135 Representativeness of a national research network: Findings from PCORnet®

Objectives/Goals: We aimed to evaluate the representativeness of the patient population that is accessible through PCORnet®, both at the network level and within individual studies that enroll patients using the network, and to develop concrete recommendations regarding the design and evaluation of future studies. Methods/Study Population: We evaluated potential study participants that could be recruited through PCORnet, defined as patients with a healthcare encounter and any diagnosis recorded at a participating network site in 2023, relative to US population data from the American Community Survey (ACS) with respect to demographic, geographic, and socioeconomic summary data. Individual studies, conducted using the network, rarely involve all PCORnet patients, but rather those who meet clinical eligibility criteria and pass through a series of operational filters, such as site selection. We evaluated all patients at sites that have participated in at least 10 studies, as well as individual studies published in the COVID-19 clinical domain, compared to corresponding, eligible patients across the entire network. Results/Anticipated Results: PCORnet included data from over 47 million people across the USA with everyday healthcare encounters in 2023. This population of potential study participants was generally representative of the US population, though less likely to be from rural communities (11.7% vs. 18.4%) and low socioeconomic status (SES) (18.9% vs 25%). Patients from sites that frequently participate in PCORnet studies (10+) were representative of PCORnet overall, with an opportunity to improve inclusion of Hispanic populations. Among individual studies in the COVID-19 clinical domain, retrospective studies were largely representative, but prospective studies demonstrated large gaps in representation. Discussion/Significance of Impact: PCORnet provides access to a representative population of patients receiving healthcare. Differences in SES and rurality may be explained by differences in healthcare access. Population-level data, available through PCORnet, can be used to improve study design and evaluation, particularly for prospective studies.