Medicaid coverage accuracy in electronic health records

Miguel Marino, Heather Angier, Steele Valenzuela, Megan Hoopes, Marie Killerby, Brenna Blackburn, Nathalie Huguet, John Heintzman, Brigit Hatch, Jean P. O'Malley, Jennifer E. DeVoe

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


Health insurance coverage facilitates access to preventive screenings and other essential health care services, and is linked to improved health outcomes; therefore, it is critical to understand how well coverage information is documented in the electronic health record (EHR) and which characteristics are associated with accurate documentation. Our objective was to evaluate the validity of EHR data for monitoring longitudinal Medicaid coverage and assess variation by patient demographics, visit types, and clinic characteristics. We conducted a retrospective, observational study comparing Medicaid status agreement between Oregon community health center EHR data linked at the patient-level to Medicaid enrollment data (gold standard). We included adult patients with a Medicaid identification number and ≥1 clinic visit between 1/1/2013–12/31/2014 [>1 million visits (n = 135,514 patients)]. We estimated statistical correspondence between EHR and Medicaid data at each visit (visit-level) and for different insurance cohorts over time (patient-level). Data were collected in 2016 and analyzed 2017–2018. We observed excellent agreement between EHR and Medicaid data for health insurance information: kappa (>0.80), sensitivity (>0.80), and specificity (>0.85). Several characteristics were associated with agreement; at the visit-level, agreement was lower for patients who preferred a non-English language and for visits missing income information. At the patient-level, agreement was lower for black patients and higher for older patients seen in primary care community health centers. Community health center EHR data are a valid source of Medicaid coverage information. Agreement varied with several characteristics, something researchers and clinic staff should consider when using health insurance information from EHR data.

Original languageEnglish (US)
Pages (from-to)297-304
Number of pages8
JournalPreventive Medicine Reports
StatePublished - Sep 2018


  • Electronic health records
  • Health insurance
  • Health policy
  • Medicaid

ASJC Scopus subject areas

  • Health Informatics
  • Public Health, Environmental and Occupational Health


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