Evidence map›Paper›PMID 41885918›Full record

ArticleJournal of medical Internet research2026

Patient Sharing of Digital Health Data in the Veterans Health Administration: Cross-Sectional Analysis.

Mark S Zocchi, Jessica M Lipschitz, Felicia R Bixler, Stephanie A Robinson, Bella Etingen, Timothy P Hogan, Ndindam Ndiwane, Saige Calkins, Terry Newton, Nilesh Shah and 3 more

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Mark S ZocchieHealth Partnered Evaluation Initiative, VA Bedford Healthcare System, Bedford, MA, United States.ORCID https://orcid.org/0000-0001-9464-9561
Jessica M LipschitzeHealth Partnered Evaluation Initiative, VA Bedford Healthcare System, Bedford, MA, United States.ORCID https://orcid.org/0000-0002-4085-0507
Felicia R BixlereHealth Partnered Evaluation Initiative, VA Bedford Healthcare System, Bedford, MA, United States.ORCID https://orcid.org/0000-0001-9304-4085
Stephanie A RobinsoneHealth Partnered Evaluation Initiative, VA Bedford Healthcare System, Bedford, MA, United States.ORCID https://orcid.org/0000-0002-1352-217X
Bella EtingeneHealth Partnered Evaluation Initiative, VA Bedford Healthcare System, Bedford, MA, United States.ORCID https://orcid.org/0000-0003-1325-9073
Timothy P HoganeHealth Partnered Evaluation Initiative, VA Bedford Healthcare System, Bedford, MA, United States.ORCID https://orcid.org/0000-0002-6888-0927
Ndindam NdiwaneeHealth Partnered Evaluation Initiative, VA Bedford Healthcare System, Bedford, MA, United States.ORCID https://orcid.org/0009-0003-2415-8216
Saige CalkinseHealth Partnered Evaluation Initiative, VA Bedford Healthcare System, Bedford, MA, United States.ORCID https://orcid.org/0000-0002-5806-6569
Terry NewtonOffice of Connected Care, Veterans Health Administration, Washington, DC, United States.ORCID https://orcid.org/0009-0009-2859-8124
Nilesh ShahOffice of Connected Care, Veterans Health Administration, Washington, DC, United States.ORCID https://orcid.org/0009-0004-7921-3793
Ben KrageneHealth Partnered Evaluation Initiative, VA Bedford Healthcare System, Bedford, MA, United States.ORCID https://orcid.org/0000-0002-2553-9489
Alexander S YoungeHealth Partnered Evaluation Initiative, VA Bedford Healthcare System, Bedford, MA, United States.ORCID https://orcid.org/0000-0002-9367-9213
Stephanie L ShimadaeHealth Partnered Evaluation Initiative, VA Bedford Healthcare System, Bedford, MA, United States.ORCID https://orcid.org/0000-0002-6517-5122

Funding

Toward optimizing digital mental health interventions: A clinical trial aimed at understanding what drives patient engagement.K23MH120324 · NIMH · BRIGHAM AND WOMEN'S HOSPITAL · PI LIPSCHITZ, JESSICA MORROW · 2020 to 2024
$960k
NIMH NIH HHS K23 MH120324
6 · The paper itself

Abstract

backgroundThe integration of patient-generated health data (PGHD) into health care has the potential to significantly transform patient care and clinical practice. PGHD includes health-related data created by patients, enabling the collection of health data beyond traditional health care settings. The Veterans Health Administration (VA) has taken proactive steps to incorporate PGHD into health care through its Share My Health Data (SMHD) mobile app. Launched in 2023, the SMHD app allows veterans to securely share data from their personal digital health devices with the VA for clinical and research use. However, data characterizing patients who use such tools in real-world health care systems are lacking, creating an evidence gap for implementing PGHD-informed care equitably.

objectiveThis study aimed to identify the characteristics of patients using the VA SMHD mobile app, which allows veterans to share PGHD with the VA.

methodsWe conducted a cross-sectional analysis of veterans who began using SMHD between October 2023 and September 2024 (n=3157, "SMHD users"). We collected demographic information, including age, sex, race/ethnicity, and rurality, and clinical information, including physiological and mental health conditions, from VA administrative data. We compared characteristics of SMHD users to a 10% random sample of veterans from the same underlying administrative data cohort that had never used the app (n=632,187, "nonusers"). Statistical analyses were performed using chi-square tests, independent t tests, and multivariable regression to assess the relationship between use and key characteristics.

resultsMiddle-aged veterans were more likely to be SMHD users (40-49 years: odds ratio [OR] 1.55, P<.001; 50-59 years: OR 1.37, P<.001), while veterans aged 60 years and over were less likely (60-69 years: OR 0.72, P<.001; ≥70 years: OR 0.24, P<.001). Female (OR 1.23, P<.001) and married (OR 1.31, P<.001) veterans were more likely to be SMHD users than male and unmarried veterans. In contrast, Black or African American (OR 0.62, P<.001) and rural (OR 0.82, P<.001) veterans were less likely to be SMHD users than White and urban veterans. Veterans in higher-income zip codes (OR 1.36, P<.001) were more likely to have used the app than those in lower-income zip codes. Clinically, SMHD users were more likely to have a service-connected disability (OR 1.81, P<.001), multiple physiological conditions (OR 1.86, P<.001), and multiple mental health diagnoses (OR 1.35, P<.001) versus none.

conclusionsVeterans who used the SMHD app differed significantly from nonusers across several demographic and clinical characteristics. These insights identify specific demographic and clinical subgroups with higher and lower app adoption, providing an evidence base to inform targeted implementation and outreach and support strategies to promote enhanced engagement in PGHD-informed care.

Indexed as

Mobile ApplicationsUnited States Department of Veterans AffairsVeteransAdultAgedCross-Sectional StudiesDigital HealthFemaleHumansMaleMiddle AgedUnited Statesdigital phenotypingmHealthmobile healthpatient-generated health dataveteranswearable electronic devices

Identifiers

PMID41885918
PMCPMC13066783

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.