Author(s): Sohn MW, Zhang H, Arnold N, Stroupe K, Taylor BC,
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Abstract BACKGROUND: Patient race in the Department of Veterans Affairs (VA) information system was previously recorded based on an administrative or clinical employee's observation. Since 2003, the VA started to collect self-reported race in compliance with a new federal guideline. We investigated the implications of this transition for using race/ethnicity data in multi-year trends in the VA and in other healthcare data systems that make the transition. METHODS: All unique users of VA healthcare services with self-reported race/ethnicity data in 2004 were compared with their prior observer-recorded race/ethnicity data from 1997-2002 (N = 988,277). RESULTS: In 2004, only about 39\% of all VA healthcare users reported race/ethnicity values other than "unknown" or "declined." Females reported race/ethnicity at a lower rate than males (27\% vs. 40\%; p < 0.001). Over 95\% of observer-recorded data agreed with self-reported data. Compared with the patient self-reported data, the observer-recorded White and African American races were accurate for 98\% (kappa = 0.89) and 94\% (kappa = 0.93) individuals, respectively. Accuracy of observer-recorded races was much worse for other minority groups with kappa coefficients ranging between 0.38 for American Indian or Alaskan Natives and 0.79 for Hispanic Whites. When observer-recorded race/ethnicity values were reclassified into non-African American groups, they agreed with the self-reported data for 98\% of all individuals (kappa = 0.93). CONCLUSION: For overall VA healthcare users, the agreement between observer-recorded and self-reported race/ethnicity was excellent and observer-recorded and self-reported data can be used together for multi-year trends without creating serious bias. However, this study also showed that observation was not a reliable method of race/ethnicity data collection for non-African American minorities and racial disparity might be underestimated if observer-recorded data are used due to systematic patterns of inaccurate race/ethnicity assignments.
This article was published in Popul Health Metr
and referenced in Journal of Biometrics & Biostatistics