Mp34-17 Considering the Uncounted: Characteristics of Us Counties Included vs. Not Included in Seer

You have accessJournal of UrologyDiversity, Equity & Inclusion: Health Equity & Outcomes II (MP34)1 May 2024MP34-17 CONSIDERING THE UNCOUNTED: CHARACTERISTICS OF US COUNTIES INCLUDED VS. NOT INCLUDED IN SEER Avery E. Braun, Lufan Wang, Samuel L. Washington, and Matthew R. Cooperberg Avery E. BraunAvery E. Braun , Lufan WangLufan Wang , Samuel L. WashingtonSamuel L. Washington , and Matthew R. CooperbergMatthew R. Cooperberg View All Author Informationhttps://doi.org/10.1097/01.JU.0001008876.78012.90.17AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: We sought to assess the representativeness of SEER on social determinants of health (SDOH) factors with emerging impacts on equitable care delivery and outcomes. METHODS: We queried Area Health Resource Files (AHRF) for nationwide county-level information including SEER status and SDOH domains: social context, neighborhood environment, education access/quality, healthcare access/quality and economic stability. We performed Chi-square/Wilcoxon tests to compare characteristics by SEER status. RESULTS: Out of all US counties, 1114 (34.6%) were SEER and 2107 (65.4%) were non-SEER (Table 1). The racial composition per 100k in Black, Hispanic, and Asian subgroups for men and women were different by SEER status (all p<0.01). Non-SEER sites compromised more rural (17% vs 22%, p<0.001), while SEER more urban areas (46% vs 41%, p<0.01). SEER comprised a higher percentage of foreign-born residents (7% vs 4%, p<0.01) and uninsured individuals<65 (26% vs 6%, p<0.01). SEER counties had higher composition of low employment (31% vs 28%, p=0.03) and persistent poverty (15% vs 9%, p<0.01) statuses and unemployment rates (4.2% vs 4.1%, p<0.01). Low education typology (23% vs 10%, p<0.001) was higher in SEER counties. Per 100k, SEER regions had larger portion of individuals without 4+ years of college education (<15K: 34% vs 28%, p<0.01) but only white individuals >25 years old were more likely to have less than a high school diploma (13% vs 11%, p<0.01) compared to Black (p=0.22) or Asian (p=0.08). SEER regions had higher median home value (p<0.01) and gross rent (p<0.01). However, SEER had more Black and white households per 100k with <$10,000 income (both p<0.01) and more individuals utilizing SNAP/Food stamps (p<0.01). Fewer non-SEER areas per 100k had >100 primary care providers (7% vs 10%, p<0.01), hospitals with >600 beds (9% vs 14%, p<0.01) or ancillary hospital services (hospice 79% vs 83%; indigent care 83% vs 89%; violence prevention 89% vs 92%; all p<0.01). CONCLUSIONS: Our analysis evaluating representativeness of SEER by SDOH indices from AHRF indicates important and under-reported differences. To better understand the influence of SDOH on our patients, we need to intentionally integrate variables associated with disparities in healthcare receipt and outcomes into work with nationwide databases. Source of Funding: None © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e577 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Avery E. Braun More articles by this author Lufan Wang More articles by this author Samuel L. Washington More articles by this author Matthew R. Cooperberg More articles by this author Expand All Advertisement PDF downloadLoading ...