Impact of Masking Academic Metrics on Enrolling a Broadly Diverse and Mission-Aligned Student Body.

Abstract

The June 2023 U.S. Supreme Court decision overturning affirmative action required medical schools to discontinue considering race/ethnicity in admissions decisions. Medical schools must now identify different strategies if they aim to recruit and admit applicants from groups underrepresented in medicine (URiM; race/ethnicity), as enrolling broadly diverse students remains critical for serving the U.S. population. Washington State University Elson S. Floyd College of Medicine (established in 2015) has an admissions process that assesses academic metrics using national threshold combinations of undergraduate grade point averages (UGPAs) and Medical College Admission Test (MCAT) scores (published on school's website), and legal residency in or ties to Washington state, as prescreening criteria for secondary applications. UGPAs and MCAT scores are then masked from further consideration, allowing for decisions to be made with a focus on mission-aligned criteria, such as certain personal attributes and lived experiences and coming from specific environments (i.e., educationally or socioeconomically disadvantaged backgrounds, rural communities, military service, or a member of a federally recognized Tribe). In the last 5 admissions cycles (enrollment years 2018-2022), cohort data demonstrates that as the admissions funnel narrows and each subsequent pool is smaller than the preceding one, the representation of mission-aligned applicants increases, despite the masking of academic metrics. The most recently enrolled class (enrollment year 2022) of 80 had 14 (17.5%) URiM students, closely mirroring the state's general population. The overall yield (acceptance:matriculation) has steadily improved with the last 2 cycles to 1.68:1 and 1.65:1, indicating slightly more than 1.5 times the number of offers needed to fill the class are being made. Next steps include further refining the process by considering more granular data on applicants' childhood community characteristics and rural background and examining how admissions data may correlate with residency and practice location and communities served.