JMIR Publications

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  Ethics, Privacy, and Legal Issues

  Apr 24, 2024

  The Costs of Anonymization: Case Study Using Clinical Data

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  Authors List:

  • Lisa Pilgram  
  • Thierry Meurers  
  • Bradley Malin  
  • Elke Schaeffner  
  • Kai-Uwe Eckardt  
  • Fabian Prasser  
  • GCKD Investigators

  Abstract:

  Background: Sharing data from clinical studies can accelerate scientific progress, improve transparency, and increase the potential for innovation and collaboration. However, privacy concerns remain a barrier to data sharing. Certain concerns, such as reidentification risk, can be addressed through the application of anonymization algorithms, whereby data are altered so that it is no longer reasonably related to a person. Yet, such alterations have the potential to influence the data set’s statistical properties, such that the privacy-utility trade-off must be considered. This has been studied in theory, but evidence based on real-world individual-level clinical data is rare, and anonymization has not broadly been adopted in clinical practice. Objective: The goal of this study is to contribute to a better understanding of anonymization in the real world by comprehensively evaluating the privacy-utility trade-off of differently anonymized data using data and scientific results from the German Chronic Kidney Disease (GCKD) study. Methods: The GCKD data set extracted for this study consists of 5217 records and 70 variables. A 2-step procedure was followed to determine which variables constituted reidentification risks. To capture a large portion of the risk-utility space, we decided on risk thresholds ranging from 0.02 to 1. The data were then transformed via generalization and suppression, and the anonymization process was varied using a generic and a use case–specific configuration. To assess the utility of the anonymized GCKD data, general-purpose metrics (ie, data granularity and entropy), as well as use case–specific metrics (ie, reproducibility), were applied. Reproducibility was assessed by measuring the overlap of the 95% CI lengths between anonymized and original results. Results: Reproducibility measured by 95% CI overlap was higher than utility obtained from general-purpose metrics. For example, granularity varied between 68.2% and 87.6%, and entropy varied between 25.5% and 46.2%, whereas the average 95% CI overlap was above 90% for all risk thresholds applied. A nonoverlapping 95% CI was detected in 6 estimates across all analyses, but the overwhelming majority of estimates exhibited an overlap over 50%. The use case–specific configuration outperformed the generic one in terms of actual utility (ie, reproducibility) at the same level of privacy. Conclusions: Our results illustrate the challenges that anonymization faces when aiming to support multiple likely and possibly competing uses, while use case–specific anonymization can provide greater utility. This aspect should be taken into account when evaluating the associated costs of anonymized data and attempting to maintain sufficiently high levels of privacy for anonymized data. Trial Registration: German Clinical Trials Register DRKS00003971; https://drks.de/search/en/trial/DRKS00003971

  • J Med Internet Res 2024;26(1):e49445

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  Implantable Drug Delivery Systems,...

  Apr 24, 2024

  Factor Analysis of Patients Who Find Tablets or Capsules Difficult to Swallow Due to Their Large Size: Using the Personal Health Record Infrastructure of...

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  Authors List:

  • Masaki Asano  
  • Shungo Imai  
  • Yuri Shimizu  
  • Hayato Kizaki  
  • Yukiko Ito  
  • Makoto Tsuchiya  
  • Ryoko Kuriyama  
  • Nao Yoshida  
  • Masanori Shimada  
  • Takanori Sando  
  • Tomo Ishijima  
  • Satoko Hori  

  Abstract:

  Background: Understanding patient preference regarding taking tablet or capsule formulations plays a pivotal role in treatment efficacy and adherence. Therefore, these preferences should be taken into account when designing formulations and prescriptions. Objective: This study investigates the factors affecting patient preference in patients who have difficulties swallowing large tablets or capsules and aims to identify appropriate sizes for tablets and capsules. Methods: A robust data set was developed based on a questionnaire survey conducted from December 1, 2022, to December 7, 2022, using the harmo smartphone app operated by harmo Co, Ltd. The data set included patient input regarding their tablet and capsule preferences, personal health records (including dispensing history), and drug formulation information (available from package inserts). Based on the medication formulation information, 6 indices were set for each of the tablets or capsules that were considered difficult to swallow owing to their large size and concomitant tablets or capsules (used as controls). Receiver operating characteristic (ROC) analysis was used to evaluate the performance of each index. The index demonstrating the highest area under the curve of the ROC was selected as the best index to determine the tablet or capsule size that leads to swallowing difficulties. From the generated ROCs, the point with the highest discriminative performance that maximized the Youden index was identified, and the optimal threshold for each index was calculated. Multivariate logistic regression analysis was performed to identify the risk factors contributing to difficulty in swallowing oversized tablets or capsules. Additionally, decision tree analysis was performed to estimate the combined risk from several factors, using risk factors that were significant in the multivariate logistic regression analysis. Results: This study analyzed 147 large tablets or capsules and 624 control tablets or capsules. The “long diameter + short diameter + thickness” index (with a 21.5 mm threshold) was identified as the best indicator for causing swallowing difficulties in patients. The multivariate logistic regression analysis (including 132 patients with swallowing difficulties and 1283 patients without) results identified the following contributory risk factors: aged <50 years (odds ratio [OR] 1.59, 95% CI 1.03-2.44), female (OR 2.54, 95% CI 1.70-3.78), dysphagia (OR 3.54, 95% CI 2.22-5.65), and taking large tablets or capsules (OR 9.74, 95% CI 5.19-18.29). The decision tree analysis results suggested an elevated risk of swallowing difficulties for patients with taking large tablets or capsules. Conclusions: This study identified the most appropriate index and threshold for indicating that a given tablet or capsule size will cause swallowing difficulties, as well as the contributory risk factors. Although some sampling biases (eg, only including smartphone users) may exist, our results can guide the design of patient-friendly formulations and prescriptions, promoting better medication adherence.

  • J Med Internet Res 2024;26(1):e54645

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  Digital Health Reviews

  Apr 24, 2024

  Behavior Change Approaches in Digital Technology–Based Physical Rehabilitation Interventions Following Stroke: Scoping Review

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  Authors List:

  • Helen J Gooch  
  • Kathryn A Jarvis  
  • Rachel C Stockley  

  Abstract:

  Background: Digital health technologies (DHTs) are increasingly used in physical stroke rehabilitation to support individuals in successfully engaging with the frequent, intensive, and lengthy activities required to optimize recovery. Despite this, little is known about behavior change within these interventions. Objective: This scoping review aimed to identify if and how behavior change approaches (ie, theories, models, frameworks, and techniques to influence behavior) are incorporated within physical stroke rehabilitation interventions that include a DHT. Methods: Databases (Embase, MEDLINE, PsycINFO, CINAHL, Cochrane Library, and AMED) were searched using keywords relating to behavior change, DHT, physical rehabilitation, and stroke. The results were independently screened by 2 reviewers. Sources were included if they reported a completed primary research study in which a behavior change approach could be identified within a physical stroke rehabilitation intervention that included a DHT. Data, including the study design, DHT used, and behavior change approaches, were charted. Specific behavior change techniques were coded to the behavior change technique taxonomy version 1 (BCTTv1). Results: From a total of 1973 identified sources, 103 (5%) studies were included for data charting. The most common reason for exclusion at full-text screening was the absence of an explicit approach to behavior change (165/245, 67%). Almost half (45/103, 44%) of the included studies were described as pilot or feasibility studies. Virtual reality was the most frequently identified DHT type (58/103, 56%), and almost two-thirds (65/103, 63%) of studies focused on upper limb rehabilitation. Only a limited number of studies (18/103, 17%) included a theory, model, or framework for behavior change. The most frequently used BCTTv1 clusters were feedback and monitoring (88/103, 85%), reward and threat (56/103, 54%), goals and planning (33/103, 32%), and shaping knowledge (33/103, 32%). Relationships between feedback and monitoring and reward and threat were identified using a relationship map, with prominent use of both of these clusters in interventions that included virtual reality. Conclusions: Despite an assumption that DHTs can promote engagement in rehabilitation, this scoping review demonstrates that very few studies of physical stroke rehabilitation that include a DHT overtly used any form of behavior change approach. From those studies that did consider behavior change, most did not report a robust underpinning theory. Future development and research need to explicitly articulate how including DHTs within an intervention may support the behavior change required for optimal engagement in physical rehabilitation following stroke, as well as establish their effectiveness. This understanding is likely to support the realization of the transformative potential of DHTs in stroke rehabilitation.

  • J Med Internet Res 2024;26(1):e48725

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  e-Mental Health and Cyberpsychology

  Apr 24, 2024

  The Impact of Video-Based Microinterventions on Attitudes Toward Mental Health and Help Seeking in Youth: Web-Based Randomized Controlled Trial

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  Authors List:

  • Diana Lemmer  
  • Markus Moessner  
  • Nicolas Arnaud  
  • Harald Baumeister  
  • Agnes Mutter  
  • Sarah-Lena Klemm  
  • Elisa König  
  • Paul Plener  
  • Christine Rummel-Kluge  
  • Rainer Thomasius  
  • Michael Kaess  
  • Stephanie Bauer  

  Abstract:

  Background: Mental health (MH) problems in youth are prevalent, burdening, and frequently persistent. Despite the existence of effective treatment, the uptake of professional help is low, particularly due to attitudinal barriers. Objective: This study evaluated the effectiveness and acceptability of 2 video-based microinterventions aimed at reducing barriers to MH treatment and increasing the likelihood of seeking professional help in young people. Methods: This study was entirely web based and open access. The interventions addressed 5 MH problems: generalized anxiety disorder, depression, bulimia, nonsuicidal self-injury, and problematic alcohol use. Intervention 1 aimed to destigmatize and improve MH literacy, whereas intervention 2 aimed to induce positive outcome expectancies regarding professional help seeking. Of the 2435 participants who commenced the study, a final sample of 1394 (57.25%) participants aged 14 to 29 years with complete data and sufficient durations of stay on the video pages were randomized in a fully automated manner to 1 of the 5 MH problems and 1 of 3 conditions (control, intervention 1, and intervention 2) in a permuted block design. After the presentation of a video vignette, no further videos were shown to the control group, whereas a second, short intervention video was presented to the intervention 1 and 2 groups. Intervention effects on self-reported potential professional help seeking (primary outcome), stigma, and attitudes toward help seeking were examined using analyses of covariance across and within the 5 MH problems. Furthermore, we assessed video acceptability. Results: No significant group effects on potential professional help seeking were found in the total sample (F_2,1385=0.99; P=.37). However, the groups differed significantly with regard to stigma outcomes and the likelihood of seeking informal help (F_2,1385=3.75; P=.02). Furthermore, separate analyses indicated substantial differences in intervention effects among the 5 MH problems. Conclusions: Interventions to promote help seeking for MH problems may require disorder-specific approaches. The study results can inform future research and public health campaigns addressing adolescents and young adults. Trial Registration: German Clinical Trials Register DRKS00023110; https://drks.de/search/de/trial/DRKS00023110

  • J Med Internet Res 2024;26(1):e54478

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  Digital Health Reviews

  Apr 23, 2024

  Electronic Media Use and Sleep Quality: Updated Systematic Review and Meta-Analysis

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  Authors List:

  • Xiaoning Han  
  • Enze Zhou  
  • Dong Liu  

  Abstract:

  Background: This paper explores the widely discussed relationship between electronic media use and sleep quality, indicating negative effects due to various factors. However, existing meta-analyses on the topic have some limitations. Objective: The study aims to analyze and compare the impacts of different digital media types, such as smartphones, online games, and social media, on sleep quality. Methods: Adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the study performed a systematic meta-analysis of literature across multiple databases, including Web of Science, MEDLINE, PsycINFO, PubMed, Science Direct, Scopus, and Google Scholar, from January 2018 to October 2023. Two trained coders coded the study characteristics independently. The effect sizes were calculated using the correlation coefficient as a standardized measure of the relationship between electronic media use and sleep quality across studies. The Comprehensive Meta-Analysis software (version 3.0) was used to perform the meta-analysis. Statistical methods such as funnel plots were used to assess the presence of asymmetry and a p-curve test to test the p-hacking problem, which can indicate publication bias. Results: Following a thorough screening process, the study involved 55 papers (56 items) with 41,716 participants from over 20 countries, classifying electronic media use into “general use” and “problematic use.” The meta-analysis revealed that electronic media use was significantly linked with decreased sleep quality and increased sleep problems with varying effect sizes across subgroups. A significant cultural difference was also observed in these effects. General use was associated with a significant decrease in sleep quality (P<.001). The pooled effect size was 0.28 (95% CI 0.21-0.35; k=20). Problematic use was associated with a significant increase in sleep problems (P≤.001). The pooled effect size was 0.33 (95% CI 0.28-0.38; k=36). The subgroup analysis indicated that the effect of general smartphone use and sleep problems was r=0.33 (95% CI 0.27-0.40), which was the highest among the general group. The effect of problematic internet use and sleep problems was r=0.51 (95% CI 0.43-0.59), which was the highest among the problematic groups. There were significant differences among these subgroups (general: Q_between=14.46, P=.001; problematic: Q_between=27.37, P<.001). The results of the meta-regression analysis using age, gender, and culture as moderators indicated that only cultural difference in the relationship between Eastern and Western culture was significant (Q_between=6.69; P=.01). All funnel plots and p-curve analyses showed no evidence of publication and selection bias. Conclusions: Despite some variability, the study overall confirms the correlation between increased electronic media use and poorer sleep outcomes, which is notably more significant in Eastern cultures.

  • J Med Internet Res 2024;26(1):e48356

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  e-Mental Health and Cyberpsychology

  Apr 23, 2024

  Empowering School Staff to Support Pupil Mental Health Through a Brief, Interactive Web-Based Training Program: Mixed Methods Study

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  Authors List:

  • Emma Soneson  
  • Emma Howarth  
  • Alison Weir  
  • Peter B Jones  
  • Mina Fazel  

  Abstract:

  Background: Schools in the United Kingdom and elsewhere are expected to protect and promote pupil mental health. However, many school staff members do not feel confident in identifying and responding to pupil mental health difficulties and report wanting additional training in this area. Objective: We aimed to explore the feasibility of Kognito’s At-Risk for Elementary School Educators, a brief, interactive web-based training program that uses a simulation-based approach to improve school staff’s knowledge and skills in supporting pupil mental health. Methods: We conducted a mixed methods, nonrandomized feasibility study of At-Risk for Elementary School Educators in 6 UK primary schools. Our outcomes were (1) school staff’s self-efficacy and preparedness to identify and respond to pupil mental health difficulties, (2) school staff’s identification of mental health difficulties and increased risk of mental health difficulties, (3) mental health support for identified pupils (including conversations about concerns, documentation of concerns, in-class and in-school support, and referral and access to specialist mental health services), and (4) the acceptability and practicality of the training. We assessed these outcomes using a series of questionnaires completed at baseline (T1), 1 week after the training (T2), and 3 months after the training (T3), as well as semistructured qualitative interviews. Following guidance for feasibility studies, we assessed quantitative outcomes across time points by comparing medians and IQRs and analyzed qualitative data using reflexive thematic analysis. Results: A total of 108 teachers and teaching assistants (TAs) completed T1 questionnaires, 89 (82.4%) completed T2 questionnaires, and 70 (64.8%) completed T3 questionnaires; 54 (50%) completed all 3. Eight school staff members, including teachers, TAs, mental health leads, and senior leaders, participated in the interviews. School staff reported greater confidence and preparedness in identifying and responding to mental health difficulties after completing the training. The proportion of pupils whom they identified as having mental health difficulties or increased risk declined slightly over time (median_T1=10%; median_T2=10%; median_T3=7.4%), but findings suggested a slight increase in accuracy compared with a validated screening measure (the Strengths and Difficulties Questionnaire). In-school mental health support outcomes for identified pupils improved after the training, with increases in formal documentation and communication of concerns as well as provision of in-class and in-school support. Referrals and access to external mental health services remained constant. The qualitative findings indicated that school staff perceived the training as useful, practical, and acceptable. Conclusions: The findings suggest that brief, interactive web-based training programs such as At-Risk for Elementary School Educators are a feasible means to improve the identification of and response to mental health difficulties in UK primary schools. Such training may help address the high prevalence of mental health difficulties in this age group by helping facilitate access to care and support. Trial Registration:

  • J Med Internet Res 2024;26(1):e46764

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  Mobile Health (mhealth)

  Apr 23, 2024

  Problems and Barriers Related to the Use of mHealth Apps From the Perspective of Patients: Focus Group and Interview Study

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  Authors List:

  • Godwin Denk Giebel  
  • Carina Abels  
  • Felix Plescher  
  • Christian Speckemeier  
  • Nils Frederik Schrader  
  • Kirstin Börchers  
  • Jürgen Wasem  
  • Silke Neusser  
  • Nikola Blase  

  Abstract:

  Background: Since fall 2020, mobile health (mHealth) apps have become an integral part of the German health care system. The belief that mHealth apps have the potential to make the health care system more efficient, close gaps in care, and improve the economic outcomes related to health is unwavering and already partially confirmed. Nevertheless, problems and barriers in the context of mHealth apps usually remain unconsidered. Objective: The focus groups and interviews conducted in this study aim to shed light on problems and barriers in the context of mHealth apps from the perspective of patients. Methods: Guided focus groups and individual interviews were conducted with patients with a disease for which an approved mHealth app was available at the time of the interviews. Participants were recruited via self-help groups. The interviews were recorded, transcribed, and subjected to a qualitative content analysis. The content analysis was based on 10 problem categories (“validity,” “usability,” “technology,” “use and adherence,” “data privacy and security,” “patient-physician relationship,” “knowledge and skills,” “individuality,” “implementation,” and “costs”) identified in a previously conducted scoping review. Participants were asked to fill out an additional questionnaire about their sociodemographic data and about their use of technology. Results: A total of 38 patients were interviewed in 5 focus groups (3 onsite and 2 web-based) and 5 individual web-based interviews. The additional questionnaire was completed by 32 of the participants. Patients presented with a variety of different diseases, such as arthrosis, tinnitus, depression, or lung cancer. Overall, 16% (5/32) of the participants had already been prescribed an app. During the interviews, all 10 problem categories were discussed and considered important by patients. A myriad of problem manifestations could be identified for each category. This study shows that there are relevant problems and barriers in the context of mHealth apps from the perspective of patients, which warrant further attention. Conclusions: There are essentially 3 different areas of problems in the context of mHealth apps that could be addressed to improve care: quality of the respective mHealth app, its integration into health care, and the expandable digital literacy of patients.

  • J Med Internet Res 2024;26(1):e49982

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  Generative Language Models Including...

  Apr 22, 2024

  Using ChatGPT-4 to Create Structured Medical Notes From Audio Recordings of Physician-Patient Encounters: Comparative Study

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  Authors List:

  • Annessa Kernberg  
  • Jeffrey A Gold  
  • Vishnu Mohan  

  Abstract:

  Background: Medical documentation plays a crucial role in clinical practice, facilitating accurate patient management and communication among health care professionals. However, inaccuracies in medical notes can lead to miscommunication and diagnostic errors. Additionally, the demands of documentation contribute to physician burnout. Although intermediaries like medical scribes and speech recognition software have been used to ease this burden, they have limitations in terms of accuracy and addressing provider-specific metrics. The integration of ambient artificial intelligence (AI)–powered solutions offers a promising way to improve documentation while fitting seamlessly into existing workflows. Objective: This study aims to assess the accuracy and quality of Subjective, Objective, Assessment, and Plan (SOAP) notes generated by ChatGPT-4, an AI model, using established transcripts of History and Physical Examination as the gold standard. We seek to identify potential errors and evaluate the model’s performance across different categories. Methods: We conducted simulated patient-provider encounters representing various ambulatory specialties and transcribed the audio files. Key reportable elements were identified, and ChatGPT-4 was used to generate SOAP notes based on these transcripts. Three versions of each note were created and compared to the gold standard via chart review; errors generated from the comparison were categorized as omissions, incorrect information, or additions. We compared the accuracy of data elements across versions, transcript length, and data categories. Additionally, we assessed note quality using the Physician Documentation Quality Instrument (PDQI) scoring system. Results: Although ChatGPT-4 consistently generated SOAP-style notes, there were, on average, 23.6 errors per clinical case, with errors of omission (86%) being the most common, followed by addition errors (10.5%) and inclusion of incorrect facts (3.2%). There was significant variance between replicates of the same case, with only 52.9% of data elements reported correctly across all 3 replicates. The accuracy of data elements varied across cases, with the highest accuracy observed in the “Objective” section. Consequently, the measure of note quality, assessed by PDQI, demonstrated intra- and intercase variance. Finally, the accuracy of ChatGPT-4 was inversely correlated to both the transcript length (P=.05) and the number of scorable data elements (P=.05). Conclusions: Our study reveals substantial variability in errors, accuracy, and note quality generated by ChatGPT-4. Errors were not limited to specific sections, and the inconsistency in error types across replicates complicated predictability. Transcript length and data complexity were inversely correlated with note accuracy, raising concerns about the model’s effectiveness in handling complex medical cases. The quality and reliability of clinical notes produced by ChatGPT-4 do not meet the standards required for clinical use. Although AI holds promise in health care, caution should be exercised before widespread adoption. Further research is needed to address accuracy, variability, and potential errors. ChatGPT-4, while valuable in various applications, should not be considered a safe alternative to human-generated clinical documentation at this time.

  • J Med Internet Res 2024;26(1):e54419

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  Digital Health Reviews

  Apr 22, 2024

  Patient and Staff Experience of Remote Patient Monitoring—What to Measure and How: Systematic Review

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  Authors List:

  • Valeria Pannunzio  
  • Hosana Cristina Morales Ornelas  
  • Pema Gurung  
  • Robert van Kooten  
  • Dirk Snelders  
  • Hendrikus van Os  
  • Michel Wouters  
  • Rob Tollenaar  
  • Douwe Atsma  
  • Maaike Kleinsmann  

  Abstract:

  Background: Patient and staff experience is a vital factor to consider in the evaluation of remote patient monitoring (RPM) interventions. However, no comprehensive overview of available RPM patient and staff experience–measuring methods and tools exists. Objective: This review aimed at obtaining a comprehensive set of experience constructs and corresponding measuring instruments used in contemporary RPM research and at proposing an initial set of guidelines for improving methodological standardization in this domain. Methods: Full-text papers reporting on instances of patient or staff experience measuring in RPM interventions, written in English, and published after January 1, 2011, were considered for eligibility. By “RPM interventions,” we referred to interventions including sensor-based patient monitoring used for clinical decision-making; papers reporting on other kinds of interventions were therefore excluded. Papers describing primary care interventions, involving participants under 18 years of age, or focusing on attitudes or technologies rather than specific interventions were also excluded. We searched 2 electronic databases, Medline (PubMed) and EMBASE, on February 12, 2021.We explored and structured the obtained corpus of data through correspondence analysis, a multivariate statistical technique. Results: In total, 158 papers were included, covering RPM interventions in a variety of domains. From these studies, we reported 546 experience-measuring instances in RPM, covering the use of 160 unique experience-measuring instruments to measure 120 unique experience constructs. We found that the research landscape has seen a sizeable growth in the past decade, that it is affected by a relative lack of focus on the experience of staff, and that the overall corpus of collected experience measures can be organized in 4 main categories (service system related, care related, usage and adherence related, and health outcome related). In the light of the collected findings, we provided a set of 6 actionable recommendations to RPM patient and staff experience evaluators, in terms of both what to measure and how to measure it. Overall, we suggested that RPM researchers and practitioners include experience measuring as part of integrated, interdisciplinary data strategies for continuous RPM evaluation. Conclusions: At present, there is a lack of consensus and standardization in the methods used to measure patient and staff experience in RPM, leading to a critical knowledge gap in our understanding of the impact of RPM interventions. This review offers targeted support for RPM experience evaluators by providing a structured, comprehensive overview of contemporary patient and staff experience measures and a set of practical guidelines for improving research quality and standardization in this domain.

  • J Med Internet Res 2024;26(1):e48463

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  Generative Language Models Including...

  Apr 22, 2024

  ChatGPT’s Performance in Cardiac Arrest and Bradycardia Simulations Using the American Heart Association's Advanced Cardiovascular Life Support Guidelines:...

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  Authors List:

  • Cecilia Pham  
  • Romi Govender  
  • Salik Tehami  
  • Summer Chavez  
  • Omolola E Adepoju  
  • Winston Liaw  

  Abstract:

  Background: ChatGPT is the most advanced large language model to date, with prior iterations having passed medical licensing examinations, providing clinical decision support, and improved diagnostics. Although limited, past studies of ChatGPT’s performance found that artificial intelligence could pass the American Heart Association’s advanced cardiovascular life support (ACLS) examinations with modifications. ChatGPT’s accuracy has not been studied in more complex clinical scenarios. As heart disease and cardiac arrest remain leading causes of morbidity and mortality in the United States, finding technologies that help increase adherence to ACLS algorithms, which improves survival outcomes, is critical. Objective: This study aims to examine the accuracy of ChatGPT in following ACLS guidelines for bradycardia and cardiac arrest. Methods: We evaluated the accuracy of ChatGPT’s responses to 2 simulations based on the 2020 American Heart Association ACLS guidelines with 3 primary outcomes of interest: the mean individual step accuracy, the accuracy score per simulation attempt, and the accuracy score for each algorithm. For each simulation step, ChatGPT was scored for correctness (1 point) or incorrectness (0 points). Each simulation was conducted 20 times. Results: ChatGPT’s median accuracy for each step was 85% (IQR 40%-100%) for cardiac arrest and 30% (IQR 13%-81%) for bradycardia. ChatGPT’s median accuracy over 20 simulation attempts for cardiac arrest was 69% (IQR 67%-74%) and for bradycardia was 42% (IQR 33%-50%). We found that ChatGPT’s outputs varied despite consistent input, the same actions were persistently missed, repetitive overemphasis hindered guidance, and erroneous medication information was presented. Conclusions: This study highlights the need for consistent and reliable guidance to prevent potential medical errors and optimize the application of ChatGPT to enhance its reliability and effectiveness in clinical practice. Trial Registration:

  • J Med Internet Res 2024;26(1):e55037

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  Research Letter

  Apr 22, 2024

  Evaluation of Prompts to Simplify Cardiovascular Disease Information Generated Using a Large Language Model: Cross-Sectional Study

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  • Vishala Mishra  
  • Ashish Sarraju  
  • Neil M Kalwani  
  • Joseph P Dexter  

  Abstract:

  In this cross-sectional study, we evaluated the completeness, readability, and syntactic complexity of cardiovascular disease prevention information produced by GPT-4 in response to 4 kinds of prompts.

  • J Med Internet Res 2024;26(1):e55388

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  Digital Health Reviews

  Apr 19, 2024

  Investigating the Cost-Effectiveness of Telemonitoring Patients With Cardiac Implantable Electronic Devices: Systematic Review

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  Authors List:

  • Sarah Raes  
  • Andrea Prezzi  
  • Rik Willems  
  • Hein Heidbuchel  
  • Lieven Annemans  

  Abstract:

  Background: Telemonitoring patients with cardiac implantable electronic devices (CIEDs) can improve their care management. However, the results of cost-effectiveness studies are heterogeneous. Therefore, it is still a matter of debate whether telemonitoring is worth the investment. Objective: This systematic review aims to investigate the cost-effectiveness of telemonitoring patients with CIEDs, focusing on its key drivers, and the impact of the varying perspectives. Methods: A systematic review was performed in PubMed, Web of Science, Embase, and EconLit. The search was completed on July 7, 2022. Studies were included if they fulfilled the following criteria: patients had a CIED, comparison with standard care, and inclusion of health economic evaluations (eg, cost-effectiveness analyses and cost-utility analyses). Only complete and peer-reviewed studies were included, and no year limits were applied. The exclusion criteria included studies with partial economic evaluations, systematic reviews or reports, and studies without standard care as a control group. Besides general study characteristics, the following outcome measures were extracted: impact on total cost or income, cost or income drivers, cost or income drivers per patient, cost or income drivers as a percentage of the total cost impact, incremental cost-effectiveness ratios, or cost-utility ratios. Quality was assessed using the Consensus Health Economic Criteria checklist. Results: Overall, 15 cost-effectiveness analyses were included. All studies were performed in Western countries, mainly Europe, and had primarily a male participant population. Of the 15 studies, 3 (20%) calculated the incremental cost-effectiveness ratio, 1 (7%) the cost-utility ratio, and 11 (73%) the health and cost impact of telemonitoring. In total, 73% (11/15) of the studies indicated that telemonitoring of patients with implantable cardioverter-defibrillators (ICDs) and cardiac resynchronization therapy ICDs was cost-effective and cost-saving, both from a health care and patient perspective. Cost-effectiveness results for telemonitoring of patients with pacemakers were inconclusive. The key drivers for cost reduction from a health care perspective were hospitalizations and scheduled in-office visits. Hospitalization costs were reduced by up to US $912 per patient per year. Scheduled in-office visits included up to 61% of the total cost reduction. Key drivers for cost reduction from a patient perspective were loss of income, cost for scheduled in-office visits and transport. Finally, of the 15 studies, 8 (52%) reported improved quality of life, with statistically significance in only 1 (13%) study (P=.03). Conclusions: From a health care and patient perspective, telemonitoring of patients with an ICD or a cardiac resynchronization therapy ICD is a cost-effective and cost-saving alternative to standard care. Inconclusive results were found for patients with pacemakers. However, telemonitoring can lead to a decrease in providers’ income, mainly due to a lack of reimbursement. Introducing appropriate reimbursement could make telemonitoring sustainable for providers while still being cost-effective from a health care payer perspective. Trial Registration: PROSPERO CRD42022322334; https://tinyurl.com/puunapdr

  • J Med Internet Res 2024;26(1):e47616

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