Identifying Family and Unpaid Caregivers in Electronic Health Records: Descriptive Analysis.



Most efforts to identify caregivers for research use passive approaches such as self-nomination. We describe an approach in which electronic health records (EHRs) can help identify, recruit, and increase diverse representations of family and other unpaid caregivers.


Few health systems have implemented systematic processes for identifying caregivers. This study aimed to develop and evaluate an EHR-driven process for identifying veterans likely to have unpaid caregivers in a caregiver survey study. We additionally examined whether there were EHR-derived veteran characteristics associated with veterans having unpaid caregivers.


We selected EHR home- and community-based referrals suggestive of veterans' need for supportive care from friends or family. We identified veterans with these referrals across the 8 US Department of Veteran Affairs medical centers enrolled in our study. Phone calls to a subset of these veterans confirmed whether they had a caregiver, specifically an unpaid caregiver. We calculated the screening contact rate for unpaid caregivers of veterans using attempted phone screening and for those who completed phone screening. The veteran characteristics from the EHR were compared across referral and screening groups using descriptive statistics, and logistic regression was used to compare the likelihood of having an unpaid caregiver among veterans who completed phone screening.


During the study period, our EHR-driven process identified 12,212 veterans with home- and community-based referrals; 2134 (17.47%) veteran households were called for phone screening. Among the 2134 veterans called, 1367 (64.06%) answered the call, and 813 (38.1%) veterans had a caregiver based on self-report of the veteran, their caregiver, or another person in the household. The unpaid caregiver identification rate was 38.1% and 59.5% among those with an attempted phone screening and completed phone screening, respectively. Veterans had increased odds of having an unpaid caregiver if they were married (adjusted odds ratio [OR] 2.69, 95% CI 1.68-4.34), had respite care (adjusted OR 2.17, 95% CI 1.41-3.41), or had adult day health care (adjusted OR 3.69, 95% CI 1.60-10.00). Veterans with a dementia diagnosis (adjusted OR 1.37, 95% CI 1.00-1.89) or veteran-directed care referral (adjusted OR 1.95, 95% CI 0.97-4.20) were also suggestive of an association with having an unpaid caregiver.


The EHR-driven process to identify veterans likely to have unpaid caregivers is systematic and resource intensive. Approximately 60% (813/1367) of veterans who were successfully screened had unpaid caregivers. In the absence of discrete fields in the EHR, our EHR-driven process can be used to identify unpaid caregivers; however, incorporating caregiver identification fields into the EHR would support a more efficient and systematic identification of caregivers.

Trial registration NCT03474380;





Published Version (Please cite this version)


Publication Info

Ma, Jessica E, Janet Grubber, Cynthia J Coffman, Virginia Wang, S Nicole Hastings, Kelli D Allen, Megan Shepherd-Banigan, Kasey Decosimo, et al. (2022). Identifying Family and Unpaid Caregivers in Electronic Health Records: Descriptive Analysis. JMIR formative research, 6(7). p. e35623. 10.2196/35623 Retrieved from

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Jessica Ma

Assistant Professor of Medicine

Cynthia Jan Coffman

Professor of Biostatistics & Bioinformatics

Virginia Wang

Associate Professor in Population Health Sciences

Dr. Virginia Wang is an Associate Professor in Population Health Sciences and Medicine at the Duke University School of Medicine and Core Faculty in the Duke-Margolis Center for Health Policy. She is also a Core Investigator in the Health Services Research Center of Innovation to Accelerate Discovery and Practice Transformation at the Durham Veterans Affairs Health Care System. Dr. Wang received her PhD in Health Policy and Management, with a focus on organizational behavior. Her research examines organizational influences and policy on the provision of health services, provider strategy and performance, care coordination, and outcomes for patients with complex chronic disease.

Dr. Wang’s research has been supported by the Agency for Healthcare Research and Quality, National Institute of Diabetes and Digestive and Kidney Diseases, Department of Veterans Affairs, and the Centers for Medicare & Medicaid Services Office of Minority Health.

Areas of expertise:  health services research, organizational behavior, health policy, implementation and program evaluation

Susan Nicole Hastings

Professor of Medicine

Kelli Dominick Allen

Adjunct Professor in the Department of Medicine
  • Improving care and outcomes for individuals with osteoarthritis and other musculoskeletal conditions with an emphasis on non-pharmacological therapies including physical activity, weight management, rehabilitation services, and pain coping
    * Understanding rand reducing disparities in musculoskeletal conditions
    * Musculoskeletal conditions in U.S. military Veterans
    * Pragmatic clinical trials
    * Adaptive interventions

Megan E Shepherd-Banigan

Assistant Professor in Population Health Sciences

Dr. Megan Shepherd-Banigan designs research studies to improve the health, emotional well-being, and social functioning of adults with mental and physical disabilities. Her methods combine empirical approaches that address methodologically challenging research questions in health systems and policy research. Dr. Shepherd-Banigan uses large survey and administrative datasets to evaluate the impact of policies that support family members to care for adults with disabilities.  

Dr. Shepherd-Banigan won a VA Career Development Award from 2019-2024 and is studying ways to strengthen family support for veterans under-going traumatic stress treatment. She also leads a project that surveys family caregivers of Vietnam-era veterans who might be eligible for expanded support services under the VA Mission Act to evaluate program impacts. As co-investigator on an NIA-funded CARE IDEAS study (Terri Wetle, PI) , she is investigating end-of-life-care planning and well-being among dementia care dyads.  Finally, Dr. Shepherd-Banigan is leading a project in partnership with the Rosalynn Carter Institute for Caregivers to identify creative empirically-based approaches to support family caregivers. 


Nina Sperber

Associate Professor in Population Health Sciences

My research career has centered on understanding how to improve delivery of new evidence-based practices in health care systems. I work in health services research and development for the VA health care system and have an academic appointment with the Duke University School of Medicine. I create study designs that integrate qualitative and quantitative methods (mixed-methods) and apply Implementation Science and System Science approaches. I currently have a developing body of academic work that uses participatory system dynamics modeling as a strategy to identify system level factors that affect development and implementation of equitable AI tools. For the VA health care system, I direct a cross-functional team that conducts rapid turnaround projects for high priority needs by VHA national, regional, and facility leaders.


Van Houtven

Courtney Harold Van Houtven

Professor in Population Health Sciences

Dr. Courtney Van Houtven is a Professor in The Department of Population Health Science, Duke University School of Medicine and Duke-Margolis Center for Health Policy. She is also a Research Career Scientist in The Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), Durham Veterans Affairs Health Care System. Dr. Van Houtven’s aging and economics research interests encompass long-term care financing, intra-household decision-making, unpaid family and friend care, and home- and community-based services. She examines how family caregiving affects health care utilization, expenditures, health and work outcomes of care recipients and caregivers. She is also interested in understanding how best to support family caregivers to optimize caregiver and care recipient outcomes.

Dr. Van Houtven  is co-PI on the QUERI Program Project, “Optimizing Function and Independence”, in which her caregiver skills training program developed as an RCT in VA, now called Caregivers FIRST, has been implemented at 125 VA sites nationally. The team will evaluate how intensification of an implementation strategy changes adoption. She directs the VA-CARES Evaluation Center, which evaluates the VA’s Caregiver Support Program. She leads a mixed methods R01 study as PI from the National Institute on Aging that will assess the value of "home time" for persons living with dementia and their caregivers (RF1 AG072364).

Areas of expertise: Health Services Research and Health Economics

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