Accuracy of Race, Ethnicity, and Language Preference in an Electronic Health Record

Abstract

BACKGROUND: Collection of data on race, ethnicity, and language preference is required as part of the “meaningful use” of electronic health records (EHRs). These data serve as a foundation for interventions to reduce health disparities. OBJECTIVE: Our aim was to compare the accuracy of EHR-recorded data on race, ethnicity, and language preference to that reported directly by patients. DESIGN/SUBJECTS/MAIN MEASURES: Data collected as part of a tobacco cessation intervention for minority and low-income smokers across a network of 13 primary care clinics (n = 569). KEY RESULTS: Patients were more likely to self-report Hispanic ethnicity (19.6 % vs. 16.6 %, p < 0.001) and African American race (27.0 % vs. 20.4 %, p < 0.001) than was reported in the EHR. Conversely, patients were less likely to complete the survey in Spanish than the language preference noted in the EHR suggested (5.1 % vs. 6.3 %, p < 0.001). Thirty percent of whites self-reported identification with at least one other racial or ethnic group, as did 37.0 % of Hispanics, and 41.0 % of African Americans. Over one-third of EHR-documented Spanish speakers elected to take the survey in English. One-fifth of individuals who took the survey in Spanish were recorded in the EHR as English-speaking. CONCLUSION: We demonstrate important inaccuracies and the need for better processes to document race/ ethnicity and language preference in EHRs.