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Patient Sharing of Digital Health Data in the Veterans Health Administration: Cross-Sectional Analysis
by
Calkins, Saige
, Kragen, Ben
, Newton, Terry
, Bixler, Felicia R
, Shah, Nilesh
, Zocchi, Mark S
, Hogan, Timothy P
, Lipschitz, Jessica M
, Shimada, Stephanie L
, Ndiwane, Ndindam
, Young, Alexander S
, Robinson, Stephanie A
, Etingen, Bella
in
Adult
/ African Americans
/ Aged
/ Care and treatment
/ Cross-Sectional Studies
/ Digital Health
/ Female
/ Humans
/ Male
/ Middle Aged
/ Mobile Applications
/ Original Paper
/ Patient Generated Health Data
/ Patients
/ Public health
/ United States
/ United States Department of Veterans Affairs
/ Veterans - statistics & numerical data
2026
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Patient Sharing of Digital Health Data in the Veterans Health Administration: Cross-Sectional Analysis
by
Calkins, Saige
, Kragen, Ben
, Newton, Terry
, Bixler, Felicia R
, Shah, Nilesh
, Zocchi, Mark S
, Hogan, Timothy P
, Lipschitz, Jessica M
, Shimada, Stephanie L
, Ndiwane, Ndindam
, Young, Alexander S
, Robinson, Stephanie A
, Etingen, Bella
in
Adult
/ African Americans
/ Aged
/ Care and treatment
/ Cross-Sectional Studies
/ Digital Health
/ Female
/ Humans
/ Male
/ Middle Aged
/ Mobile Applications
/ Original Paper
/ Patient Generated Health Data
/ Patients
/ Public health
/ United States
/ United States Department of Veterans Affairs
/ Veterans - statistics & numerical data
2026
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Patient Sharing of Digital Health Data in the Veterans Health Administration: Cross-Sectional Analysis
by
Calkins, Saige
, Kragen, Ben
, Newton, Terry
, Bixler, Felicia R
, Shah, Nilesh
, Zocchi, Mark S
, Hogan, Timothy P
, Lipschitz, Jessica M
, Shimada, Stephanie L
, Ndiwane, Ndindam
, Young, Alexander S
, Robinson, Stephanie A
, Etingen, Bella
in
Adult
/ African Americans
/ Aged
/ Care and treatment
/ Cross-Sectional Studies
/ Digital Health
/ Female
/ Humans
/ Male
/ Middle Aged
/ Mobile Applications
/ Original Paper
/ Patient Generated Health Data
/ Patients
/ Public health
/ United States
/ United States Department of Veterans Affairs
/ Veterans - statistics & numerical data
2026
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Patient Sharing of Digital Health Data in the Veterans Health Administration: Cross-Sectional Analysis
Journal Article
Patient Sharing of Digital Health Data in the Veterans Health Administration: Cross-Sectional Analysis
2026
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Overview
The 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.
This study aimed to identify the characteristics of patients using the VA SMHD mobile app, which allows veterans to share PGHD with the VA.
We 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.
Middle-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.
Veterans 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.
Publisher
Journal of Medical Internet Research,JMIR Publications Inc,JMIR Publications
Subject
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