Identifying Family and Unpaid Caregivers in Electronic Health Records: Descriptive Analysis.
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2022-07
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Abstract
Background
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.Objective
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.Methods
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.Results
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.Conclusions
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
ClincalTrials.gov NCT03474380; https://clinicaltrials.gov/ct2/show/NCT03474380.Type
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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 https://hdl.handle.net/10161/26118.
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Scholars@Duke
Jessica Ma
Cynthia Jan Coffman
Virginia Wang
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
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