Wendy K. K. Lam

Clinical trials have provided evidence for determining treatment effectiveness. However, clinical trial participants have been underrepresented by diverse and special population groups (e.g., younger and older adults, different races/ethnicities), contributing to disparities in our understanding of diseases and treatments in all those affected. Addressing these disparities in clinical trial participation would be critical to achieving health equity in the USA and beyond. To assess enrollment inclusivity in clinical research at a large academic medical center in the southeast, we used administrative information to develop a snapshot of clinical research participation by age, sex, race, ethnicity, and rurality that was accessible to the public. We compared research enrollment statistics with relevant geographic benchmarks (county, state, and national) from the 2020 US Census. Comparisons revealed 1) over-participation by females relative to county, state, and national benchmarks; 2) under-representation of Black/African Americans relative to county, but higher relative to state and national, levels; and 3) underrepresentation of Hispanic/Latino and Asian groups. The ISP Snapshot has promoted accountability and transparency in this institution’s efforts toward health equity. The process has highlighted the need to update and standardize use of outdated categories (e.g., binary gender, rural status) that limit accurate reporting.

Prior research highlights that rural populations have been historically underrepresented/excluded from clinical research. The primary objective of this study was to describe the inclusion of rural populations within our research enterprise using Clinical Research Management System demographic information at a large academic medical center in the Southeast. This was a cross‐sectional study using participant demographic information for all protocols entered into our Clinical Research Management System between May 2018 and March 2021. Descriptive statistics were used to analyze the representation of rural and non‐rural participants and demographic breakdown by age, sex, race, and ethnicity for our entire enterprise and at the state level. We also compared Material Community Deprivation Index levels between urban and rural participants. Results indicated that 19% of the research population was classified as rural and 81% as non‐rural for our entire sample, and 17.5% rural and 82.5% urban for our state‐level sample. There were significant differences in race, sex, and age between rural and non‐rural participants and Material Community Deprivation Indices between rural and non‐rural participants. Lessons learned and recommendations for increasing the inclusion of rural populations in research are discussed.

Newborn screening was developed more than 50 years ago as a way to prevent developmental disability associated with untreated phenylketonuria through early detection and treatment.¹ Since then, newborn screening has expanded to include dozens of conditions that, if not identified in early infancy, are associated with significant morbidity and mortality.² In the United States, each state is responsible for determining which conditions should be included in screening. Adding a condition to a state newborn screening panel is challenging. Not only does the newborn screening program have to implement the screening test, but systems must be put into place to enable diagnostic confirmation, prompt treatment, and public health monitoring. The resources needed to expand newborn screening must be weighed against the expected benefit, and because virtually all newborns are screened, the potential harms (eg, false positives, overdiagnosis) must be carefully considered.