Comparing mental and physical health of U.S. veterans by VA healthcare use: implications for generalizability of research in the VA electronic health records. Academic Article uri icon

Overview

abstract

  • OBJECTIVE: The Department of Veterans Affairs' (VA) electronic health records (EHR) offer a rich source of big data to study medical and health care questions, but patient eligibility and preferences may limit generalizability of findings. We therefore examined the representativeness of VA veterans by comparing veterans using VA healthcare services to those who do not. METHODS: We analyzed data on 3051 veteran participants age ≥ 18 years in the 2019 National Health Interview Survey. Weighted logistic regression was used to model participant characteristics, health conditions, pain, and self-reported health by past year VA healthcare use and generate predicted marginal prevalences, which were used to calculate Cohen's d of group differences in absolute risk by past-year VA healthcare use. RESULTS: Among veterans, 30.4% had past-year VA healthcare use. Veterans with lower income and members of racial/ethnic minority groups were more likely to report past-year VA healthcare use. Health conditions overrepresented in past-year VA healthcare users included chronic medical conditions (80.6% vs. 69.4%, d = 0.36), pain (78.9% vs. 65.9%; d = 0.35), mental distress (11.6% vs. 5.9%; d = 0.47), anxiety (10.8% vs. 4.1%; d = 0.67), and fair/poor self-reported health (27.9% vs. 18.0%; d = 0.40). CONCLUSIONS: Heterogeneity in veteran sociodemographic and health characteristics was observed by past-year VA healthcare use. Researchers working with VA EHR data should consider how the patient selection process may relate to the exposures and outcomes under study. Statistical reweighting may be needed to generalize risk estimates from the VA EHR data to the overall veteran population.

publication date

  • December 9, 2022

Research

keywords

  • United States Department of Veterans Affairs
  • Veterans

Identity

PubMed Central ID

  • PMC9733218

Scopus Document Identifier

  • 85143674034

Digital Object Identifier (DOI)

  • 10.1186/s12913-022-08899-y

PubMed ID

  • 36494829

Additional Document Info

volume

  • 22

issue

  • 1