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Concordance Between Electronic Health Record-Recorded Race and Ethnicity and Patient Report in Emergency Department
Nicholas R Pettit1, Kathleen A Lane2, Leslie Gibbs1
1Department of Emergency Medicine (Pettit, Gibbs, Musey), Indiana University School of Medicine, Indianapolis, IN.
Objective:
We assessed the concordance of patient-reported race and ethnicity for emergency department (ED) patients compared with what was recorded in the electronic health record.
Methods:
We conducted a single-center, prospective, observational study of 744 ED patients (English- and/or Spanish-speaking), asking them to describe their race and ethnicity. We compared the distributions of ethnicity and race between patient-reported and electronic health record data using McNemar's test. We calculated percent agreement and Cohen's kappa, with 95% confidence intervals (CI), for the concordance of patient-reported race and ethnicity with electronic health record data.
Results:
Of 744 ED patients, 731 participants who completed the survey reported their ethnicity, resulting in 98.2% of electronic health records obtained ethnicities matched self-reported data (kappa = 0.95; 95% CI: 0.92 to 0.98). For those who self-reported as Hispanic, only 92.3% agreement was observed between the self-reported and electronic health record values. For all patients who had race recorded, 85.4% agreement was observed (kappa = 0.75; 95% CI 0.71 to 0.79). High rates of agreement were observed for Black or African American patients (98.7%) and White patients (96.6%), with low rates for those who identified as "More than one race" (22.9%) or "Other" race (1.8%). In the subset of Hispanic patients, low rates of agreement (25.0%) were observed for race (kappa = 0.10; 95% CI 0.01 to 0.19).
Conclusions:
Documentation discordance regarding race and ethnicity exists between electronic health records and self-reported data for our ED patients, particularly for ethnically Hispanic and Latino/a patients. Future efforts should focus on ensuring that demographic information in the electronic health record is accurately collected.
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