Evidence map›Paper›PMID 40549960›Full record

ArticleJMIR mHealth and uHealth2025

Integrating Mobile Health App Data Into Electronic Medical or Health Record Systems and Its Impact on Health Care Delivery and Patient Health Outcomes: Scoping Review.

Jialing Lin, Shona Marie Bates, Luke N Allen, Michael Wright, Limin Mao, Michael Kidd

Abstract readScoping Review
In one paragraph

Article in JMIR mHealth and uHealth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Patient Portal Use Among Older Adults: A Systematic Review and Meta-Analysis.Proceedings. IEEE International Conference on Healthcare Informatics · 2026
    Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. More Older Adults Try Patient Portals in Recent Years, but Many Don't Continue: A Meta-Analysis.Extended abstracts on Human factors in computing systems. CHI Conference · 2026
    Article
  12. Article
  13. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jialing LinInternational Centre for Future Health Systems, University of New South Wales, Level 2, AGSM Building, UNSW Sydney, Kensington, 2052, Australia, 61 02 9348 1394, 61 02 9348 1394.ORCID 0000-0002-0643-9191
Shona Marie BatesInternational Centre for Future Health Systems, University of New South Wales, Level 2, AGSM Building, UNSW Sydney, Kensington, 2052, Australia, 61 02 9348 1394, 61 02 9348 1394.ORCID 0000-0003-3976-0253
Luke N AllenInternational Centre for Future Health Systems, University of New South Wales, Level 2, AGSM Building, UNSW Sydney, Kensington, 2052, Australia, 61 02 9348 1394, 61 02 9348 1394.ORCID 0000-0003-2750-3575
Michael WrightInternational Centre for Future Health Systems, University of New South Wales, Level 2, AGSM Building, UNSW Sydney, Kensington, 2052, Australia, 61 02 9348 1394, 61 02 9348 1394.ORCID 0000-0003-2708-4753
Limin MaoInternational Centre for Future Health Systems, University of New South Wales, Level 2, AGSM Building, UNSW Sydney, Kensington, 2052, Australia, 61 02 9348 1394, 61 02 9348 1394.ORCID 0000-0003-0995-5789
Michael KiddInternational Centre for Future Health Systems, University of New South Wales, Level 2, AGSM Building, UNSW Sydney, Kensington, 2052, Australia, 61 02 9348 1394, 61 02 9348 1394.ORCID 0000-0002-0221-1245

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Mobile health (mHealth) apps are increasingly being used to capture patient health data, provide information, and guide self-management, with reported improvements in health care service delivery and outcomes. However, the impact of integrating mHealth app data into electronic medical record or electronic health record (EMR/EHR) systems remains underexplored. Objective: This study aims to identify what is known about the impact of integrating mHealth app data into EMR/EHR systems on health care delivery and patient outcomes. Methods: A scoping review was conducted to identify original studies that investigated the integration of patient-facing mHealth app data into EMR/EHR systems and the impact on health care outcomes. The PubMed, Embase, Web of Science, Cochrane Library, CINAHL, ProQuest, and PsycINFO databases were searched for papers published between January 2014 and July 2024. Two authors independently screened and extracted data on study characteristics, mHealth app features, details of integration with EMR/EHR systems, and effects on health care delivery and patient outcomes. Results: Nineteen studies with 113,135 participants were included. Among these, 6 were randomized clinical trial studies, 8 were conducted in the United States, 12 occurred in hospital settings, 15 involved adult participants, and 6 targeted diabetes management. Main features of the apps and EMR/EHR systems can be categorized into tracking or recording health data (n=19), app data integrated into EMR/EHR systems (n=19), app data summarized or presented on EMR/EHR interface (n=19), communication with the health care team (n=12), reminders or alerts (n=10), synchronization with other apps or devices (n=8), educational information (n=4), and using existing portal credentials to app access (n=2). Most studies reported benefits of integrating the app and EMR/EHR, such as enhanced patient education and self-management (n=5), real-time data recorded and shared with clinicians (n=4), support for clinical decision-making (n=3), improved communication between patients and clinicians (n=7), and improved patient outcomes (n=13). Challenges identified included high drop-off rates in app usage (n=3), limited accessibility due to device restrictions (n=3), incompatibility between mHealth apps and EMR/EHR systems (n=3), increased clinical workload in response to additional information (n=3), data accuracy issues due to network connectivity (n=1), and data security concerns (n=1). Conclusions: Evidence suggests that the effective integration of mHealth app data into EMR/EHR systems can enhance both clinicians' health care delivery and patients' health outcomes. However, current literature is limited, and future opportunities remain to examine the impact on long-term outcomes, such as mortality, readmissions, and costs, and assess the scalability and sustainability of integration among more broader health conditions and disabilities across diverse health care settings.

Indexed as

Delivery of Health CareElectronic Health RecordsMobile ApplicationsOutcome Assessment, Health CareHumansTelemedicinedigital healthelectronic medical recordsimplementationintegrationmHealthmobile phonesscoping reviewusability

Identifiers

PMID40549960
PMCPMC12208509

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.