, Mulugeta AU - Taber, J. David PY - 2018/03/02 TI - Improving Transplant Medication Safety Through a Pharmacist-Empowered, Patient-Centered, mHealth-Based Intervention: TRANSAFE Rx Study Protocol JO - JMIR Res Protoc SP - e59 VL - 7 IS - 3 KW - telemedicine KW - mhealth KW - transplant KW - clinical trial KW - errors KW - adherence N2 - Background: Medication errors, adverse drug events, and nonadherence are the predominant causes of graft loss in kidney transplant recipients and lead to increased healthcare utilization. Research has demonstrated that clinical pharmacists have the unique education and training to identify these events early and develop strategies to mitigate or prevent downstream sequelae. In addition, studies utilizing mHealth interventions have demonstrated success in improving the control of chronic conditions that lead to kidney transplant deterioration. Objective: The goal of the prospective, randomized TRANSAFE Rx study is to measure the clinical and economic effectiveness of a pharmacist-led, mHealth-based intervention, as compared to usual care, in kidney transplant recipients. Methods: TRANSAFE Rx is a 12-month, parallel, two-arm, 1:1 randomized controlled clinical trial involving 136 participants (68 in each arm) and measuring the clinical and economic effectiveness of a pharmacist-led intervention which utilizes an innovative mobile health application to improve medication safety and health outcomes, as compared to usual posttransplant care. Results: The primary outcome measure of this study will be the incidence and severity of MEs and ADRs, which will be identified, categorized, and compared between the intervention and control cohorts. The exploratory outcome measures of this study are to compare the incidence and severity of acute rejections, infections, graft function, graft loss, and death between research cohorts and measure the association between medication safety issues and these events. Additional data that will be gathered includes sociodemographics, health literacy, depression, and support. Conclusions: With this report we describe the study design, methods, and outcome measures that will be utilized in the ongoing TRANSAFE Rx clinical trial. Trial Registration: ClinicalTrials.gov NCT03247322: https://clinicaltrials.gov/ct2/show/NCT03247322 (Archived by WebCite at http://www.webcitation.org/6xcSUnuzW) UR - https://www.researchprotocols.org/2018/3/e59/ UR - http://dx.doi.org/10.2196/resprot.9078 UR - http://www.ncbi.nlm.nih.gov/pubmed/29500161 ID - info:doi/10.2196/resprot.9078 ER - TY - JOUR AU - Lämsä, Elina AU - Timonen, Johanna AU - Ahonen, Riitta PY - 2018/02/23 TI - Pharmacy Customers? Experiences With Electronic Prescriptions: Cross-Sectional Survey on Nationwide Implementation in Finland JO - J Med Internet Res SP - e68 VL - 20 IS - 2 KW - electronic prescribing KW - pharmacies KW - patient satisfaction KW - surveys and questionnaires N2 - Background: One of the forerunners in electronic health, Finland has introduced electronic prescriptions (ePrescriptions) nationwide by law. This has led to significant changes for pharmacy customers. Despite the worldwide ambition to develop ePrescription services, there are few reports of nationally adopted systems and particularly on the experiences of pharmacy customers. Objective: The aim of this study was to investigate Finnish pharmacy customers? (1) experiences with purchasing medicines with ePrescriptions; (2) experiences with renewing ePrescriptions and acting on behalf of someone else at the pharmacy; (3) ways in which customers keep up to date with their ePrescriptions; and (4) overall satisfaction with ePrescriptions. Methods: Questionnaires were distributed to 2913 pharmacy customers aged ?18 years purchasing prescription medicines for themselves with an ePrescription in 18 community pharmacies across Finland in autumn 2015. Customers? experiences were explored with 10 structured questions. The data were stored in SPSS for Windows and subjected to descriptive analysis, chi-square, Fisher exact, Kolmogorov-Smirnov, the Mann-Whitney U, and Kruskal-Wallis tests. Results: Completed questionnaires were returned by 1288 customers, a response rate of 44.19% (1288/2913). The majority of the respondents did not encounter any problems during pharmacy visits (1161/1278, 90.85%) and were informed about the current status of their ePrescriptions after their medication was dispensed (1013/1276, 79.44%). Over half of the respondents had usually received a patient instruction sheet from their physician (752/1255, 59.92%), and nearly all of them regarded its content as clear (711/724, 98.2%). Half of the respondents had renewed their ePrescriptions through the pharmacy (645/1281, 50.35%), and one-third of them had acted on behalf of someone else with ePrescriptions (432/1280, 33.75%). Problems were rarely encountered in the renewal process (49/628, 7.8%) or when acting on behalf of another person (25/418, 6.0%) at the pharmacy. The most common way of keeping up to date with ePrescriptions was to ask at the pharmacy (631/1278, 49.37%). The vast majority of the respondents were satisfied with ePrescriptions as a whole (1221/1274, 95.84%). Conclusions: Finnish pharmacy customers are satisfied with the recently implemented nationwide ePrescription system. They seldom have any difficulties purchasing medicines, renewing their ePrescriptions, or acting on behalf of someone else at the pharmacy. Customers usually keep up to date with their ePrescriptions by asking at the pharmacy. However, some customers are unaware of the practices or have difficulty keeping up to date with the status of their ePrescriptions. The provision of relevant information and assistance by health care professionals is therefore required to promote customers? adoption of the ePrescription system. UR - http://www.jmir.org/2018/2/e68/ UR - http://dx.doi.org/10.2196/jmir.9367 UR - http://www.ncbi.nlm.nih.gov/pubmed/29475826 ID - info:doi/10.2196/jmir.9367 ER - TY - JOUR AU - Keyworth, Chris AU - Hart, Jo AU - Thoong, Hong AU - Ferguson, Jane AU - Tully, Mary PY - 2017/08/01 TI - A Technological Innovation to Reduce Prescribing Errors Based on Implementation Intentions: The Acceptability and Feasibility of MyPrescribe JO - JMIR Hum Factors SP - e17 VL - 4 IS - 3 KW - drug prescribing KW - behavior and behavior mechanisms KW - clinical competence KW - qualitative research KW - mobile applications KW - pharmacists KW - patient safety KW - telemedicine N2 - Background: Although prescribing of medication in hospitals is rarely an error-free process, prescribers receive little feedback on their mistakes and ways to change future practices. Audit and feedback interventions may be an effective approach to modifying the clinical practice of health professionals, but these may pose logistical challenges when used in hospitals. Moreover, such interventions are often labor intensive. Consequently, there is a need to develop effective and innovative interventions to overcome these challenges and to improve the delivery of feedback on prescribing. Implementation intentions, which have been shown to be effective in changing behavior, link critical situations with an appropriate response; however, these have rarely been used in the context of improving prescribing practices. Objective: Semistructured qualitative interviews were conducted to evaluate the acceptability and feasibility of providing feedback on prescribing errors via MyPrescribe, a mobile-compatible website informed by implementation intentions. Methods: Data relating to 200 prescribing errors made by 52 junior doctors were collected by 11 hospital pharmacists. These errors were populated into MyPrescribe, where prescribers were able to construct their own personalized action plans. Qualitative interviews with a subsample of 15 junior doctors were used to explore issues regarding feasibility and acceptability of MyPrescribe and their experiences of using implementation intentions to construct prescribing action plans. Framework analysis was used to identify prominent themes, with findings mapped to the behavioral components of the COM-B model (capability, opportunity, motivation, and behavior) to inform the development of future interventions. Results: MyPrescribe was perceived to be effective in providing opportunities for critical reflection on prescribing errors and to complement existing training (such as junior doctors? e-portfolio). The participants were able to provide examples of how they would use ?If-Then? plans for patient management. Technology, as opposed to other methods of learning (eg, traditional ?paper based? learning), was seen as a positive advancement for continued learning. Conclusions: MyPrescribe was perceived as an acceptable and feasible learning tool for changing prescribing practices, with participants suggesting that it would make an important addition to medical prescribers? training in reflective practice. MyPrescribe is a novel theory-based technological innovation that provides the platform for doctors to create personalized implementation intentions. Applying the COM-B model allows for a more detailed understanding of the perceived mechanisms behind prescribing practices and the ways in which interventions aimed at changing professional practice can be implemented. UR - http://humanfactors.jmir.org/2017/3/e17/ UR - http://dx.doi.org/10.2196/humanfactors.7153 UR - http://www.ncbi.nlm.nih.gov/pubmed/28765104 ID - info:doi/10.2196/humanfactors.7153 ER - TY - JOUR UR - ID - ref1 ER - TY - JOUR AU - Phillips, L. Jennifer AU - Shea, M. Jennifer AU - Leung, Valerie AU - MacDonald, Don PY - 2015/01/06 TI - Impact of Early Electronic Prescribing on Pharmacists? Clarification Calls in Four Community Pharmacies Located in St John?s, Newfoundland JO - JMIR Med Inform SP - e2 VL - 3 IS - 1 KW - electronic prescribing KW - pharmacy KW - pharmacists KW - Clinical Pharmacy Information Systems N2 - Background: Electronic prescribing (e-prescribing) can potentially help prevent medication errors. As the use of e-prescribing increases across Canada, understanding the benefits and gaps of early e-prescribing can help inform deployment of future e-prescribing systems. Objective: The purpose of this exploratory study was to determine the prevalence of, reasons for, and average time taken for pharmacist clarification calls to prescribers for electronic medical record (EMR)-generated and handwritten prescriptions. Methods: Four community pharmacies in St John?s, Newfoundland, Canada prospectively collected information on clarification calls to prescribers for new prescriptions over a period of 17 to 19 weeks. Four semistructured interviews were conducted following the data collection period to gain further insight. Results: An estimated 1.33% of handwritten prescriptions required clarification compared with 0.66% of EMR-generated prescriptions. Overall, 1.11% of prescriptions required clarification with the prescriber. While illegibility was eliminated with EMR-generated prescriptions, clarification was still required for missing information (24%) and appropriateness (51%). Key themes, including errors unique to EMR-generated prescriptions, emerged from the qualitative interviews. Conclusions: Advanced e-prescribing functionality will enable secure transmission of prescriptions from prescribers to a patient?s pharmacy of choice through a provincial electronic Drug Information System (DIS)/Pharmacy Network, which will lessen the need for clarification calls, especially in the domains of missing information and appropriateness of the prescription. This exploratory study provides valuable insight into the benefits and gaps of early e-prescribing. Advanced e-prescribing systems will provide an opportunity for further realization of quality and safety benefits related to medication prescribing. UR - http://medinform.jmir.org/2015/1/e2/ UR - http://dx.doi.org/10.2196/medinform.3541 UR - http://www.ncbi.nlm.nih.gov/pubmed/25595165 ID - info:doi/10.2196/medinform.3541 ER -