744 Reducing Implicit Bias in the Neurosurgery Application and Interview Process

Abstract

INTRODUCTION: Each year, Neurosurgery residency programs aim to match the best and brightest applicants aspiring to join the field. Traditionally, metrics such as USMLE Step 1 and 2 scores, publications, and medical school grades have played a key role in determining who is interviewed, the interviewers’ impression of the candidates, and subsequently who is most likely to match. However, these evaluative tools are known to reflect biases in the medical and medical education systems, potentially overlooking diverse applicants well-suited for a career in neurosurgery. METHODS: During the 2020-2021 and 2021-2022 residency application cycles, our program instituted a new process for reviewing applications, conducting interviews, and generating a final rank list. Each application was reviewed by attending and resident reviewers, who were blinded to potentially biasing information including pictures and board scores. From this review, selected applicants were interviewed using a set of standardized questions, designed to evaluate specific domains essential for success in neurosurgery. Linear regression was performed to determine correlation between traditional metrics and domain-based interview scores and final rank. RESULTS: 137 applicants were interviewed. There was no significant correlation between rank and Step 1 (p = 0.47, R2 = 0.003) or Step 2 scores (p = 0.16, R2 = 0.014).Interview scores lacked statistically significant association with Step 1 scores (p=0.10, R2=.02), but were found to correlate with Step 2 scores (p = 0.02, R2 = .05). CONCLUSIONS: In our two-cycle experience using this new system, we found no correlation between applicants’ Step 1 scores and their interview scores or final rank list position. We propose this as one alternative method to historically biased tools for evaluating neurosurgery applicants.