How Administrative Data Collection and Analysis Can Better Reflect Racial and Ethnic Identities

Abstract

Measuring race and ethnicity for administrative data sets and then analyzing these data to understand racial/ethnic disparities present many logistical and theoretical challenges. In this chapter, we conduct a synthetic review of studies on how to effectively measure race/ethnicity for administrative data purposes and then utilize these measures in analyses. Recommendations based on this synthesis include combining the measure of Hispanic ethnicity with the broader racial/ethnic measure and allowing individuals to select more than one race/ethnicity. Data collection should rely on self-reports but could be supplemented using birth certificates or equivalent sources. Collecting data over time, especially for young people, will help identify multiracial and American Indian populations. For those with more complex racial/ethnic identities, including measures of country of origin, language, and recency of immigration can be helpful in addition to asking individuals which racial/ethnic identity they most identify with. Administrative data collection could also begin to incorporate phenotype measures to facilitate the calculation of disparities within race/ethnicity by skin tone. Those analyzing racial/ethnic disparities should understand how these measures are created and attempt to develop fieldwide terminology to describe racial/ethnic identities.