Transition to the new race/ethnicity data collection standards in the Department of Veterans Affairs.
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).


CONCLUSIONS
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.
Sohn
Min-Woong
MW
Midwest Center for Health Services and Policy Research, Hines, IL, USA. msohn@northwestern.edu
Zhang
Huiyuan
H
Arnold
Noreen
N
Stroupe
Kevin
K
Taylor
Brent C
BC
Wilt
Timothy J
TJ
Hynes
Denise M
DM