Using Common Data Elements to Foster Interoperability of Research on Health Disparities

Common Data Elements (CDEs) are standardized questions, variables, or measures with specific sets of responses that are common across multiple studies. They are organized around a particular research topic or question, validated, and defined via a consensus building process. Their use fosters comparability of results and findings across studies. Defining CDEs and incorporating them at the data collection/creation stage promotes good data management practices by ensuring the interoperability and reusability of data from the beginning of the research data lifecycle.

CDEs are more common in NIH-funded clinical and biomedical research than in social, behavioral, and economic (SBE) research. Yet the community-driven, consensus-building approach to defining CDEs makes them well suited to measuring complex social phenomena, such as race and gender. Not only do CDEs offer both a repository of established measures, they also offer a mechanism for the research community to define new measures that reflect expanding knowledge and shifting identities. For example, as concepts of race and gender change over time and in different contexts, researchers can establish new CDEs to reflect those changes. This characteristic of CDEs – their flexibility and consensus-driven nature – has the potential to strengthen research on diverse populations.

The Social, Behavioral, and Economic COVID Coordinating Center at ICPSR (SBE CCC) is leading the effort to establish CDEs for SBE research into the effects of the COVID-19 pandemic. We are collaborating with fifteen NIH-funded research teams who are examining pandemic-related health disparities related to race, ethnicity, sex, geography, income, and other factors. This talk will describe our process for identifying, validating, and building consensus on CDEs related to COVID public health policies. We will also discuss plans to establish additional CDEs for COVID research, and to use SBE research on COVID-19 to illustrate how CDEs can improve harmonization across social science research.