Considerations for Collecting and Analyzing Race and Ethnicity Data in Clinical Studies

In this session, I will present some collective work from the Northwestern University Department of Preventive Medicine's Working Group focusing on Response to Structural Racism in Research and that of the JEDI working within the BERD-SIG. I will present experiences and lessons learned (as a collaborative biostatistician) in conducting research studies involving race and ethnicity data. I will take the perspective of the entire research study life cycle from study design to data collection, analysis, and reporting. As several members of these working groups are collaborative biostatisticians and methodologists, we call upon previous work and experiences across a multitude of fields of study and research study types. I will illustrate several options of setting up data dictionaries and demographic surveys for research study participants, and the aim is to spark discussion on pros and cons for different methods of data collection surrounding these data types. Similarly, we will unpack the meaning and implications for interpretation when considering "adjustment," "confounding", and "heterogeneity of exposure effects" when it comes to the constructs of race and ethnicity. Ultimately, I hope to leave the audience with recommendations for starting point(s) in designing, conducting, analyzing, and reporting on research studies involving race and ethnicity variables. Duke University In-Person Location: Hock Plaza, Room #214 (CRTP) More information: https://ctsi.duke.edu/seminar-considerations-collecting-and-analyzing-r… Zoom registration: https://duke.zoom.us/webinar/register/WN_ewhS91CbSp-UNK8lpVJlfA This event is co-sponsored by the Duke Department of Biostatistics and Bioinformatics and the Duke Biostatistics, Epidemiology, and Research Design (BERD) Methods Core. It is being cross-promoted by the NC BERD Consortium, a collaboration of the CTSA-funded BERD cores at UNC-Chapel Hill, Wake Forest University School of Medicine, and Duke University School of Medicine.