ArticleJournal of medical Internet research2020
Selecting Mobile Health Technologies for Electronic Health Record Integration: Case Study.
Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Effectiveness and Implementation of Digital Health Interventions on Physiological, Psychological, and Functional Outcomes in Adults With Multimorbidity: Systematic Review and Meta-Analysis of Randomized Controlled Trials.Journal of medical Internet research · 2026Pooled it
- Selection and Prioritization of Medical Devices for HTA Evaluation: A Systematic Review of Existing Approaches.Applied health economics and health policy · 2025Pooled it
- The gaps and challenges in digital health technology use as perceived by patients: a scoping review and narrative meta-synthesis.Frontiers in digital health · 2025Pooled it
- Electronic health records in Brazil: Prospects and technological challenges.Frontiers in public health · 2022Pooled it
- AI-Driven Wearable Bioelectronics in Digital Healthcare.Biosensors · 2025Review
- Twenty-Five Years of Evolution and Hurdles in Electronic Health Records and Interoperability in Medical Research: Comprehensive Review.Journal of medical Internet research · 2025Review
- Perceptions of electronic health records by ethnically diverse groups in mental health: A systematic literature review.Global mental health (Cambridge, England) · 2025Review
- A Reflective Thematic Analysis Into the Perceptions of Pregnant Radiographers Regarding the Usefulness of the PregiDose Mobile App to Enhance Fetal Dosimetry and Well-Being: Qualitative Exploration.JMIR formative research · 2024Article
- Review
- Biases in Electronic Health Records Data for Generating Real-World Evidence: An Overview.Journal of healthcare informatics research · 2024Article
- Interviews with HIV Experts for Development of a Mobile Health Application in HIV Care-A Qualitative Study.Healthcare (Basel, Switzerland) · 2023Article
- A mobile health application for patients eligible for statin therapy: app development and qualitative feedback on design and usability.BMC medical informatics and decision making · 2023Article
- The Need for Data Standards and Implementation Policies to Integrate CGM Data into the Electronic Health Record.Journal of diabetes science and technology · 2023Review
- Mapping the global landscape of wearable devices in healthcare: A dual-database bibliometric analysis (2016-2026).Digital healthReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Mobile health (mHealth) technologies, such as wearable devices and sensors that can be placed in the home, allow for the capture of physiologic, behavioral, and environmental data from patients between clinic visits. The inclusion of these data in the medical record may benefit patients and providers. Most health systems now have electronic health records (EHRs), and the ability to pull and send data to and from mobile devices via smartphones and other methods is increasing; however, many challenges exist in the evaluation and selection of devices to integrate to meet the needs of diverse patients with a range of clinical needs. We present a case report that describes a method that our health system uses, guided by a telehealth model to evaluate the selection of devices for EHR integration.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.