138 Practical considerations for early career investigators interested in engaging with large national databases

Objectives/Goals: To present practical considerations especially important for early career investigators using large cloud-based data portals, with lessons learned from a descriptive project characterizing chronic pain among young Black adults. Our translational science goal is to improve investigators’ engagement with these types of data sources. Methods/Study Population: Lessons learned from our analytic experience conducting secondary data analyses using data from the NIH All of Us Research Program (AoU). The analytic activities are in support of Aim 1 of an NIH K01 Mentored Research Scientist award focusing on young Black adults with chronic pain. Engagement with data was a collaboration across junior and senior investigators with expertise in quantitative and qualitative methods. We assessed AoU data for usability, data completeness, accessibility, and program support. Variables of interest in the K01 project include physical and mental health, commodities, health care utilization, SDoH, and demographics. We present qualitative descriptions of our user experiences, paired with descriptive and summary statistics for the pain-related data. Results/Anticipated Results: “Controlled-tiered” data were easily accessible. Data completeness differed by variable type: variable categories (e.g., chronic pain) had fewer missing data than survey items used to calculate composite variables (e.g., GAD-7). The cohort comprised 146 Black adults aged 18–24 and 3,315 aged 25–44. We compared pain intensity, self-rated health, SDoH, and healthcare utilization by age. Limited EHR-recorded pain severity, and responses to disability and comorbidity survey items prevented comparisons by age. Program support for accessing the data met expectations. A quantitative PhD graduate student was needed to engage. Advanced coding skills required to use the cloud-based data portal challenges broad usability of the data and claims for inclusive use of this data resource. Discussion/Significance of Impact: AoU can be leveraged to examine key health indicators for large cohorts of underrepresented adults. However, the skill level and time required to fully engage with these data is beyond that of most early career investigators. We encourage CTSAs to coordinate capacity-building efforts to use these large population data and support a team science approach.