This event is a complementary on-demand pre-event promotional webinar associated with the DIA 2023 Global Annual Meetingand open to the public.

This webinar will describe a standardized process to collect and synthesize race and ethnicity (R/E) information across multiple data sources to generate estimates of R/E distributions for 30 different diseases/conditions.

Historically, clinical trials have lacked patient representativeness across multiple dimensions (age, gender, race & ethnicity), resulting in significant gaps in understanding clinical safety and efficacy among relevant demographic subgroups. Studies often lack the diversity of recipients that are ultimately impacted by product approval and use in the real world. In its November 2020 Guidance, the FDA promotes enrollment practices that would lead to clinical trials that better reflect the population most likely to use the drug if the drug is approved. Real world data can be used to inform diversity planning for clinical development.

This webinar describes a process that first defines the disease/condition of interest by looking for the accepted name(s) for the disease/condition and the ICD10 diagnosis code(s) that best represent the disease of interest, including the set of names and ICD10s that encompass all the disease’s/condition’s variations.

The process then queries the patient counts, split by race & ethnicity, for each term or ICD10 or sets of terms or ICD10s in a variety healthcare encounter data sources: Longitudinal patient electronic medical records systems (EMRs); Integrated Health Network EMR; Ambulatory EMR; Government sources of publicly available electronic datasets including CDC’s cross-sectional household survey: National Health Interview Survey; Published literature and historical clinical trials in the indication of interest. Data and literature sources are evaluated based on population representativeness, sample size, recency or study period, sensitivity/ability to identify the indication, granularity of R/E categories, completeness of data collected, known and potential biases.

Please also check out DIA’s DIA 2023 Global Annual Meeting taking place June 25-29, 2023!