GEOSPATIAL ANALYSIS OF THE PROPORTION OF PERSONS DEFINED AS UNDERREPRESENTED IN MEDICINE FOR EACH MEDICAL SCHOOL AND THEIR SURROUNDING CORE-BASED STATISTICAL AREA
Topics:
Keywords: Diversity, Medical School, underrepresented minority
Abstract Type: Lightning Paper Abstract
Authors:
Zoel Augusto Quiñónez, Stanford University
Angel Benitez-Melo, University of San Diego
Laura Margaret Diaz, University of California, Berkeley
Michael Lennig, Stanford University
Danton Char, Stanford University
Charlotte Smith, University of California, Berkeley
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Abstract
Purpose of Study: Current efforts to assess diversity in medicine exclude examination of how communities reflect their local populations, which is important considering literature demonstrating that patients are better served by physicians from a concordant community. Here we use the AAMC definition of Underrepresented in Medicine URIM to assess how individual institutions represent the historically underserved members of their surrounding community.
Methods Used: We used ArcGIS Pro v 3.0 (ESRI, Redlands, CA) for geospatial analysis and data representation. Using R [R Core Team, Vienna], we performed parametric tests of proportions and non-parametric Wilcoxon rank-sum tests where appropriate. Medical School demographics were obtained from the AAMC table 2021_FACTS_TABLE_B-5.2. Population data was collected from the USA Census 2020 Redistricting Core-Based Statistical Data layer.
Summary of Results: 80% of medical schools have a lower proportion of students defined as URiM that in their core-based statistical area, with 10.3% having a greater proportion. There is no difference in URiM students between institutions that have less URiMs than their core-based statistical area when compared to those that have more (20.0% vs. 37.8%, p = 0.197) or those that have numbers that are no different (20.0% vs. 23.5% p = 0.664).
Conclusions: Medical schools fail to train physicians that reflect the Black, Hispanic and Indigenous populations of their surrounding community. Those that reflect the URiM population do so due to a lower proportion of URiM individuals within the core-based statistical area rather than an increased enrollment of URiMs.
GEOSPATIAL ANALYSIS OF THE PROPORTION OF PERSONS DEFINED AS UNDERREPRESENTED IN MEDICINE FOR EACH MEDICAL SCHOOL AND THEIR SURROUNDING CORE-BASED STATISTICAL AREA
Category
Lightning Paper Abstract
