BACKGROUND: Using information from electronic health records (EHRs) to examine racial/ethnic health disparities is increasingly common. This study examines the degree of concordance between administratively recorded race/ethnicity and the criterion standard of self-reported race/ethnicity at a tertiary care Veterans Affairs Medical Center (VAMC) in North Carolina. METHODS: We compared self-reported race among 204 respondents to a cross-sectional mailed survey of patients with diabetes conducted in 2006-2007 to the race/ethnicity recorded in the EHR. Concordance was defined as the percent agreement between self-reported and administratively-reported race. RESULTS: The overall response rate to the survey was 68.9% (204 of 296). Of the 204 respondents, 32 (15.7%) reported a different race/ethnicity from the race/ethnicity reported in the EHR. Misclassification resulted from either the patient reporting a race/ethnicity and having the information missing in the EHR (9.3% of respondents) or the EHR having a different race/ethnicity listed than reported by the patient (6.3% of respondents). LIMITATIONS: This study was conducted at one VAMC. CONCLUSIONS: While we found misclassification of race/ethnicity in the EHR, the level of discordance is smaller than previously reported in the Veterans Health Administration. Despite this, efforts still need to be made to ensure correct information is included in the EHR.
BACKGROUND: Using information from electronic health records (EHRs) to examine racial/ethnic health disparities is increasingly common. This study examines the degree of concordance between administratively recorded race/ethnicity and the criterion standard of self-reported race/ethnicity at a tertiary care Veterans Affairs Medical Center (VAMC) in North Carolina. METHODS: We compared self-reported race among 204 respondents to a cross-sectional mailed survey of patients with diabetes conducted in 2006-2007 to the race/ethnicity recorded in the EHR. Concordance was defined as the percent agreement between self-reported and administratively-reported race. RESULTS: The overall response rate to the survey was 68.9% (204 of 296). Of the 204 respondents, 32 (15.7%) reported a different race/ethnicity from the race/ethnicity reported in the EHR. Misclassification resulted from either the patient reporting a race/ethnicity and having the information missing in the EHR (9.3% of respondents) or the EHR having a different race/ethnicity listed than reported by the patient (6.3% of respondents). LIMITATIONS: This study was conducted at one VAMC. CONCLUSIONS: While we found misclassification of race/ethnicity in the EHR, the level of discordance is smaller than previously reported in the Veterans Health Administration. Despite this, efforts still need to be made to ensure correct information is included in the EHR.
Authors: Fernanda C G Polubriaginof; Patrick Ryan; Hojjat Salmasian; Andrea Wells Shapiro; Adler Perotte; Monika M Safford; George Hripcsak; Shaun Smith; Nicholas P Tatonetti; David K Vawdrey Journal: J Am Med Inform Assoc Date: 2019-08-01 Impact factor: 4.497
Authors: Elissa V Klinger; Sara V Carlini; Irina Gonzalez; Stella St Hubert; Jeffrey A Linder; Nancy A Rigotti; Emily Z Kontos; Elyse R Park; Lucas X Marinacci; Jennifer S Haas Journal: J Gen Intern Med Date: 2014-12-20 Impact factor: 5.128
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Authors: Jacqueline M Ferguson; Hoda S Abdel Magid; Amanda L Purnell; Mathew V Kiang; Thomas F Osborne Journal: Public Health Rep Date: 2021-04-07 Impact factor: 3.117
Authors: Roberta Z Horth; Shelly Wagstaff; Theron Jeppson; Vishal Patel; Jefferson McClellan; Nicole Bissonette; Michael Friedrichs; Angela C Dunn Journal: BMC Public Health Date: 2019-08-14 Impact factor: 3.295
Authors: Karen H Seal; Daniel Bertenthal; Evan Carey; Carl Grunfeld; Daniel D Bikle; Chuanyi M Lu Journal: J Gen Intern Med Date: 2022-01-01 Impact factor: 6.473