Accuracy of race, ethnicity, and language preference in an electronic health record

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.

Our aim was to compare the accuracy of EHR-recorded data on race, ethnicity, and language preference to that reported directly by patients.

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).

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.

We demonstrate important inaccuracies and the need for better processes to document race/ ethnicity and language preference in EHRs.