Improving the Collection of Race, Ethnicity, and Language Data to Reduce Healthcare Disparities: A Case Study from an Academic Medical Center

Perspect Health Inf Manag. 2016 Oct 1;13(Fall):1g. eCollection 2016 fall.

Abstract

Well-designed electronic health records (EHRs) must integrate a variety of accurate information to support efforts to improve quality of care, particularly equity-in-care initiatives. This case study provides insight into the challenges those initiatives may face in collecting accurate race, ethnicity, and language (REAL) information in the EHR. We present the experience of an academic medical center strengthening its EHR for better collection of REAL data with funding from the EHR Incentive Programs for meaningful use of health information technology and the Texas Medicaid 1115 Waiver program. We also present a plan to address some of the challenges that arose during the course of the project. Our experience at an academic medical center can provide guidance about the likely challenges similar institutions may expect when they implement new initiatives to collect REAL data, particularly challenges regarding scope, personnel, and other resource needs.

MeSH terms

  • Academic Medical Centers*
  • Data Accuracy*
  • Data Collection / standards*
  • Ethnicity*
  • Healthcare Disparities / trends*
  • Humans
  • Language*
  • Racial Groups*
  • Texas
  • United States