دورية أكاديمية
Collection and Analysis of Adherence Information for Software as a Medical Device Clinical Trials: Systematic Review
العنوان: | Collection and Analysis of Adherence Information for Software as a Medical Device Clinical Trials: Systematic Review |
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المؤلفون: | Emily Grayek, Tamar Krishnamurti, Lydia Hu, Olivia Babich, Katherine Warren, Baruch Fischhoff |
المصدر: | JMIR mHealth and uHealth, Vol 11, p e46237 (2023) |
بيانات النشر: | JMIR Publications, 2023. |
سنة النشر: | 2023 |
المجموعة: | LCC:Information technology LCC:Public aspects of medicine |
مصطلحات موضوعية: | Information technology, T58.5-58.64, Public aspects of medicine, RA1-1270 |
الوصف: | BackgroundThe rapid growth of digital health apps has necessitated new regulatory approaches to ensure compliance with safety and effectiveness standards. Nonadherence and heterogeneous user engagement with digital health apps can lead to trial estimates that overestimate or underestimate an app’s effectiveness. However, there are no current standards for how researchers should measure adherence or address the risk of bias imposed by nonadherence through efficacy analyses. ObjectiveThis systematic review aims to address 2 critical questions regarding clinical trials of software as a medical device (SaMD) apps: How well do researchers report adherence and engagement metrics for studies of effectiveness and efficacy? and What efficacy analyses do researchers use to account for nonadherence and how appropriate are their methods? MethodsWe searched the Food and Drug Administration’s registration database for registrations of repeated-use, patient-facing SaMD therapeutics. For each such registration, we searched ClinicalTrials.gov, company websites, and MEDLINE for the corresponding clinical trial and study articles through March 2022. Adherence and engagement data were summarized for each of the 24 identified articles, corresponding to 10 SaMD therapeutics. Each article was analyzed with a framework developed using the Cochrane risk-of-bias questions to estimate the potential effects of imperfect adherence on SaMD effectiveness. This review, funded by the Richard King Mellon Foundation, is registered on the Open Science Framework. ResultsWe found that although most articles (23/24, 96%) reported collecting information about SaMD therapeutic engagement, of the 20 articles for apps with prescribed use, only 9 (45%) reported adherence information across all aspects of prescribed use: 15 (75%) reported metrics for the initiation of therapeutic use, 16 (80%) reported metrics reporting adherence between the initiation and discontinuation of the therapeutic (implementation), and 4 (20%) reported the discontinuation of the therapeutic (persistence). The articles varied in the reported metrics. For trials that reported adherence or engagement, there were 4 definitions of initiation, 8 definitions of implementation, and 4 definitions of persistence. All articles studying a therapeutic with a prescribed use reported effectiveness estimates that might have been affected by nonadherence; only a few (2/20, 10%) used methods appropriate to evaluate efficacy. ConclusionsThis review identifies 5 areas for improving future SaMD trials and studies: use consistent metrics for reporting adherence, use reliable adherence metrics, preregister analyses for observational studies, use less biased efficacy analysis methods, and fully report statistical methods and assumptions. |
نوع الوثيقة: | article |
وصف الملف: | electronic resource |
اللغة: | English |
تدمد: | 2291-5222 |
Relation: | https://mhealth.jmir.org/2023/1/e46237; https://doaj.org/toc/2291-5222 |
DOI: | 10.2196/46237 |
URL الوصول: | https://doaj.org/article/212e3ab5d3b64231a6adff8943031284 |
رقم الأكسشن: | edsdoj.212e3ab5d3b64231a6adff8943031284 |
قاعدة البيانات: | Directory of Open Access Journals |
تدمد: | 22915222 |
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DOI: | 10.2196/46237 |