134 Comparing Real-World Impacts of Cohorts using the Translational Science Benefits Model

Abstract

OBJECTIVES/GOALS: The Translational Science Benefits Model (TSBM), developed at Washington University in St. Louis, was used to create a survey to collect group-level data on the real-world impacts of research. It was used with two cohorts of CTSA-supported pilot studies to compare the benefits of campus-community partnerships to campus-only projects. METHODS/STUDY POPULATION: Investigators from two funding streams were surveyed: a campus-based cohort (n=31), and a campus-community partnership cohort (n=6). All studies were related to COVID-19. The Translational Benefits Survey collected quantitative and qualitative data for each of the 30 TSBM benefits, in 4 benefit categories: clinical, community, economic and policy. Text provided by investigators to support each reported benefit was evaluated by two coders through a process that required coder consensus to verify a benefit as realized. Verified benefits were aggregated for each cohort, and the percentage of projects per cohort with realized clinical, community, economic and policy benefits were calculated. RESULTS/ANTICIPATED RESULTS: Campus-community partnerships did not realize any clinical benefits, whereas 26% of campus-based projects realized at least one clinical benefit. In contrast, campus-community partnerships were more likely to realize community health benefits (17% vs 10% of campus projects) and economic benefits (17% vs 13% of campus projects). We identified a substantial amount of self-reported benefits (64% across all categories) that were unable to be confirmed as realized using the provided text, which either described activities not relevant to the selected benefit, or lacked critical details needed to verify that the benefit was realized. DISCUSSION/SIGNIFICANCE: This project demonstrates that the TSBM can be utilized to collect group-level data and to compare cohorts’real-world benefits. It also illuminates the need to improve the process for verifying self-reported benefits. Sharing data on these real-world impacts has the potential to convey the strengths of translational science to the public.