Race and Gender in Integrated Data Systems: Why, Wherefrom, and How

Background and Purpose: Integrated administrative data systems (IADs) are a powerful resource to implement research and analysis that informs social work and social policy. IADs commonly capture racial and gender identity data from multiple administrative sources, but there is no agreed upon criteria for whether and how to synthesize this information in a way that (1) produces knowledge to advance equity, while (2) underscoring race and gender as social constructs. This study leverages a county-level IAD to test and analyze an event-table design to represent racial and gender identities that, when informed with historical and community knowledge, may meet both of the aforementioned goals.

Methods: Event tables are data sets created by linking administrative data from vital records and other systems that are relevant to a specific research question. This process entails cleaning and standardizing the data followed by implementing deterministic and probabilistic data linkage methods. Once a unique identifier is given to each individual, data on individual’s “events” within each system and their timing (dates) can be structured into longitudinal data for research.

To illustrate our approach, we present a case study on a research study that focuses on characterizing people that interact with homelessness services and workforce development supports in an urban county. The sample consists of 820 individuals. We include multiple race identifiers for each person in the registry as shown across all systems and share this tabulated data with community partners whose policies will be informed by our analysis. Based on this experience, we develop criteria to inform the use of racial and gender identity data when there are discrepancies across systems and when categories for these variables differ across administrative systems.

Results: Preliminary results show that intra-person variations in racial and gender identity across administrative data are rare but relevant to highlight. Sharing these variations with community partners elevates the awareness of race and gender as social constructs, increases cross knowledge sharing between researchers and community partners, and has the potential to improve data collection and services.

Conclusions and Implications: We provide a case study for equity considerations in the use of race and gender variables in integrated data systems. We highlight the value of including qualitative knowledge from agency data managers, users, and those represented in the data to inform the synthesis of information around gender and race. We present historical and social context behind potential discrepancies and discuss approaches to missing data. Finally, we illustrate how this approach can guide research analysis and contextualize results, thus enhancing the research process and advancing equity with IADs.