TY - JOUR AU - Demuth, Stanislas AU - De Sèze, Jérôme AU - Edan, Gilles AU - Ziemssen, Tjalf AU - Simon, Françoise AU - Gourraud, Pierre-Antoine PY - 2025/1/28 TI - Digital Representation of Patients as Medical Digital Twins: Data-Centric Viewpoint JO - JMIR Med Inform SP - e53542 VL - 13 KW - digital twin KW - artificial intelligence KW - data architecture KW - synthetic data KW - computational modeling KW - precision medicine KW - conceptual clarification KW - conceptual KW - patient KW - medicine KW - health record KW - digital records KW - synthetic patient UR - https://medinform.jmir.org/2025/1/e53542 UR - http://dx.doi.org/10.2196/53542 ID - info:doi/10.2196/53542 ER - TY - JOUR AU - Zhang, Lan AU - Bullen, Christopher AU - Chen, Jinsong PY - 2025/1/20 TI - Digital Health Innovations to Catalyze the Transition to Value-Based Health Care JO - JMIR Med Inform SP - e57385 VL - 13 KW - digital health KW - value-based health care KW - VBHC KW - patient-reported outcome measures KW - PROM KW - digital transformation KW - health care innovation KW - patient-centric care KW - health technology KW - patient-reported outcome KW - PRO KW - outcome measure KW - telehealth KW - telemedicine KW - eHealth KW - personalized KW - customized KW - engagement KW - patient-centered care KW - standardization KW - implementation UR - https://medinform.jmir.org/2025/1/e57385 UR - http://dx.doi.org/10.2196/57385 ID - info:doi/10.2196/57385 ER - TY - JOUR AU - Gabrielli, Silvia AU - Mayora Ibarra, Oscar AU - Forti, Stefano PY - 2025/1/16 TI - A Holistic Digital Health Framework to Support Health Prevention Strategies in the First 1000 Days JO - JMIR Pediatr Parent SP - e55235 VL - 8 KW - digital health KW - digital therapeutics KW - behavioral intervention technology KW - prevention KW - citizen science KW - first 1000 days UR - https://pediatrics.jmir.org/2025/1/e55235 UR - http://dx.doi.org/10.2196/55235 ID - info:doi/10.2196/55235 ER - TY - JOUR AU - Walzer, Stefan AU - Barthel, Carolin AU - Pazouki, Ronja AU - Marx, Helga AU - Ziegler, Sven AU - Koenig, Peter AU - Kugler, Christiane AU - Jobst, Stefan PY - 2025/1/15 TI - Teaching in the Digital Age?Developing a Support Program for Nursing Education Providers: Design-Based Research JO - JMIR Form Res SP - e66109 VL - 9 KW - digital competencies KW - nursing education KW - support program KW - needs assessment KW - design-based research KW - feasibility study KW - nursing education provider KW - qualitative research KW - nurse KW - health care KW - focus group KW - digital age KW - expert consultation KW - thematic content analysis KW - feasibility test KW - satisfaction KW - competency-based approach KW - workplace barrier KW - health care digitalization KW - digital technology N2 - Background: Health care systems and the nursing profession worldwide are being transformed by technology and digitalization. Nurses acquire digital competence through their own experience in daily practice, but also from education and training; nursing education providers thus play an important role. While nursing education providers have some level of digital competence, there is a need for ongoing training and support for them to develop more advanced skills and effectively integrate technology into their teaching. Objective: This study aims to develop a needs-based support program for nursing education providers to foster digital competencies and to test this intervention. Methods: We used a design-based research approach, incorporating iterative development with expert consultation to create and evaluate a support program for nursing education providers. Focus groups were conducted online to assess needs, and thematic content analysis was used to derive key insights. The support program was then refined through expert feedback and subjected to a feasibility and satisfaction test, with participant evaluations analyzed descriptively. Results: Six main categories emerged from the focus groups, highlighting key areas, including the use of digital technology, ongoing support needs, and the current state of digitalization in nursing education. The support program was developed based on these findings, with expert validation leading to adjustments in timing, content prioritization, and platform integration. Preliminary testing showed good overall satisfaction with the support program, although participants suggested improvements in content relevance and digital platform usability. Conclusions: Although the feasibility test showed high satisfaction with the support program, low participation rates and limited perceived knowledge gain were major concerns. The results suggest that while the program was well received, further refinements, including a focus on competency-based approaches and addressing workplace barriers, are needed to increase participation and effectiveness of such interventions. The findings of this research can be used as a basis for the development of similar programs in other educational and health care contexts. UR - https://formative.jmir.org/2025/1/e66109 UR - http://dx.doi.org/10.2196/66109 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/66109 ER - TY - JOUR AU - Kip, Hanneke AU - Beerlage-de Jong, Nienke AU - van Gemert-Pijnen, C. Lisette J. E. W. AU - Kelders, M. Saskia PY - 2025/1/13 TI - The CeHRes Roadmap 2.0: Update of a Holistic Framework for Development, Implementation, and Evaluation of eHealth Technologies JO - J Med Internet Res SP - e59601 VL - 27 KW - eHealth development KW - eHealth implementation KW - CeHRes Roadmap KW - participatory development KW - human-centered design KW - persuasive design KW - eHealth framework UR - https://www.jmir.org/2025/1/e59601 UR - http://dx.doi.org/10.2196/59601 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/59601 ER - TY - JOUR AU - Auyeung, Larry AU - Mak, S. Winnie W. AU - Tsang, Zoe Ella PY - 2024/12/19 TI - Service Attributes and Acceptability of Digital and Nondigital Depression Management Methods Among Individuals With Depressive Symptoms: Survey Study JO - JMIR Form Res SP - e55450 VL - 8 KW - eHealth KW - acceptability KW - user preference KW - diffusion of innovation KW - mental health services N2 - Background: Academic research on digital mental health tends to focus on its efficacy and effectiveness, with much less attention paid to user preferences and experiences in real-world settings. Objective: This study aims to analyze service characteristics that service users value and compare the extent to which various digital and nondigital mental health treatments and management methods fulfill users? expectations. Methods: A total of 114 people with at least moderate levels of depressive symptoms (as measured by Patient Health Questionnaire?9 score ?10) completed a web-based questionnaire measuring their awareness and adoption of digital mental health services and their valuation of 15 psychological service attributes, including effectiveness, credibility, waiting time, and more. They were also assessed on their expectations toward seven common mental health treatments and management methods, including (1) face-to-face psychological intervention, (2) medication, (3) guided internet-based psychological intervention, (4) face-to-face counseling service, (5) self-guided mental health apps for depression, (6) self-help bibliotherapy, and (7) psychological intervention via videoconferencing. Results: A Friedman test with a Dunn posttest showed the average importance rank of ?effectiveness? was significantly higher than all other measured attributes. ?Privacy,? ?credibility,? and ?cost? were ranked as equally important. Participants rated face-to-face psychological intervention the most effective management method, while other digital management methods were perceived as less effective. Medication was perceived as the least appealing method, while other methods were deemed equally appealing. Face-to-face psychological intervention, medication, and counseling were considered less satisfactory due to their higher costs and longer waiting times when compared to digital services. Repeated measures ANOVA showed some forms of management method were more likely to be adopted, including guided internet-based psychological intervention, psychological intervention via videoconferencing, face-to-face psychological intervention, and face-to-face counseling services provided by a counselor as compared to self-guided mobile apps, self-help bibliotherapy, and medication. Conclusions: The study highlights the importance of considering multiple service attributes beyond effectiveness in depression management methods, despite effectiveness being regarded as the most crucial factor using the rank method. Compared to nondigital services, digital services were identified as having specific strengths as perceived by users. Future dissemination and promotion efforts may focus on debunking myths of guided internet-based psychological intervention as a less effective option and promoting the particular service strengths of digital services. UR - https://formative.jmir.org/2024/1/e55450 UR - http://dx.doi.org/10.2196/55450 UR - http://www.ncbi.nlm.nih.gov/pubmed/39699956 ID - info:doi/10.2196/55450 ER - TY - JOUR AU - Naccarella, Lucio AU - Rawstorn, Charles Jonathan AU - Kelly, Jaimon AU - Quested, Eleanor AU - Jenkinson, Stuart AU - Kwasnicka, Dominika PY - 2024/12/10 TI - Unlocking the Potential for Implementation of Equitable, Digitally Enabled Citizen Science: Multidisciplinary Digital Health Perspective JO - J Med Internet Res SP - e50491 VL - 26 KW - citizen science KW - digital health KW - equity KW - implementation science KW - community KW - research KW - health inequality KW - health equity KW - health integration KW - mental well-being KW - well-being UR - https://www.jmir.org/2024/1/e50491 UR - http://dx.doi.org/10.2196/50491 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/50491 ER - TY - JOUR AU - Gupta, Vikash AU - Erdal, Barbaros AU - Ramirez, Carolina AU - Floca, Ralf AU - Genereaux, Bradley AU - Bryson, Sidney AU - Bridge, Christopher AU - Kleesiek, Jens AU - Nensa, Felix AU - Braren, Rickmer AU - Younis, Khaled AU - Penzkofer, Tobias AU - Bucher, Michael Andreas AU - Qin, Melvin Ming AU - Bae, Gigon AU - Lee, Hyeonhoon AU - Cardoso, Jorge M. AU - Ourselin, Sebastien AU - Kerfoot, Eric AU - Choudhury, Rahul AU - White, D. Richard AU - Cook, Tessa AU - Bericat, David AU - Lungren, Matthew AU - Haukioja, Risto AU - Shuaib, Haris PY - 2024/12/9 TI - Current State of Community-Driven Radiological AI Deployment in Medical Imaging JO - JMIR AI SP - e55833 VL - 3 KW - radiology KW - open-source KW - radiology in practice KW - deep learning KW - artificial intelligence KW - imaging informatics KW - clinical deployment KW - imaging KW - medical informatics KW - workflow KW - operation KW - implementation KW - adoption KW - taxonomy KW - use case KW - model KW - integration KW - machine learning KW - mobile phone UR - https://ai.jmir.org/2024/1/e55833 UR - http://dx.doi.org/10.2196/55833 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/55833 ER - TY - JOUR AU - Varghese, Julian AU - Schuster, Alexander AU - Poschkamp, Broder AU - Yildirim, Kemal AU - Oehm, Johannes AU - Berens, Philipp AU - Müller, Sarah AU - Gervelmeyer, Julius AU - Koch, Lisa AU - Hoffmann, Katja AU - Sedlmayr, Martin AU - Kakkassery, Vinodh AU - Kohlbacher, Oliver AU - Merle, David AU - Bartz-Schmidt, Ulrich Karl AU - Ueffing, Marius AU - Stahl, Dana AU - Leddig, Torsten AU - Bialke, Martin AU - Hampf, Christopher AU - Hoffmann, Wolfgang AU - Berthe, Sebastian AU - Waltemath, Dagmar AU - Walter, Peter AU - Lipprandt, Myriam AU - Röhrig, Rainer AU - Storp, Julian Jens AU - Zimmermann, Alexander Julian AU - Holtrup, Lea AU - Brix, Tobias AU - Stahl, Andreas AU - Eter, Nicole PY - 2024/12/5 TI - EyeMatics: An Ophthalmology Use Case Within the German Medical Informatics Initiative JO - JMIR Med Inform SP - e60851 VL - 12 KW - digital ophthalmology KW - interoperability KW - precision ophthalmology KW - patient engagement KW - Germany KW - clinical use KW - intravitreal KW - injections KW - eye KW - treatment KW - patient data KW - framework KW - AI KW - artificial intelligence KW - biomarker KW - retinal KW - scan KW - user-centered KW - observational UR - https://medinform.jmir.org/2024/1/e60851 UR - http://dx.doi.org/10.2196/60851 ID - info:doi/10.2196/60851 ER - TY - JOUR AU - Liu, Shuimei AU - Guo, Raymond L. PY - 2024/11/19 TI - Data Ownership in the AI-Powered Integrative Health Care Landscape JO - JMIR Med Inform SP - e57754 VL - 12 KW - data ownership KW - integrative healthcare KW - artificial intelligence KW - AI KW - ownership KW - data science KW - governance KW - consent KW - privacy KW - security KW - access KW - model KW - framework KW - transparency UR - https://medinform.jmir.org/2024/1/e57754 UR - http://dx.doi.org/10.2196/57754 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/57754 ER - TY - JOUR AU - Piera-Jiménez, Jordi AU - Carot-Sans, Gerard AU - Ramiro-Pareta, Marina AU - Nogueras, Mercedes Maria AU - Folguera-Profitós, Júlia AU - Ródenas, Pepi AU - Jiménez-Rueda, Alba AU - de Pando Navarro, Thais AU - Mira Palacios, Antoni Josep AU - Fajardo, Carles Joan AU - Ustrell Campillo, Joan AU - Vela, Emili AU - Monterde, David AU - Valero-Bover, Damià AU - Bonet, Tara AU - Tarrasó-Urios, Guillermo AU - Cantenys-Sabà, Roser AU - Fabregat-Fabregat, Pau AU - Gómez Oliveros, Beatriz AU - Berdún, Jesús AU - Michelena, Xabier AU - Cano, Isaac AU - González-Colom, Rubèn AU - Roca, Josep AU - Solans, Oscar AU - Pontes, Caridad AU - Pérez-Sust, Pol PY - 2024/11/18 TI - A 25-Year Retrospective of Health IT Infrastructure Building: The Example of the Catalonia Region JO - J Med Internet Res SP - e58933 VL - 26 KW - health ITs KW - eHealth KW - integrated care KW - open platforms KW - interoperability KW - Catalonia KW - digitalization KW - health care structure KW - health care delivery KW - integrated pathway KW - integrated treatment plan KW - process management UR - https://www.jmir.org/2024/1/e58933 UR - http://dx.doi.org/10.2196/58933 UR - http://www.ncbi.nlm.nih.gov/pubmed/39556831 ID - info:doi/10.2196/58933 ER - TY - JOUR AU - Willcockson, Ursula Irmgard AU - Valdes, Herman Ignacio PY - 2024/11/14 TI - Unintended Consequences of Data Sharing Under the Meaningful Use Program JO - JMIR Med Inform SP - e52675 VL - 12 KW - electronic health records KW - EHR KW - medical record KW - interoperability KW - health information interoperability KW - clinical burden KW - Medicare KW - Medicaid KW - reimbursement KW - data science KW - data governance KW - data breach KW - cybersecurity KW - privacy UR - https://medinform.jmir.org/2024/1/e52675 UR - http://dx.doi.org/10.2196/52675 ID - info:doi/10.2196/52675 ER - TY - JOUR AU - Nagarajan, Radha AU - Kondo, Midori AU - Salas, Franz AU - Sezgin, Emre AU - Yao, Yuan AU - Klotzman, Vanessa AU - Godambe, A. Sandip AU - Khan, Naqi AU - Limon, Alfonso AU - Stephenson, Graham AU - Taraman, Sharief AU - Walton, Nephi AU - Ehwerhemuepha, Louis AU - Pandit, Jay AU - Pandita, Deepti AU - Weiss, Michael AU - Golden, Charles AU - Gold, Adam AU - Henderson, John AU - Shippy, Angela AU - Celi, Anthony Leo AU - Hogan, R. William AU - Oermann, K. Eric AU - Sanger, Terence AU - Martel, Steven PY - 2024/11/14 TI - Economics and Equity of Large Language Models: Health Care Perspective JO - J Med Internet Res SP - e64226 VL - 26 KW - large language model KW - LLM KW - health care KW - economics KW - equity KW - cloud service providers KW - cloud KW - health outcome KW - implementation KW - democratization UR - https://www.jmir.org/2024/1/e64226 UR - http://dx.doi.org/10.2196/64226 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/64226 ER - TY - JOUR AU - van Maurik, S. I. AU - Doodeman, J. H. AU - Veeger-Nuijens, W. B. AU - Möhringer, M. R. P. AU - Sudiono, R. D. AU - Jongbloed, W. AU - van Soelen, E. PY - 2024/10/24 TI - Targeted Development and Validation of Clinical Prediction Models in Secondary Care Settings: Opportunities and Challenges for Electronic Health Record Data JO - JMIR Med Inform SP - e57035 VL - 12 KW - clinical prediction model KW - electronic health record KW - targeted validation KW - EHR KW - EMR KW - prediction models KW - validation KW - CPM KW - secondary care KW - machine learning KW - artificial intelligence KW - AI UR - https://medinform.jmir.org/2024/1/e57035 UR - http://dx.doi.org/10.2196/57035 ID - info:doi/10.2196/57035 ER - TY - JOUR AU - Fernando, Manasha AU - Abell, Bridget AU - McPhail, M. Steven AU - Tyack, Zephanie AU - Tariq, Amina AU - Naicker, Sundresan PY - 2024/10/17 TI - Applying the Non-Adoption, Abandonment, Scale-up, Spread, and Sustainability Framework Across Implementation Stages to Identify Key Strategies to Facilitate Clinical Decision Support System Integration Within a Large Metropolitan Health Service: Interview and Focus Group Study JO - JMIR Med Inform SP - e60402 VL - 12 KW - medical informatics KW - adoption and implementation KW - behavior KW - health systems N2 - Background: Computerized clinical decision support systems (CDSSs) enhance patient care through real-time, evidence-based guidance for health care professionals. Despite this, the effective implementation of these systems for health services presents multifaceted challenges, leading to inappropriate use and abandonment over the course of time. Using the Non-Adoption, Abandonment, Scale-Up, Spread, and Sustainability (NASSS) framework, this qualitative study examined CDSS adoption in a metropolitan health service, identifying determinants across implementation stages to optimize CDSS integration into health care practice. Objective: This study aims to identify the theory-informed (NASSS) determinants, which included multiple CDSS interventions across a 2-year period, both at the health-service level and at the individual hospital setting, that either facilitate or hinder the application of CDSSs within a metropolitan health service. In addition, this study aimed to map these determinants onto specific stages of the implementation process, thereby developing a system-level understanding of CDSS application across implementation stages. Methods: Participants involved in various stages of the implementation process were recruited (N=30). Participants took part in interviews and focus groups. We used a hybrid inductive-deductive qualitative content analysis and a framework mapping approach to categorize findings into barriers, enablers, or neutral determinants aligned to NASSS framework domains. These determinants were also mapped to implementation stages using the Active Implementation Framework stages approach. Results: Participants comprised clinical adopters (14/30, 47%), organizational champions (5/30, 16%), and those with roles in organizational clinical informatics (5/30, 16%). Most determinants were mapped to the organization level, technology, and adopter subdomains. However, the study findings also demonstrated a relative lack of long-term implementation planning. Consequently, determinants were not uniformly distributed across the stages of implementation, with 61.1% (77/126) identified in the exploration stage, 30.9% (39/126) in the full implementation stage, and 4.7% (6/126) in the installation stages. Stakeholders engaged in more preimplementation and full-scale implementation activities, with fewer cycles of monitoring and iteration activities identified. Conclusions: These findings addressed a substantial knowledge gap in the literature using systems thinking principles to identify the interdependent dynamics of CDSS implementation. A lack of sustained implementation strategies (ie, training and longer-term, adopter-level championing) weakened the sociotechnical network between developers and adopters, leading to communication barriers. More rigorous implementation planning, encompassing all 4 implementation stages, may, in a way, help in addressing the barriers identified and enhancing enablers. UR - https://medinform.jmir.org/2024/1/e60402 UR - http://dx.doi.org/10.2196/60402 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/60402 ER - TY - JOUR AU - Reis, Florian AU - Lenz, Christian AU - Gossen, Manfred AU - Volk, Hans-Dieter AU - Drzeniek, Michael Norman PY - 2024/9/5 TI - Practical Applications of Large Language Models for Health Care Professionals and Scientists JO - JMIR Med Inform SP - e58478 VL - 12 KW - artificial intelligence KW - healthcare KW - chatGPT KW - large language model KW - prompting KW - LLM KW - applications KW - AI KW - scientists KW - physicians KW - health care UR - https://medinform.jmir.org/2024/1/e58478 UR - http://dx.doi.org/10.2196/58478 ID - info:doi/10.2196/58478 ER - TY - JOUR AU - Svempe, Liga PY - 2024/9/5 TI - Exploring Impediments Imposed by the Medical Device Regulation EU 2017/745 on Software as a Medical Device JO - JMIR Med Inform SP - e58080 VL - 12 KW - software KW - artificial intelligence KW - medical device regulation KW - rights KW - digital health UR - https://medinform.jmir.org/2024/1/e58080 UR - http://dx.doi.org/10.2196/58080 UR - http://www.ncbi.nlm.nih.gov/pubmed/39235850 ID - info:doi/10.2196/58080 ER - TY - JOUR AU - Julian, Silva Guilherme AU - Shau, Wen-Yi AU - Chou, Hsu-Wen AU - Setia, Sajita PY - 2024/8/15 TI - Bridging Real-World Data Gaps: Connecting Dots Across 10 Asian Countries JO - JMIR Med Inform SP - e58548 VL - 12 KW - Asia KW - electronic medical records KW - EMR KW - health care databases KW - health technology assessment KW - HTA KW - real-world data KW - real-world evidence UR - https://medinform.jmir.org/2024/1/e58548 UR - http://dx.doi.org/10.2196/58548 UR - http://www.ncbi.nlm.nih.gov/pubmed/39026427 ID - info:doi/10.2196/58548 ER - TY - JOUR AU - Sendra-Portero, Francisco AU - Lorenzo-Álvarez, Rocío AU - Rudolphi-Solero, Teodoro AU - Ruiz-Gómez, José Miguel PY - 2024/8/6 TI - The Second Life Metaverse and Its Usefulness in Medical Education After a Quarter of a Century JO - J Med Internet Res SP - e59005 VL - 26 KW - medical education KW - medical students KW - postgraduate KW - computer simulation KW - virtual worlds KW - metaverse UR - https://www.jmir.org/2024/1/e59005 UR - http://dx.doi.org/10.2196/59005 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/59005 ER - TY - JOUR AU - Han Sr, Wei AU - Li 2nd, Yuanting AU - Chen 3rd, Changgen AU - Huang, Danni AU - Wang, Junchao AU - Li, Xiang AU - Ji, Zhongliang AU - Li, Qin AU - Li, Zhuang PY - 2024/8/1 TI - 5G Key Technologies for Helicopter Aviation Medical Rescue JO - J Med Internet Res SP - e50355 VL - 26 KW - low airspace KW - helicopters KW - medical aid KW - 5G technology KW - aeronautical engineering UR - https://www.jmir.org/2024/1/e50355 UR - http://dx.doi.org/10.2196/50355 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/50355 ER - TY - JOUR AU - Zhui, Li AU - Yhap, Nina AU - Liping, Liu AU - Zhengjie, Wang AU - Zhonghao, Xiong AU - Xiaoshu, Yuan AU - Hong, Cui AU - Xuexiu, Liu AU - Wei, Ren PY - 2024/7/25 TI - Impact of Large Language Models on Medical Education and Teaching Adaptations JO - JMIR Med Inform SP - e55933 VL - 12 KW - large language models KW - medical education KW - opportunities KW - challenges KW - critical thinking KW - educator UR - https://medinform.jmir.org/2024/1/e55933 UR - http://dx.doi.org/10.2196/55933 ID - info:doi/10.2196/55933 ER - TY - JOUR AU - Chindamorragot, Naruemol AU - Suitthimeathegorn, Orawan AU - Garg, Amit PY - 2024/7/24 TI - Centralized Pump Monitoring System: Perception on Utility and Workflows by Nurses in a Tertiary Hospital JO - Asian Pac Isl Nurs J SP - e60116 VL - 8 KW - infusion management KW - nurse efficiency KW - pump monitoring system KW - nurse attrition UR - https://apinj.jmir.org/2024/1/e60116 UR - http://dx.doi.org/10.2196/60116 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/60116 ER - TY - JOUR AU - Lakew, Nathan AU - Jonsson, Jakob AU - Lindner, Philip PY - 2024/7/23 TI - Probing the Role of Digital Payment Solutions in Gambling Behavior: Preliminary Results From an Exploratory Focus Group Session With Problem Gamblers JO - JMIR Hum Factors SP - e54951 VL - 11 KW - digital payment solutions KW - online gambling behavior KW - sociotechnical KW - subjective experience KW - focus group N2 - Background: Technology has significantly reshaped the landscape and accessibility of gambling, creating uncharted territory for researchers and policy makers involved in the responsible gambling (RG) agenda. Digital payment solutions (DPS) are the latest addition of technology-based services in gambling and are now prominently used for deposit and win withdrawal. The seamless collaboration between online gambling operators and DPS, however, has raised concerns regarding the potential role of DPS platforms in facilitating harmful behavior. Objective: Using a focus group session with problem gamblers, this study describes a preliminary investigation of the role of DPS in the online gambling context and its influence on players? gambling habits, financial behavior, choices of gambling environment, and the overall outcome of gambling subjective experiences. Methods: A total of 6 problem gamblers participated in a one-and-half-hour focus group session to discuss how DPSs are integrated into their everyday gambling habits, what motivates them to use DPS, and what shifts they observe in their gambling behavior. Thematic analysis was used to analyze the empirical evidence with a mix of inductive and deductive research approaches as a knowledge claim strategy. Results: Our initial findings revealed that the influence of DPSs in online gambling is multifaced where, on the one hand, their ability to integrate with players? existing habits seamlessly underscores the facilitating role they play in potentially maximizing harm. On the other hand, we find preliminary evidence that DPSs can have a direct influence on gambling outcomes in both subtle and pervasive ways?nudging, institutionalizing, constraining, or triggering players? gambling activities. This study also highlights the increasingly interdisciplinary nature of online gambling, and it proposes a preliminary conceptual framework to illustrate the sociotechnical interplay between DPS and gambling habits that ultimately capture the outcome of gambling?s subjective experience. Conclusions: Disguised as a passive payment enabler, the role of DPS has so far received scant attention; however, this exploratory qualitative study demonstrates that given the technological advantage and access to customer financial data, DPS can become a potent platform to enable and at times trigger harmful gambling. In addition, DPS?s bird?s-eye view of cross-operator gambling behavior can open up an opportunity for researchers and policy makers to explore harm reduction measures that can be implemented at the digital payment level for gambling customers. Finally, more interdisciplinary studies are needed to formulate the sociotechnical nature of online gambling and holistic harm minimization strategy. UR - https://humanfactors.jmir.org/2024/1/e54951 UR - http://dx.doi.org/10.2196/54951 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/54951 ER - TY - JOUR AU - Lamer, Antoine AU - Saint-Dizier, Chloé AU - Paris, Nicolas AU - Chazard, Emmanuel PY - 2024/7/17 TI - Data Lake, Data Warehouse, Datamart, and Feature Store: Their Contributions to the Complete Data Reuse Pipeline JO - JMIR Med Inform SP - e54590 VL - 12 KW - data reuse KW - data lake KW - data warehouse KW - feature extraction KW - datamart KW - feature store UR - https://medinform.jmir.org/2024/1/e54590 UR - http://dx.doi.org/10.2196/54590 ID - info:doi/10.2196/54590 ER - TY - JOUR AU - Faust, Louis AU - Wilson, Patrick AU - Asai, Shusaku AU - Fu, Sunyang AU - Liu, Hongfang AU - Ruan, Xiaoyang AU - Storlie, Curt PY - 2024/6/28 TI - Considerations for Quality Control Monitoring of Machine Learning Models in Clinical Practice JO - JMIR Med Inform SP - e50437 VL - 12 KW - artificial intelligence KW - machine learning KW - implementation science KW - quality control KW - monitoring KW - patient safety UR - https://medinform.jmir.org/2024/1/e50437 UR - http://dx.doi.org/10.2196/50437 UR - http://www.ncbi.nlm.nih.gov/pubmed/38941140 ID - info:doi/10.2196/50437 ER - TY - JOUR AU - Lu, Linken AU - Lu, Tangsheng AU - Tian, Chunyu AU - Zhang, Xiujun PY - 2024/6/28 TI - AI: Bridging Ancient Wisdom and Modern Innovation in Traditional Chinese Medicine JO - JMIR Med Inform SP - e58491 VL - 12 KW - traditional Chinese medicine KW - TCM KW - artificial intelligence KW - AI KW - diagnosis UR - https://medinform.jmir.org/2024/1/e58491 UR - http://dx.doi.org/10.2196/58491 UR - http://www.ncbi.nlm.nih.gov/pubmed/38941141 ID - info:doi/10.2196/58491 ER - TY - JOUR AU - Richter, Gesine AU - Krawczak, Michael PY - 2024/6/18 TI - How to Elucidate Consent-Free Research Use of Medical Data: A Case for ?Health Data Literacy? JO - JMIR Med Inform SP - e51350 VL - 12 KW - health data literacy KW - informed consent KW - broad consent KW - data sharing KW - data collection KW - data donation KW - data linkage KW - personal health data UR - https://medinform.jmir.org/2024/1/e51350 UR - http://dx.doi.org/10.2196/51350 ID - info:doi/10.2196/51350 ER - TY - JOUR AU - Nkoy, L. Flory AU - Stone, L. Bryan AU - Zhang, Yue AU - Luo, Gang PY - 2024/4/17 TI - A Roadmap for Using Causal Inference and Machine Learning to Personalize Asthma Medication Selection JO - JMIR Med Inform SP - e56572 VL - 12 KW - asthma KW - causal inference KW - forecasting KW - machine learning KW - decision support KW - drug KW - drugs KW - pharmacy KW - pharmacies KW - pharmacology KW - pharmacotherapy KW - pharmaceutic KW - pharmaceutics KW - pharmaceuticals KW - pharmaceutical KW - medication KW - medications KW - medication selection KW - respiratory KW - pulmonary KW - forecast KW - ICS KW - inhaled corticosteroid KW - inhaler KW - inhaled KW - corticosteroid KW - corticosteroids KW - artificial intelligence KW - personalized KW - customized UR - https://medinform.jmir.org/2024/1/e56572 UR - http://dx.doi.org/10.2196/56572 UR - http://www.ncbi.nlm.nih.gov/pubmed/38630536 ID - info:doi/10.2196/56572 ER - TY - JOUR AU - Asgari, Elham AU - Kaur, Japsimar AU - Nuredini, Gani AU - Balloch, Jasmine AU - Taylor, M. Andrew AU - Sebire, Neil AU - Robinson, Robert AU - Peters, Catherine AU - Sridharan, Shankar AU - Pimenta, Dominic PY - 2024/4/12 TI - Impact of Electronic Health Record Use on Cognitive Load and Burnout Among Clinicians: Narrative Review JO - JMIR Med Inform SP - e55499 VL - 12 KW - electronic health record KW - cognitive load KW - burnout KW - technology KW - clinician UR - https://medinform.jmir.org/2024/1/e55499 UR - http://dx.doi.org/10.2196/55499 UR - http://www.ncbi.nlm.nih.gov/pubmed/38607672 ID - info:doi/10.2196/55499 ER - TY - JOUR AU - Washington, Peter PY - 2024/4/11 TI - A Perspective on Crowdsourcing and Human-in-the-Loop Workflows in Precision Health JO - J Med Internet Res SP - e51138 VL - 26 KW - crowdsourcing KW - digital medicine KW - human-in-the-loop KW - human in the loop KW - human-AI collaboration KW - machine learning KW - precision health KW - artificial intelligence KW - AI UR - https://www.jmir.org/2024/1/e51138 UR - http://dx.doi.org/10.2196/51138 UR - http://www.ncbi.nlm.nih.gov/pubmed/38602750 ID - info:doi/10.2196/51138 ER - TY - JOUR AU - Karadag, Serap Ayse AU - Kandi, Basak AU - Sanl?, Berna AU - Ulusal, Hande AU - Basusta, Hasan AU - Sener, Seray AU - Cal?ka, Sinem PY - 2024/3/28 TI - Social Media Use in Dermatology in Turkey: Challenges and Tips for Patient Health JO - JMIR Dermatol SP - e51267 VL - 7 KW - social media KW - dermatology KW - internet KW - health promotion KW - patient education KW - Instagram KW - YouTube KW - online social networking KW - social networking KW - Turkey KW - patient health KW - skin KW - skin disease KW - skincare KW - cosmetics KW - digital communication KW - misinformation UR - https://derma.jmir.org/2024/1/e51267 UR - http://dx.doi.org/10.2196/51267 UR - http://www.ncbi.nlm.nih.gov/pubmed/38546714 ID - info:doi/10.2196/51267 ER - TY - JOUR AU - Kim, Meelim AU - Patrick, Kevin AU - Nebeker, Camille AU - Godino, Job AU - Stein, Spencer AU - Klasnja, Predrag AU - Perski, Olga AU - Viglione, Clare AU - Coleman, Aaron AU - Hekler, Eric PY - 2024/3/5 TI - The Digital Therapeutics Real-World Evidence Framework: An Approach for Guiding Evidence-Based Digital Therapeutics Design, Development, Testing, and Monitoring JO - J Med Internet Res SP - e49208 VL - 26 KW - accessible KW - decision making KW - decision KW - decision-based evidence-making KW - development KW - digital therapeutics KW - medication adherence KW - monitoring KW - pharmaceuticals KW - public health KW - real-world data KW - real-world evidence KW - safe KW - testing KW - therapeutics UR - https://www.jmir.org/2024/1/e49208 UR - http://dx.doi.org/10.2196/49208 UR - http://www.ncbi.nlm.nih.gov/pubmed/38441954 ID - info:doi/10.2196/49208 ER - TY - JOUR AU - Bhargava, Hansa AU - Salomon, Carmela AU - Suresh, Srinivasan AU - Chang, Anthony AU - Kilian, Rachel AU - Stijn, van Diana AU - Oriol, Albert AU - Low, Daniel AU - Knebel, Ashley AU - Taraman, Sharief PY - 2024/2/29 TI - Promises, Pitfalls, and Clinical Applications of Artificial Intelligence in Pediatrics JO - J Med Internet Res SP - e49022 VL - 26 KW - artificial intelligence KW - pediatrics KW - autism spectrum disorder KW - ASD KW - disparities KW - pediatric KW - youth KW - child KW - children KW - autism KW - autistic KW - barrier KW - barriers KW - clinical application KW - clinical applications KW - professional development KW - continuing education KW - continuing medical education KW - CME KW - implementation UR - https://www.jmir.org/2024/1/e49022 UR - http://dx.doi.org/10.2196/49022 UR - http://www.ncbi.nlm.nih.gov/pubmed/38421690 ID - info:doi/10.2196/49022 ER - TY - JOUR AU - Stendal, Karen AU - Bernabe, C. Rosemarie D. L. PY - 2024/2/13 TI - Extended Reality?New Opportunity for People With Disability? Practical and Ethical Considerations JO - J Med Internet Res SP - e41670 VL - 26 KW - extended reality KW - virtual worlds KW - virtual reality KW - disability KW - practical KW - ethical KW - technology KW - virtual KW - reality KW - development KW - research KW - challenges UR - https://www.jmir.org/2024/1/e41670 UR - http://dx.doi.org/10.2196/41670 UR - http://www.ncbi.nlm.nih.gov/pubmed/38349731 ID - info:doi/10.2196/41670 ER - TY - JOUR AU - Sharma, Yashoda AU - Saha, Anindita AU - Goldsack, C. Jennifer PY - 2024/2/9 TI - Defining the Dimensions of Diversity to Promote Inclusion in the Digital Era of Health Care: A Lexicon JO - JMIR Public Health Surveill SP - e51980 VL - 10 KW - digital medicine KW - inclusion KW - digital health technology/product KW - digital health KW - digital technology KW - health care system KW - innovation KW - equity KW - quality KW - disparity KW - digital era KW - digital access KW - digital literacy UR - https://publichealth.jmir.org/2024/1/e51980 UR - http://dx.doi.org/10.2196/51980 UR - http://www.ncbi.nlm.nih.gov/pubmed/38335013 ID - info:doi/10.2196/51980 ER - TY - JOUR AU - Xu, Jian PY - 2024/2/5 TI - The Current Status and Promotional Strategies for Cloud Migration of Hospital Information Systems in China: Strengths, Weaknesses, Opportunities, and Threats Analysis JO - JMIR Med Inform SP - e52080 VL - 12 KW - hospital information system KW - HIS KW - cloud computing KW - cloud migration KW - Strengths, Weaknesses, Opportunities, and Threats analysis N2 - Background: In the 21st century, Chinese hospitals have witnessed innovative medical business models, such as online diagnosis and treatment, cross-regional multidepartment consultation, and real-time sharing of medical test results, that surpass traditional hospital information systems (HISs). The introduction of cloud computing provides an excellent opportunity for hospitals to address these challenges. However, there is currently no comprehensive research assessing the cloud migration of HISs in China. This lack may hinder the widespread adoption and secure implementation of cloud computing in hospitals. Objective: The objective of this study is to comprehensively assess external and internal factors influencing the cloud migration of HISs in China and propose promotional strategies. Methods: Academic articles from January 1, 2007, to February 21, 2023, on the topic were searched in PubMed and HuiyiMd databases, and relevant documents such as national policy documents, white papers, and survey reports were collected from authoritative sources for analysis. A systematic assessment of factors influencing cloud migration of HISs in China was conducted by combining a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis and literature review methods. Then, various promotional strategies based on different combinations of external and internal factors were proposed. Results: After conducting a thorough search and review, this study included 94 academic articles and 37 relevant documents. The analysis of these documents reveals the increasing application of and research on cloud computing in Chinese hospitals, and that it has expanded to 22 disciplinary domains. However, more than half (n=49, 52%) of the documents primarily focused on task-specific cloud-based systems in hospitals, while only 22% (n=21 articles) discussed integrated cloud platforms shared across the entire hospital, medical alliance, or region. The SWOT analysis showed that cloud computing adoption in Chinese hospitals benefits from policy support, capital investment, and social demand for new technology. However, it also faces threats like loss of digital sovereignty, supplier competition, cyber risks, and insufficient supervision. Factors driving cloud migration for HISs include medical big data analytics and use, interdisciplinary collaboration, health-centered medical service provision, and successful cases. Barriers include system complexity, security threats, lack of strategic planning and resource allocation, relevant personnel shortages, and inadequate investment. This study proposes 4 promotional strategies: encouraging more hospitals to migrate, enhancing hospitals? capabilities for migration, establishing a provincial-level unified medical hybrid multi-cloud platform, strengthening legal frameworks, and providing robust technical support. Conclusions: Cloud computing is an innovative technology that has gained significant attention from both the Chinese government and the global community. In order to effectively support the rapid growth of a novel, health-centered medical industry, it is imperative for Chinese health authorities and hospitals to seize this opportunity by implementing comprehensive strategies aimed at encouraging hospitals to migrate their HISs to the cloud. UR - https://medinform.jmir.org/2024/1/e52080 UR - http://dx.doi.org/10.2196/52080 UR - http://www.ncbi.nlm.nih.gov/pubmed/38315519 ID - info:doi/10.2196/52080 ER - TY - JOUR AU - Koonce, Y. Taneya AU - Giuse, A. Dario AU - Williams, M. Annette AU - Blasingame, N. Mallory AU - Krump, A. Poppy AU - Su, Jing AU - Giuse, B. Nunzia PY - 2024/1/30 TI - Using a Natural Language Processing Approach to Support Rapid Knowledge Acquisition JO - JMIR Med Inform SP - e53516 VL - 12 KW - natural language processing KW - electronic health records KW - machine learning KW - data mining KW - knowledge management KW - NLP UR - https://medinform.jmir.org/2024/1/e53516 UR - http://dx.doi.org/10.2196/53516 UR - http://www.ncbi.nlm.nih.gov/pubmed/38289670 ID - info:doi/10.2196/53516 ER - TY - JOUR AU - Morris, Seymour James PY - 2023/12/28 TI - A Call to Reconsider a Nationwide Electronic Health Record System: Correcting the Failures of the National Program for IT JO - JMIR Med Inform SP - e53112 VL - 11 KW - electronic health record KW - EHR KW - medical record linkage KW - health information interoperability KW - health information management KW - health information systems KW - information systems KW - interoperability KW - health records KW - medical records KW - national UR - https://medinform.jmir.org/2023/1/e53112 UR - http://dx.doi.org/10.2196/53112 ID - info:doi/10.2196/53112 ER - TY - JOUR AU - Schwab, D. Julian AU - Werle, D. Silke AU - Hühne, Rolf AU - Spohn, Hannah AU - Kaisers, X. Udo AU - Kestler, A. Hans PY - 2023/12/22 TI - The Necessity of Interoperability to Uncover the Full Potential of Digital Health Devices JO - JMIR Med Inform SP - e49301 VL - 11 KW - semantic terminology KW - semantic KW - terminology KW - terminologies KW - data linkage KW - interoperability KW - data exchange KW - SNOMED CT KW - LOINC KW - eHealth KW - patient-reported outcome questionnaires KW - requirement for standards KW - standard KW - standards KW - PRO KW - PROM KW - patient reported UR - https://medinform.jmir.org/2023/1/e49301 UR - http://dx.doi.org/10.2196/49301 UR - http://www.ncbi.nlm.nih.gov/pubmed/38133917 ID - info:doi/10.2196/49301 ER - TY - JOUR AU - Nourse, Rebecca AU - Dingler, Tilman AU - Kelly, Jaimon AU - Kwasnicka, Dominika AU - Maddison, Ralph PY - 2023/12/18 TI - The Role of a Smart Health Ecosystem in Transforming the Management of Chronic Health Conditions JO - J Med Internet Res SP - e44265 VL - 25 KW - smart home KW - health KW - chronic condition KW - chronic illness KW - digital health KW - technology KW - behavior change KW - wearable KW - smart technology KW - smart health KW - economic KW - cost KW - security KW - data storage KW - implementation UR - https://www.jmir.org/2023/1/e44265 UR - http://dx.doi.org/10.2196/44265 UR - http://www.ncbi.nlm.nih.gov/pubmed/38109188 ID - info:doi/10.2196/44265 ER - TY - JOUR AU - Zhu, Hongjian AU - Wong, Kee Weng PY - 2023/10/16 TI - An Overview of Adaptive Designs and Some of Their Challenges, Benefits, and Innovative Applications JO - J Med Internet Res SP - e44171 VL - 25 KW - doubly adaptive biased coin designs KW - model-based optimal designs KW - particle swarm optimization KW - repair mechanism UR - https://www.jmir.org/2023/1/e44171 UR - http://dx.doi.org/10.2196/44171 UR - http://www.ncbi.nlm.nih.gov/pubmed/37843888 ID - info:doi/10.2196/44171 ER - TY - JOUR AU - Herington, Jonathan AU - Connelly, Kay AU - Illes, Judy PY - 2023/9/18 TI - Ethical Imperatives for Working With Diverse Populations in Digital Research JO - J Med Internet Res SP - e47884 VL - 25 KW - digital health research KW - justice KW - research ethics KW - diversity KW - engagement KW - research participants KW - participatory UR - https://www.jmir.org/2023/1/e47884 UR - http://dx.doi.org/10.2196/47884 UR - http://www.ncbi.nlm.nih.gov/pubmed/37721792 ID - info:doi/10.2196/47884 ER - TY - JOUR AU - Fear, Kathleen AU - Gleber, Conrad PY - 2023/9/13 TI - Shaping the Future of Older Adult Care: ChatGPT, Advanced AI, and the Transformation of Clinical Practice JO - JMIR Aging SP - e51776 VL - 6 KW - generative AI KW - artificial intelligence KW - large language models KW - ChatGPT KW - Generative Pre-trained Transformer UR - https://aging.jmir.org/2023/1/e51776 UR - http://dx.doi.org/10.2196/51776 UR - http://www.ncbi.nlm.nih.gov/pubmed/37703085 ID - info:doi/10.2196/51776 ER - TY - JOUR AU - Tajabadi, Mohammad AU - Grabenhenrich, Linus AU - Ribeiro, Adèle AU - Leyer, Michael AU - Heider, Dominik PY - 2023/8/29 TI - Sharing Data With Shared Benefits: Artificial Intelligence Perspective JO - J Med Internet Res SP - e47540 VL - 25 KW - federated learning KW - machine learning KW - medical data KW - fairness KW - data sharing KW - artificial intelligence KW - development KW - artificial intelligence model KW - applications KW - data analysis KW - diagnostic tool KW - tool UR - https://www.jmir.org/2023/1/e47540 UR - http://dx.doi.org/10.2196/47540 UR - http://www.ncbi.nlm.nih.gov/pubmed/37642995 ID - info:doi/10.2196/47540 ER - TY - JOUR AU - Chenais, Gabrielle AU - Lagarde, Emmanuel AU - Gil-Jardiné, Cédric PY - 2023/5/23 TI - Artificial Intelligence in Emergency Medicine: Viewpoint of Current Applications and Foreseeable Opportunities and Challenges JO - J Med Internet Res SP - e40031 VL - 25 KW - viewpoint KW - ethics KW - artificial intelligence KW - emergency medicine KW - perspectives KW - mobile phone UR - https://www.jmir.org/2023/1/e40031 UR - http://dx.doi.org/10.2196/40031 UR - http://www.ncbi.nlm.nih.gov/pubmed/36972306 ID - info:doi/10.2196/40031 ER - TY - JOUR AU - Benis, Arriel AU - Haghi, Mostafa AU - Deserno, M. Thomas AU - Tamburis, Oscar PY - 2023/5/19 TI - One Digital Health Intervention for Monitoring Human and Animal Welfare in Smart Cities: Viewpoint and Use Case JO - JMIR Med Inform SP - e43871 VL - 11 KW - One Health KW - Digital Health KW - One Digital Health KW - accident and emergency informatics KW - eHealth KW - informatics KW - medicine KW - veterinary medicine KW - environmental monitoring KW - education KW - patient engagement KW - citizen science KW - data science KW - pets KW - human-animal bond KW - intervention KW - ambulatory monitoring KW - health monitoring KW - Internet of Things KW - smart environment KW - mobile phone UR - https://medinform.jmir.org/2023/1/e43871 UR - http://dx.doi.org/10.2196/43871 UR - http://www.ncbi.nlm.nih.gov/pubmed/36305540 ID - info:doi/10.2196/43871 ER - TY - JOUR AU - Harahap, Clydea Nabila AU - Handayani, Wuri Putu AU - Hidayanto, Nizar Achmad PY - 2023/3/14 TI - Integrated Personal Health Record in Indonesia: Design Science Research Study JO - JMIR Med Inform SP - e44784 VL - 11 KW - personal health record KW - integrated KW - Indonesia KW - design science KW - mobile phone N2 - Background: Personal health records (PHRs) are consumer-centric tools designed to facilitate the tracking, management, and sharing of personal health information. PHR research has mainly been conducted in high-income countries rather than in low- and middle-income countries. Moreover, previous studies that proposed PHR design in low- and middle-income countries did not describe integration with other systems, or there was no stakeholder involvement in exploring PHR requirements. Objective: This study developed an integrated PHR architecture and prototype in Indonesia using design science research. We conducted the research in Indonesia, a low- to middle-income country with the largest population in Southeast Asia and a tiered health system. Methods: This study followed the design science research guidelines. The requirements were identified through interviews with 37 respondents from health organizations and a questionnaire with 1012 patients. Afterward, the proposed architecture and prototype were evaluated via interviews with 6 IT or eHealth experts. Results: The architecture design refers to The Open Group Architecture Framework version 9.2 and comprises 5 components: architecture vision, business architecture, application architecture, data architecture, and technology architecture. We developed a high-fidelity prototype for patients and physicians. In the evaluation, improvements were made to add the stakeholders and the required functionality to the PHR and add the necessary information to the functions that were developed in the prototype. Conclusions: We used design science to illustrate PHR integration in Indonesia, which involves related stakeholders in requirement gathering and evaluation. We developed architecture and application prototypes based on health systems in Indonesia, which comprise routine health services, including disease treatment and health examinations, as well as promotive and preventive health efforts. UR - https://medinform.jmir.org/2023/1/e44784 UR - http://dx.doi.org/10.2196/44784 UR - http://www.ncbi.nlm.nih.gov/pubmed/36917168 ID - info:doi/10.2196/44784 ER - TY - JOUR AU - Li, Dongliang AU - Zhang, Rujia AU - Chen, Chun AU - Huang, Yunyun AU - Wang, Xiaoyi AU - Yang, Qingren AU - Zhu, Xuebo AU - Zhang, Xiangyang AU - Hao, Mo AU - Shui, Liming PY - 2023/1/9 TI - Developing a Capsule Clinic?A 24-Hour Institution for Improving Primary Health Care Accessibility: Evidence From China JO - JMIR Med Inform SP - e41212 VL - 11 KW - primary health care KW - accessibility KW - capsule clinic KW - 24-hour clinic KW - big-data KW - China KW - United Nations KW - internet clinic UR - https://medinform.jmir.org/2023/1/e41212 UR - http://dx.doi.org/10.2196/41212 UR - http://www.ncbi.nlm.nih.gov/pubmed/36622737 ID - info:doi/10.2196/41212 ER - TY - JOUR AU - Alexander, Natasha AU - Aftandilian, Catherine AU - Guo, Lawrence Lin AU - Plenert, Erin AU - Posada, Jose AU - Fries, Jason AU - Fleming, Scott AU - Johnson, Alistair AU - Shah, Nigam AU - Sung, Lillian PY - 2022/11/17 TI - Perspective Toward Machine Learning Implementation in Pediatric Medicine: Mixed Methods Study JO - JMIR Med Inform SP - e40039 VL - 10 IS - 11 KW - machine learning KW - clinical utilization KW - preferences KW - qualitative interviews N2 - Background: Given the costs of machine learning implementation, a systematic approach to prioritizing which models to implement into clinical practice may be valuable. Objective: The primary objective was to determine the health care attributes respondents at 2 pediatric institutions rate as important when prioritizing machine learning model implementation. The secondary objective was to describe their perspectives on implementation using a qualitative approach. Methods: In this mixed methods study, we distributed a survey to health system leaders, physicians, and data scientists at 2 pediatric institutions. We asked respondents to rank the following 5 attributes in terms of implementation usefulness: the clinical problem was common, the clinical problem caused substantial morbidity and mortality, risk stratification led to different actions that could reasonably improve patient outcomes, reducing physician workload, and saving money. Important attributes were those ranked as first or second most important. Individual qualitative interviews were conducted with a subsample of respondents. Results: Among 613 eligible respondents, 275 (44.9%) responded. Qualitative interviews were conducted with 17 respondents. The most common important attributes were risk stratification leading to different actions (205/275, 74.5%) and clinical problem causing substantial morbidity or mortality (177/275, 64.4%). The attributes considered least important were reducing physician workload and saving money. Qualitative interviews consistently prioritized implementations that improved patient outcomes. Conclusions: Respondents prioritized machine learning model implementation where risk stratification would lead to different actions and clinical problems that caused substantial morbidity and mortality. Implementations that improved patient outcomes were prioritized. These results can help provide a framework for machine learning model implementation. UR - https://medinform.jmir.org/2022/11/e40039 UR - http://dx.doi.org/10.2196/40039 UR - http://www.ncbi.nlm.nih.gov/pubmed/36394938 ID - info:doi/10.2196/40039 ER - TY - JOUR AU - Qin, Jiaxin AU - Wu, Jian PY - 2022/11/8 TI - Realizing the Potential of Computer-Assisted Surgery by Embedding Digital Twin Technology JO - JMIR Med Inform SP - e35138 VL - 10 IS - 11 KW - computer-assisted surgery KW - digital twin KW - virtual space KW - surgical navigation KW - remote surgery UR - https://medinform.jmir.org/2022/11/e35138 UR - http://dx.doi.org/10.2196/35138 UR - http://www.ncbi.nlm.nih.gov/pubmed/36346669 ID - info:doi/10.2196/35138 ER - TY - JOUR AU - Maletzky, Alexander AU - Böck, Carl AU - Tschoellitsch, Thomas AU - Roland, Theresa AU - Ludwig, Helga AU - Thumfart, Stefan AU - Giretzlehner, Michael AU - Hochreiter, Sepp AU - Meier, Jens PY - 2022/10/21 TI - Lifting Hospital Electronic Health Record Data Treasures: Challenges and Opportunities JO - JMIR Med Inform SP - e38557 VL - 10 IS - 10 KW - electronic health record KW - medical data preparation KW - machine learning KW - retrospective data analysis UR - https://medinform.jmir.org/2022/10/e38557 UR - http://dx.doi.org/10.2196/38557 UR - http://www.ncbi.nlm.nih.gov/pubmed/36269654 ID - info:doi/10.2196/38557 ER - TY - JOUR AU - Wells, J. Brian AU - Downs, M. Stephen AU - Ostasiewski, Brian PY - 2022/9/23 TI - Using Electronic Health Records for the Learning Health System: Creation of a Diabetes Research Registry JO - JMIR Med Inform SP - e39746 VL - 10 IS - 9 KW - electronic health record KW - EHR KW - Learning Health System KW - registry KW - diabetes UR - https://medinform.jmir.org/2022/9/e39746 UR - http://dx.doi.org/10.2196/39746 UR - http://www.ncbi.nlm.nih.gov/pubmed/36149742 ID - info:doi/10.2196/39746 ER - TY - JOUR AU - Hu, Zoe AU - Hu, Ricky AU - Yau, Olivia AU - Teng, Minnie AU - Wang, Patrick AU - Hu, Grace AU - Singla, Rohit PY - 2022/8/15 TI - Tempering Expectations on the Medical Artificial Intelligence Revolution: The Medical Trainee Viewpoint JO - JMIR Med Inform SP - e34304 VL - 10 IS - 8 KW - medical education KW - artificial intelligence KW - health care trainees KW - AI KW - health care workers UR - https://medinform.jmir.org/2022/8/e34304 UR - http://dx.doi.org/10.2196/34304 UR - http://www.ncbi.nlm.nih.gov/pubmed/35969464 ID - info:doi/10.2196/34304 ER - TY - JOUR AU - Krzyzanowski, Brittany AU - Manson, M. Steven PY - 2022/8/3 TI - Twenty Years of the Health Insurance Portability and Accountability Act Safe Harbor Provision: Unsolved Challenges and Ways Forward JO - JMIR Med Inform SP - e37756 VL - 10 IS - 8 KW - Health Insurance Portability and Accountability Act KW - HIPAA KW - data privacy KW - health KW - maps KW - safe harbor KW - visualization KW - patient privacy UR - https://medinform.jmir.org/2022/8/e37756 UR - http://dx.doi.org/10.2196/37756 UR - http://www.ncbi.nlm.nih.gov/pubmed/35921140 ID - info:doi/10.2196/37756 ER - TY - JOUR AU - Pawelek, Jeff AU - Baca-Motes, Katie AU - Pandit, A. Jay AU - Berk, B. Benjamin AU - Ramos, Edward PY - 2022/7/8 TI - The Power of Patient Engagement With Electronic Health Records as Research Participants JO - JMIR Med Inform SP - e39145 VL - 10 IS - 7 KW - electronic health record KW - EHR KW - digital health technology KW - digital clinical trial KW - underrepresentation KW - underrepresented in biomedical research KW - biomedical research UR - https://medinform.jmir.org/2022/7/e39145 UR - http://dx.doi.org/10.2196/39145 UR - http://www.ncbi.nlm.nih.gov/pubmed/35802410 ID - info:doi/10.2196/39145 ER - TY - JOUR AU - Klimek, Peter AU - Baltic, Dejan AU - Brunner, Martin AU - Degelsegger-Marquez, Alexander AU - Garhöfer, Gerhard AU - Gouya-Lechner, Ghazaleh AU - Herzog, Arnold AU - Jilma, Bernd AU - Kähler, Stefan AU - Mikl, Veronika AU - Mraz, Bernhard AU - Ostermann, Herwig AU - Röhl, Claas AU - Scharinger, Robert AU - Stamm, Tanja AU - Strassnig, Michael AU - Wirthumer-Hoche, Christa AU - Pleiner-Duxneuner, Johannes PY - 2022/6/17 TI - Quality Criteria for Real-world Data in Pharmaceutical Research and Health Care Decision-making: Austrian Expert Consensus JO - JMIR Med Inform SP - e34204 VL - 10 IS - 6 KW - real-world data KW - real-world evidence KW - data quality KW - data quality criteria KW - RWD quality recommendations KW - pharmaceutical research KW - health care decision-making KW - quality criteria for RWD in health care KW - Gesellschaft für Pharmazeutische Medizin KW - GPMed UR - https://medinform.jmir.org/2022/6/e34204 UR - http://dx.doi.org/10.2196/34204 UR - http://www.ncbi.nlm.nih.gov/pubmed/35713954 ID - info:doi/10.2196/34204 ER - TY - JOUR AU - Zirikly, Ayah AU - Desmet, Bart AU - Newman-Griffis, Denis AU - Marfeo, E. Elizabeth AU - McDonough, Christine AU - Goldman, Howard AU - Chan, Leighton PY - 2022/3/18 TI - Information Extraction Framework for Disability Determination Using a Mental Functioning Use-Case JO - JMIR Med Inform SP - e32245 VL - 10 IS - 3 KW - natural language processing KW - text mining KW - bioinformatics KW - health informatics KW - machine learning KW - disability KW - mental health KW - functioning KW - NLP KW - electronic health record KW - framework KW - EHR KW - automation KW - eHealth KW - decision support KW - functional status KW - whole-person function UR - https://medinform.jmir.org/2022/3/e32245 UR - http://dx.doi.org/10.2196/32245 UR - http://www.ncbi.nlm.nih.gov/pubmed/35302510 ID - info:doi/10.2196/32245 ER - TY - JOUR AU - Liaw, R. Winston AU - Westfall, M. John AU - Williamson, S. Tyler AU - Jabbarpour, Yalda AU - Bazemore, Andrew PY - 2022/3/8 TI - Primary Care: The Actual Intelligence Required for Artificial Intelligence to Advance Health Care and Improve Health JO - JMIR Med Inform SP - e27691 VL - 10 IS - 3 KW - artificial intelligence KW - primary care UR - https://medinform.jmir.org/2022/3/e27691 UR - http://dx.doi.org/10.2196/27691 UR - http://www.ncbi.nlm.nih.gov/pubmed/35258464 ID - info:doi/10.2196/27691 ER - TY - JOUR AU - Luo, Gang PY - 2022/3/1 TI - A Roadmap for Boosting Model Generalizability for Predicting Hospital Encounters for Asthma JO - JMIR Med Inform SP - e33044 VL - 10 IS - 3 KW - clinical decision support KW - forecasting KW - machine learning KW - patient care management KW - medical informatics KW - asthma KW - health care KW - health care systems KW - health care costs KW - prediction models KW - risk prediction UR - https://medinform.jmir.org/2022/3/e33044 UR - http://dx.doi.org/10.2196/33044 UR - http://www.ncbi.nlm.nih.gov/pubmed/35230246 ID - info:doi/10.2196/33044 ER - TY - JOUR AU - Ashworth, Henry AU - Ebrahim, Senan AU - Ebrahim, Hassaan AU - Bhaiwala, Zahra AU - Chilazi, Michael PY - 2022/2/11 TI - A Free, Open-Source, Offline Digital Health System for Refugee Care JO - JMIR Med Inform SP - e33848 VL - 10 IS - 2 KW - electronic health record KW - mHealth KW - refugee KW - displaced population KW - digital health KW - COVID-19 KW - health care N2 - Background: Rise of conflict, extreme weather events, and pandemics have led to larger displaced populations worldwide. Displaced populations have unique acute and chronic health needs that must be met by low-resource health systems. Electronic health records (EHRs) have been shown to improve health outcomes in displaced populations, but need to be adapted to meet the constraints of these health systems. Objective: The aim of this viewpoint is to describe the development and deployment of an EHR designed to care for displaced populations in low-resource settings. Methods: Using a human-centered design approach, we conducted in-depth interviews and focus groups with patients, health care providers, and administrators in Lebanon and Jordan to identify the essential EHR features. These features, including modular workflows, multilingual interfaces, and offline-first capabilities, led to the development of the Hikma Health EHR, which has been deployed in Lebanon and Nicaragua. Results: We report the successes and challenges from 12 months of Hikma Health EHR deployment in a mobile clinic providing care to Syrian refugees in Bekaa Valley, Lebanon. Successes include the EHR?s ability to (1) increase clinical efficacy by providing detailed patient records, (2) be adaptable to the threats of COVID-19, and (3) improve organizational planning. Lessons learned include technical fixes to methods of identifying patients through name or their medical record ID. Conclusions: As the number of displaced people continues to rise globally, it is imperative that solutions are created to help maximize the health care they receive. Free, open-sourced, and adaptable EHRs can enable organizations to better provide for displaced populations. UR - https://medinform.jmir.org/2022/2/e33848 UR - http://dx.doi.org/10.2196/33848 UR - http://www.ncbi.nlm.nih.gov/pubmed/35147509 ID - info:doi/10.2196/33848 ER - TY - JOUR AU - Sezgin, Emre AU - Sirrianni, Joseph AU - Linwood, L. Simon PY - 2022/2/10 TI - Operationalizing and Implementing Pretrained, Large Artificial Intelligence Linguistic Models in the US Health Care System: Outlook of Generative Pretrained Transformer 3 (GPT-3) as a Service Model JO - JMIR Med Inform SP - e32875 VL - 10 IS - 2 KW - natural language processing KW - artificial intelligence KW - generative pretrained transformer KW - clinical informatics KW - chatbot UR - https://medinform.jmir.org/2022/2/e32875 UR - http://dx.doi.org/10.2196/32875 UR - http://www.ncbi.nlm.nih.gov/pubmed/35142635 ID - info:doi/10.2196/32875 ER - TY - JOUR AU - Carolan, Elizabeth Jane AU - McGonigle, John AU - Dennis, Andrea AU - Lorgelly, Paula AU - Banerjee, Amitava PY - 2022/1/27 TI - Technology-Enabled, Evidence-Driven, and Patient-Centered: The Way Forward for Regulating Software as a Medical Device JO - JMIR Med Inform SP - e34038 VL - 10 IS - 1 KW - Artificial intelligence KW - machine learning KW - algorithm KW - software KW - risk assessment KW - informatics UR - https://medinform.jmir.org/2022/1/e34038 UR - http://dx.doi.org/10.2196/34038 UR - http://www.ncbi.nlm.nih.gov/pubmed/35084352 ID - info:doi/10.2196/34038 ER - TY - JOUR AU - Zhang, Xinyue AU - Saltman, Richard PY - 2022/1/11 TI - Impact of Electronic Health Record Interoperability on Telehealth Service Outcomes JO - JMIR Med Inform SP - e31837 VL - 10 IS - 1 KW - Electronic Health Records KW - Telehealth KW - Telemental health KW - Pandemic KW - Health outcomes KW - Health Policy UR - https://medinform.jmir.org/2022/1/e31837 UR - http://dx.doi.org/10.2196/31837 UR - http://www.ncbi.nlm.nih.gov/pubmed/34890347 ID - info:doi/10.2196/31837 ER - TY - JOUR AU - Madalinski, Mariusz AU - Prudham, Roger PY - 2021/12/24 TI - Can Real-time Computer-Aided Detection Systems Diminish the Risk of Postcolonoscopy Colorectal Cancer? JO - JMIR Med Inform SP - e25328 VL - 9 IS - 12 KW - artificial intelligence KW - colonoscopy KW - adenoma KW - real-time computer-aided detection KW - colonic polyp UR - https://medinform.jmir.org/2021/12/e25328 UR - http://dx.doi.org/10.2196/25328 UR - http://www.ncbi.nlm.nih.gov/pubmed/34571490 ID - info:doi/10.2196/25328 ER - TY - JOUR AU - Burmann, Anja AU - Tischler, Max AU - Faßbach, Mira AU - Schneitler, Sophie AU - Meister, Sven PY - 2021/11/11 TI - The Role of Physicians in Digitalizing Health Care Provision: Web-Based Survey Study JO - JMIR Med Inform SP - e31527 VL - 9 IS - 11 KW - digitalization KW - digital transformation KW - health care KW - human factor KW - physicians KW - digital natives KW - web-based survey KW - digital health N2 - Background: Digitalization affects all areas of society, including the health care sector. However, the digitalization of health care provision is progressing slowly compared to other sectors. In the professional and political literature, physicians are partially portrayed as digitalization sceptics. Thus, the role of physicians in this process requires further investigation. The theory of ?digital natives? suggests a lower hurdle for younger generations to engage with digital technologies. Objective: The objective of this study was to investigate the role of physicians in the process of digitalizing health care provision in Germany and to assess the age factor. Methods: We conducted a large-scale study to assess the role of this professional group in the progress of the digital transformation of the German health care sector. Therefore, in an anonymous online survey, we inquired about the current digital penetration of the personal working environment, expectations, attitude toward, and concerns regarding digitalization. Based on these data, we studied associations with the nominal variable age and variations across 2 age groups. Results: The 1274 participants included in the study generally showed a high affinity towards digitalization with a mean of 3.88 on a 5-point Likert scale; 723 respondents (56.75%) stated they personally use mobile apps in their everyday working life, with a weak tendency to be associated with the respondents? age (?=0.26). Participants saw the most noticeable existing benefits through digitalization in data quality and readability (882/1274, 69.23%) and the least in patient engagement (213/1274, 16.72%). Medical practitioners preponderantly expect further improvements through increased digitalization across almost all queried areas but the most in access to medical knowledge (1136/1274, 89.17%), treatment of orphan diseases (1016/1274, 79.75%), and medical research (1023/1274, 80.30%). Conclusions: Respondents defined their role in the digitalization of health care provision as ambivalent: ?scrutinizing? on the one hand but ?active? and ?open? on the other. A gap between willingness to participate and digital sovereignty was indicated. Thus, education on digitalization as a means to support health care provision should not only be included in the course of study but also in the continuing process of further and advanced training. UR - https://medinform.jmir.org/2021/11/e31527 UR - http://dx.doi.org/10.2196/31527 UR - http://www.ncbi.nlm.nih.gov/pubmed/34545813 ID - info:doi/10.2196/31527 ER - TY - JOUR AU - Busse, Sophie Theresa AU - Kernebeck, Sven AU - Nef, Larissa AU - Rebacz, Patrick AU - Kickbusch, Ilona AU - Ehlers, Peter Jan PY - 2021/11/10 TI - Views on Using Social Robots in Professional Caregiving: Content Analysis of a Scenario Method Workshop JO - J Med Internet Res SP - e20046 VL - 23 IS - 11 KW - social robots KW - robotics KW - health care sector KW - health personnel KW - ethics KW - forecasting KW - trends KW - technology KW - digital transformation KW - professional caregiving N2 - Background: Interest in digital technologies in the health care sector is growing and can be a way to reduce the burden on professional caregivers while helping people to become more independent. Social robots are regarded as a special form of technology that can be usefully applied in professional caregiving with the potential to focus on interpersonal contact. While implementation is progressing slowly, a debate on the concepts and applications of social robots in future care is necessary. Objective: In addition to existing studies with a focus on societal attitudes toward social robots, there is a need to understand the views of professional caregivers and patients. This study used desired future scenarios to collate the perspectives of experts and analyze the significance for developing the place of social robots in care. Methods: In February 2020, an expert workshop was held with 88 participants (health professionals and educators; [PhD] students of medicine, health care, professional care, and technology; patient advocates; software developers; government representatives; and research fellows) from Austria, Germany, and Switzerland. Using the scenario methodology, the possibilities of analog professional care (Analog Care), fully robotic professional care (Robotic Care), teams of robots and professional caregivers (Deep Care), and professional caregivers supported by robots (Smart Care) were discussed. The scenarios were used as a stimulus for the development of ideas about future professional caregiving. The discussion was evaluated using qualitative content analysis. Results: The majority of the experts were in favor of care in which people are supported by technology (Deep Care) and developed similar scenarios with a focus on dignity-centeredness. The discussions then focused on the steps necessary for its implementation, highlighting a strong need for the development of eHealth competence in society, a change in the training of professional caregivers, and cross-sectoral concepts. The experts also saw user acceptance as crucial to the use of robotics. This involves the acceptance of both professional caregivers and care recipients. Conclusions: The literature review and subsequent workshop revealed how decision-making about the value of social robots depends on personal characteristics related to experience and values. There is therefore a strong need to recognize individual perspectives of care before social robots become an integrated part of care in the future. UR - https://www.jmir.org/2021/11/e20046 UR - http://dx.doi.org/10.2196/20046 UR - http://www.ncbi.nlm.nih.gov/pubmed/34757318 ID - info:doi/10.2196/20046 ER - TY - JOUR AU - Drazich, F. Brittany AU - Nyikadzino, Yeukai AU - Gleason, T. Kelly PY - 2021/11/10 TI - A Program to Improve Digital Access and Literacy Among Community Stakeholders: Cohort Study JO - JMIR Form Res SP - e30605 VL - 5 IS - 11 KW - technology KW - disparities KW - digital access KW - digital literacy KW - community KW - stakeholders KW - digital health KW - digital divide KW - patient-centered outcomes N2 - Background: For many research teams, the role of community stakeholders is critical. However, community stakeholders, especially those in low-income settings, are at risk of being excluded from research and community engagement initiatives during and after the COVID-19 pandemic because of the rapid transition to digital operations. Objective: We aimed to describe the implementation and feasibility of a program called Addressing the Digital Divide to Improve Patient-Centered Outcomes Research, which was designed to address barriers to technology use, and to examine changes in participants? perceived comfort with digital technology before and after the program. Methods: To promote full engagement, we worked with 20 existing community leaders to cocreate a training course on using digital technology. We assessed the frequency of technology use and comfort with technology through an adapted 8-item version of the Functional Assessment of Comfort Employing Technology Scale and used the Wilcoxon signed-rank test for survey analysis. We also conducted a focus group session with 10 participants and then performed reflective journaling and content analysis to determine emergent themes. Results: We found that the program was feasible to implement and worthwhile for participants (15/16, 94%). After the program, the participants perceived an increase in the frequency of technology use (z=2.76, P=.006). The participants reported that the program was successful because of the technology training program, but recommended that the program have a slower pace and include a helpline number that they could call with questions. Conclusions: Future programs should consider that populations with low literacy view technology training as a core element to decreasing technology disparity. This study demonstrates that through low-cost input, community members can be provided the resources and training needed to virtually participate in research studies or community engagement initiatives. UR - https://formative.jmir.org/2021/11/e30605 UR - http://dx.doi.org/10.2196/30605 UR - http://www.ncbi.nlm.nih.gov/pubmed/34757316 ID - info:doi/10.2196/30605 ER - TY - JOUR AU - Lin, Yuchen AU - Lemos, Martin AU - Neuschaefer-Rube, Christiane PY - 2021/11/5 TI - Digital Health and Digital Learning Experiences Across Speech-Language Pathology, Phoniatrics, and Otolaryngology: Interdisciplinary Survey Study JO - JMIR Med Educ SP - e30873 VL - 7 IS - 4 KW - digital learning KW - e-learning KW - speech-language pathology KW - phoniatrics KW - otolaryngology KW - communication disorders KW - mobile phone N2 - Background: Advances in digital health and digital learning are transforming the lives of patients, health care providers, and health professional students. In the interdisciplinary field of communication sciences and disorders (CSD), digital uptake and incorporation of digital topics and technologies into clinical training programs has lagged behind other medical fields. There is a need to understand professional and student experiences, opinions, and needs regarding digital health and learning topics so that effective strategies for implementation can be optimized. Objective: This cross-sectional survey study aims to interdisciplinarily investigate professional and student knowledge, use, attitudes, and preferences toward digital health and learning in the German-speaking population. Methods: An open-ended, web-based survey was developed and conducted with professionals and students in CSD including phoniatricians and otolaryngologists, speech-language pathologists (German: Logopäd*innen), medical students, and speech-language pathology students. Differences in knowledge, use, attitudes, and preferences across profession, generation, and years of experience were analyzed. Results: A total of 170 participants completed the survey. Respondents demonstrated greater familiarity with digital learning as opposed to eHealth concepts. Significant differences were noted across profession (P<.001), generation (P=.001), and years of experience (P<.001), which demonstrated that students and younger participants were less familiar with digital health terminology. Professional (P<.001) and generational differences were also found (P=.04) in knowledge of digital therapy tools, though no significant differences were found for digital learning tools. Participants primarily used computers, tablets, and mobile phones; non?eHealth-specific tools (eg, word processing and videoconferencing applications); and digital formats such as videos, web courses, and apps. Many indicated a desire for more interactive platforms, such as virtual reality. Significant differences were found across generations for positive views toward digitalization (P<.001) and across profession for feelings of preparedness (P=.04). Interestingly, across profession (P=.03), generation (P=.006), and years of experience (P=.01), students and younger participants demonstrated greater support for medical certification. Commonly reported areas of concern included technical difficulties, quality and validity of digital materials, data privacy, and social presence. Respondents tended to prefer blended learning, a limited to moderate level of interactivity, and time and space?flexible learning environments (63/170, 37.1%), with a notable proportion still preferring traditional time and space?dependent learning (49/170, 28.8%). Conclusions: This comprehensive investigation into the current state of CSD student and professional opinions and experiences has shown that incorporation of digital topics and skills into academic and professional development curricula will be crucial for ensuring that the field is prepared for the ever-digitalizing health care environment. Deeper empirical investigation into efficacy and acceptance of digital learning and practice strategies and systematic training and practical organizational supports must be planned to ensure adaptive education and practice. UR - https://mededu.jmir.org/2021/4/e30873 UR - http://dx.doi.org/10.2196/30873 UR - http://www.ncbi.nlm.nih.gov/pubmed/34738911 ID - info:doi/10.2196/30873 ER - TY - JOUR AU - Nelligan, K. Rachel AU - Hinman, S. Rana AU - McManus, Fiona AU - Lamb, E. Karen AU - Bennell, L. Kim PY - 2021/10/29 TI - Moderators of the Effect of a Self-directed Digitally Delivered Exercise Program for People With Knee Osteoarthritis: Exploratory Analysis of a Randomized Controlled Trial JO - J Med Internet Res SP - e30768 VL - 23 IS - 10 KW - digital KW - text messaging KW - exercise KW - moderators KW - osteoarthritis KW - RCT KW - clinical trial KW - subgroups KW - pain KW - function KW - knee osteoarthritis KW - rehabilitation KW - digital health N2 - Background: A 24-week self-directed digitally delivered intervention was found to improve pain and function in people with knee osteoarthritis (OA). However, it is possible that this intervention may be better suited to certain subgroups of people with knee OA compared to others. Objective: The aim of this study was to explore whether certain individual baseline characteristics moderate the effects of a self-directed digitally delivered intervention on changes in pain and function over 24 weeks in people with knee OA. Methods: An exploratory analysis was conducted on data from a randomized controlled trial involving 206 people with a clinical diagnosis of knee OA. This trial compared a self-directed digitally delivered intervention comprising of web-based education, exercise, and physical activity program supported by automated exercise behavior change mobile phone text messages to web-based education alone (control). The primary outcomes were changes in overall knee pain (assessed on an 11-point numerical rating scale) and physical function (assessed using the Western Ontario and McMaster Universities Osteoarthritis Index function subscale [WOMAC]) at 24 weeks. Five baseline patient characteristics were selected as the potential moderators: (1) number of comorbidities, (2) number of other painful joints, (3) pain self-efficacy, (4) exercise self-efficacy, and (5) self-perceived importance of exercise. Separate linear regression models for each primary outcome and each potential moderator were fit, including treatment group, moderator, and interaction between treatment group and moderator, adjusting for the outcome at baseline. Results: There was evidence that pain self-efficacy moderated the effect of the intervention on physical function compared to the control at 24 weeks (interaction P=.02). Posthoc assessment of the mean change in WOMAC function by treatment arm showed that each 1-unit increase in baseline pain self-efficacy was associated with a 1.52 (95% CI 0.27 to 2.78) unit improvement in the control group. In contrast, a reduction of 0.62 (95% CI ?1.93 to 0.68) units was observed in the intervention group with each unit increase in pain self-efficacy. There was only weak evidence that pain self-efficacy moderated the effect of the intervention on pain and that number of comorbidities, number of other painful joints, exercise self-efficacy, or exercise importance moderated the effect of the intervention on pain or function. Conclusions: With the exception of pain self-efficacy, which moderated changes in function but not pain, we found limited evidence that our selected baseline patient characteristics moderated intervention outcomes. This indicates that people with a range of baseline characteristics respond similarly to the unsupervised digitally delivered exercise intervention. As these findings are exploratory in nature, they require confirmation in future studies. UR - https://www.jmir.org/2021/10/e30768 UR - http://dx.doi.org/10.2196/30768 UR - http://www.ncbi.nlm.nih.gov/pubmed/34714252 ID - info:doi/10.2196/30768 ER - TY - JOUR AU - Sarker, Abeed AU - Al-Garadi, Ali Mohammed AU - Yang, Yuan-Chi AU - Choi, Jinho AU - Quyyumi, A. Arshed AU - Martin, S. Greg PY - 2021/9/28 TI - Defining Patient-Oriented Natural Language Processing: A New Paradigm for Research and Development to Facilitate Adoption and Use by Medical Experts JO - JMIR Med Inform SP - e18471 VL - 9 IS - 9 KW - natural language processing KW - text mining KW - patient-centered care KW - evidence-based medicine KW - medical informatics UR - https://medinform.jmir.org/2021/9/e18471 UR - http://dx.doi.org/10.2196/18471 UR - http://www.ncbi.nlm.nih.gov/pubmed/34581670 ID - info:doi/10.2196/18471 ER - TY - JOUR AU - Mohan, Vishnu AU - Garrison, Cort AU - Gold, A. Jeffrey PY - 2021/9/20 TI - Using a New Model of Electronic Health Record Training to Reduce Physician Burnout: A Plan for Action JO - JMIR Med Inform SP - e29374 VL - 9 IS - 9 KW - electronic health records KW - clinician burnout KW - EHR training KW - clinician wellness KW - after-hours EHR use KW - EHR KW - patient data KW - burnout KW - simulation KW - efficiency KW - optimization KW - well-being UR - https://medinform.jmir.org/2021/9/e29374 UR - http://dx.doi.org/10.2196/29374 UR - http://www.ncbi.nlm.nih.gov/pubmed/34325400 ID - info:doi/10.2196/29374 ER - TY - JOUR AU - Kulkarni, Viraj AU - Gawali, Manish AU - Kharat, Amit PY - 2021/9/9 TI - Key Technology Considerations in Developing and Deploying Machine Learning Models in Clinical Radiology Practice JO - JMIR Med Inform SP - e28776 VL - 9 IS - 9 KW - artificial intelligence KW - AI KW - machine learning KW - deep learning KW - radiology KW - privacy KW - neural networks KW - deployment UR - https://medinform.jmir.org/2021/9/e28776 UR - http://dx.doi.org/10.2196/28776 UR - http://www.ncbi.nlm.nih.gov/pubmed/34499049 ID - info:doi/10.2196/28776 ER - TY - JOUR AU - McKillop, Mollie AU - Snowdon, Jane AU - Willis, C. Van AU - Alevy, Shira AU - Rizvi, Rubina AU - Rewalt, Karen AU - Lefebvre-Paillé, Charlyne AU - Kassler, William AU - Purcell Jackson, Gretchen PY - 2021/8/30 TI - A System to Support Diverse Social Program Management JO - JMIR Med Inform SP - e23219 VL - 9 IS - 8 KW - other clinical informatics applications KW - process management tools KW - requirements analysis and design KW - consumer health informatics KW - public health N2 - Background: Social programs are services provided by governments, nonprofits, and other organizations to help improve the health and well-being of individuals, families, and communities. Social programs aim to deliver services effectively and efficiently, but they are challenged by information silos, limited resources, and the need to deliver frequently changing mandated benefits. Objective: We aim to explore how an information system designed for social programs helps deliver services effectively and efficiently across diverse programs. Methods: This viewpoint describes the configurable and modular architecture of Social Program Management (SPM), a system to support efficient and effective delivery of services through a wide range of social programs and lessons learned from implementing SPM across diverse settings. We explored usage data to inform the engagement and impact of SPM on the efficient and effective delivery of services. Results: The features and functionalities of SPM seem to support the goals of social programs. We found that SPM provides fundamental management processes and configurable program-specific components to support social program administration; has been used by more than 280,000 caseworkers serving more than 30 million people in 13 countries; contains features designed to meet specific user requirements; supports secure information sharing and collaboration through data standardization and aggregation; and offers configurability and flexibility, which are important for digital transformation and organizational change. Conclusions: SPM is a user-centered, configurable, and flexible system for managing social program workflows. UR - https://medinform.jmir.org/2021/8/e23219 UR - http://dx.doi.org/10.2196/23219 UR - http://www.ncbi.nlm.nih.gov/pubmed/34459741 ID - info:doi/10.2196/23219 ER - TY - JOUR AU - Gonzales, Aldren AU - Smith, R. Scott AU - Dullabh, Prashila AU - Hovey, Lauren AU - Heaney-Huls, Krysta AU - Robichaud, Meagan AU - Boodoo, Roger PY - 2021/8/27 TI - Potential Uses of Blockchain Technology for Outcomes Research on Opioids JO - JMIR Med Inform SP - e16293 VL - 9 IS - 8 KW - blockchain KW - distributed ledger KW - opioid crisis KW - outcomes research KW - patient-centered outcomes research KW - mobile phone UR - https://medinform.jmir.org/2021/8/e16293 UR - http://dx.doi.org/10.2196/16293 UR - http://www.ncbi.nlm.nih.gov/pubmed/34448721 ID - info:doi/10.2196/16293 ER - TY - JOUR AU - Hogan, Katie AU - Macedo, Briana AU - Macha, Venkata AU - Barman, Arko AU - Jiang, Xiaoqian PY - 2021/7/19 TI - Contact Tracing Apps: Lessons Learned on Privacy, Autonomy, and the Need for Detailed and Thoughtful Implementation JO - JMIR Med Inform SP - e27449 VL - 9 IS - 7 KW - contact tracing KW - COVID-19 KW - privacy KW - smartphone apps KW - mobile phone apps KW - health information KW - electronic health KW - eHealth KW - pandemic KW - app KW - mobile health KW - mHealth UR - https://medinform.jmir.org/2021/7/e27449 UR - http://dx.doi.org/10.2196/27449 UR - http://www.ncbi.nlm.nih.gov/pubmed/34254937 ID - info:doi/10.2196/27449 ER - TY - JOUR AU - Makridis, Christos AU - Hurley, Seth AU - Klote, Mary AU - Alterovitz, Gil PY - 2021/6/2 TI - Ethical Applications of Artificial Intelligence: Evidence From Health Research on Veterans JO - JMIR Med Inform SP - e28921 VL - 9 IS - 6 KW - artificial intelligence KW - ethics KW - veterans KW - health data KW - technology KW - Veterans Affairs KW - health technology KW - data N2 - Background: Despite widespread agreement that artificial intelligence (AI) offers significant benefits for individuals and society at large, there are also serious challenges to overcome with respect to its governance. Recent policymaking has focused on establishing principles for the trustworthy use of AI. Adhering to these principles is especially important for ensuring that the development and application of AI raises economic and social welfare, including among vulnerable groups and veterans. Objective: We explore the newly developed principles around trustworthy AI and how they can be readily applied at scale to vulnerable groups that are potentially less likely to benefit from technological advances. Methods: Using the US Department of Veterans Affairs as a case study, we explore the principles of trustworthy AI that are of particular interest for vulnerable groups and veterans. Results: We focus on three principles: (1) designing, developing, acquiring, and using AI so that the benefits of its use significantly outweigh the risks and the risks are assessed and managed; (2) ensuring that the application of AI occurs in well-defined domains and is accurate, effective, and fit for the intended purposes; and (3) ensuring that the operations and outcomes of AI applications are sufficiently interpretable and understandable by all subject matter experts, users, and others. Conclusions: These principles and applications apply more generally to vulnerable groups, and adherence to them can allow the VA and other organizations to continue modernizing their technology governance, leveraging the gains of AI while simultaneously managing its risks. UR - https://medinform.jmir.org/2021/6/e28921 UR - http://dx.doi.org/10.2196/28921 UR - http://www.ncbi.nlm.nih.gov/pubmed/34076584 ID - info:doi/10.2196/28921 ER - TY - JOUR AU - Luo, Gang PY - 2021/5/27 TI - A Roadmap for Automating Lineage Tracing to Aid Automatically Explaining Machine Learning Predictions for Clinical Decision Support JO - JMIR Med Inform SP - e27778 VL - 9 IS - 5 KW - clinical decision support KW - database management systems KW - forecasting KW - machine learning KW - electronic medical records UR - https://medinform.jmir.org/2021/5/e27778 UR - http://dx.doi.org/10.2196/27778 UR - http://www.ncbi.nlm.nih.gov/pubmed/34042600 ID - info:doi/10.2196/27778 ER - TY - JOUR AU - Ologeanu-Taddei, Roxana PY - 2020/11/18 TI - Assessment of mHealth Interventions: Need for New Studies, Methods, and Guidelines for Study Designs JO - JMIR Med Inform SP - e21874 VL - 8 IS - 11 KW - eHealth KW - mHealth KW - usability KW - management KW - survey KW - trust KW - guidelines KW - evaluation UR - http://medinform.jmir.org/2020/11/e21874/ UR - http://dx.doi.org/10.2196/21874 UR - http://www.ncbi.nlm.nih.gov/pubmed/33206060 ID - info:doi/10.2196/21874 ER - TY - JOUR AU - Kao, David AU - Larson, Cynthia AU - Fletcher, Dana AU - Stegner, Kris PY - 2020/10/16 TI - Clinical Decision Support May Link Multiple Domains to Improve Patient Care: Viewpoint JO - JMIR Med Inform SP - e20265 VL - 8 IS - 10 KW - clinical decision support KW - population medicine KW - evidence-based medicine KW - precision medicine KW - care management KW - electronic health records UR - https://medinform.jmir.org/2020/10/e20265 UR - http://dx.doi.org/10.2196/20265 UR - http://www.ncbi.nlm.nih.gov/pubmed/33064106 ID - info:doi/10.2196/20265 ER - TY - JOUR AU - Held, Philip AU - Boley, A. Randy AU - Faig, G. Walter AU - O'Toole, A. John AU - Desai, Imran AU - Zalta, K. Alyson AU - Khan, Jawad AU - Sims, Shannon AU - Brennan, B. Michael AU - Van Horn, Rebecca AU - Glover, C. Angela AU - Hota, N. Bala AU - Patty, D. Brian AU - Rab, Shafiq S. AU - Pollack, H. Mark AU - Karnik, S. Niranjan PY - 2020/4/6 TI - The Postencounter Form System: Viewpoint on Efficient Data Collection Within Electronic Health Records JO - JMIR Form Res SP - e17429 VL - 4 IS - 4 KW - electronic health record KW - data collection KW - veterans UR - https://formative.jmir.org/2020/4/e17429 UR - http://dx.doi.org/10.2196/17429 UR - http://www.ncbi.nlm.nih.gov/pubmed/32250276 ID - info:doi/10.2196/17429 ER - TY - JOUR AU - Desveaux, Laura AU - Shaw, James AU - Wallace, Ross AU - Bhattacharyya, Onil AU - Bhatia, Sacha R. AU - Jamieson, Trevor PY - 2017/12/08 TI - Examining Tensions That Affect the Evaluation of Technology in Health Care: Considerations for System Decision Makers From the Perspective of Industry and Evaluators JO - JMIR Med Inform SP - e50 VL - 5 IS - 4 KW - technology KW - evaluation KW - policy KW - healthcare UR - http://medinform.jmir.org/2017/4/e50/ UR - http://dx.doi.org/10.2196/medinform.8207 UR - http://www.ncbi.nlm.nih.gov/pubmed/29222075 ID - info:doi/10.2196/medinform.8207 ER - TY - JOUR AU - Yen, Po-Yin AU - McAlearney, Scheck Ann AU - Sieck, J. Cynthia AU - Hefner, L. Jennifer AU - Huerta, R. Timothy PY - 2017/09/07 TI - Health Information Technology (HIT) Adaptation: Refocusing on the Journey to Successful HIT Implementation JO - JMIR Med Inform SP - e28 VL - 5 IS - 3 KW - health information technology KW - adaptation KW - adoption KW - acceptance UR - http://medinform.jmir.org/2017/3/e28/ UR - http://dx.doi.org/10.2196/medinform.7476 UR - http://www.ncbi.nlm.nih.gov/pubmed/28882812 ID - info:doi/10.2196/medinform.7476 ER - TY - JOUR AU - Deliberato, Octávio Rodrigo AU - Celi, Anthony Leo AU - Stone, J. David PY - 2017/08/03 TI - Clinical Note Creation, Binning, and Artificial Intelligence JO - JMIR Med Inform SP - e24 VL - 5 IS - 3 KW - electronic health records KW - artificial Intelligence KW - clinical informatics UR - http://medinform.jmir.org/2017/3/e24/ UR - http://dx.doi.org/10.2196/medinform.7627 UR - http://www.ncbi.nlm.nih.gov/pubmed/28778845 ID - info:doi/10.2196/medinform.7627 ER - TY - JOUR AU - Lea, Christopher Nathan AU - Nicholls, Jacqueline AU - Dobbs, Christine AU - Sethi, Nayha AU - Cunningham, James AU - Ainsworth, John AU - Heaven, Martin AU - Peacock, Trevor AU - Peacock, Anthony AU - Jones, Kerina AU - Laurie, Graeme AU - Kalra, Dipak PY - 2016/06/21 TI - Data Safe Havens and Trust: Toward a Common Understanding of Trusted Research Platforms for Governing Secure and Ethical Health Research JO - JMIR Med Inform SP - e22 VL - 4 IS - 2 KW - trusted research platforms KW - data safe havens KW - trusted researchers KW - legislative and regulatory compliance KW - public engagement KW - public involvement KW - clinical research support KW - health record linkage supported research KW - genomics research support UR - http://medinform.jmir.org/2016/2/e22/ UR - http://dx.doi.org/10.2196/medinform.5571 UR - http://www.ncbi.nlm.nih.gov/pubmed/27329087 ID - info:doi/10.2196/medinform.5571 ER - TY - JOUR AU - Talboom-Kamp, PWA Esther AU - Verdijk, A. Noortje AU - Harmans, M. Lara AU - Numans, E. Mattijs AU - Chavannes, H. Niels PY - 2016/02/09 TI - An eHealth Platform to Manage Chronic Disease in Primary Care: An Innovative Approach JO - Interact J Med Res SP - e5 VL - 5 IS - 1 KW - eHealth KW - self-management KW - anticoagulation clinic KW - chronic obstructive pulmonary disease KW - venous thromboembolism KW - integrated disease management KW - chronically ill KW - telemonitoring KW - primary care UR - http://www.i-jmr.org/2016/1/e5/ UR - http://dx.doi.org/10.2196/ijmr.4217 UR - http://www.ncbi.nlm.nih.gov/pubmed/26860333 ID - info:doi/10.2196/ijmr.4217 ER - TY - JOUR AU - Celi, Anthony Leo AU - Marshall, David Jeffrey AU - Lai, Yuan AU - Stone, J. David PY - 2015/10/23 TI - Disrupting Electronic Health Records Systems: The Next Generation JO - JMIR Med Inform SP - e34 VL - 3 IS - 4 KW - clinical decision making KW - clinical decision support KW - electronic health records KW - electronic notes UR - http://medinform.jmir.org/2015/4/e34/ UR - http://dx.doi.org/10.2196/medinform.4192 UR - http://www.ncbi.nlm.nih.gov/pubmed/26500106 ID - info:doi/10.2196/medinform.4192 ER - TY - JOUR AU - Waller, Amy AU - Forshaw, Kristy AU - Carey, Mariko AU - Robinson, Sancha AU - Kerridge, Ross AU - Proietto, Anthony AU - Sanson-Fisher, Rob PY - 2015/09/01 TI - Optimizing Patient Preparation and Surgical Experience Using eHealth Technology JO - JMIR Med Inform SP - e29 VL - 3 IS - 3 KW - eHealth KW - perioperative KW - postoperative KW - preoperative KW - surgery UR - http://medinform.jmir.org/2015/3/e29/ UR - http://dx.doi.org/10.2196/medinform.4286 UR - http://www.ncbi.nlm.nih.gov/pubmed/26330206 ID - info:doi/10.2196/medinform.4286 ER - TY - JOUR AU - Harvey, Harlan AU - Krishnaraj, Arun AU - Alkasab, K. Tarik PY - 2014/03/11 TI - Use of Expert Relevancy Ratings to Validate Task-Specific Search Strategies for Electronic Medical Records JO - JMIR Med Inform SP - e4 VL - 2 IS - 1 KW - medical informatics KW - medical records systems KW - computerized KW - health information management UR - http://medinform.jmir.org/2014/1/e4/ UR - http://dx.doi.org/10.2196/medinform.3205 UR - http://www.ncbi.nlm.nih.gov/pubmed/25601018 ID - info:doi/10.2196/medinform.3205 ER -