Evaluating diversity in neurosurgery through the use of a multidimensional statistical model: a pilot study

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  • 1 Department of Psychiatry, University of Vermont, Burlington, Vermont;
  • | 2 School of Medicine, Case Western Reserve University, Cleveland, Ohio;
  • | 3 Larner College of Medicine, University of Vermont;
  • | 4 Department of Biostatistics, University of Vermont, Burlington, Vermont; and
  • | 5 Department of Neurosurgery, Cleveland Clinic, Cleveland, Ohio
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OBJECTIVE

There is a growing body of evidence demonstrating the benefits of diversity across many domains. However, neurosurgery consistently lags most of medicine in many aspects of diversity. Any inability to make progress in this arena is likely due to the multifactorial and complex nature of the issue, which makes it difficult to meaningfully measure and track diversity within the workforce. The goal of this pilot study was to assess the utilization of a multidimensional statistical model to quantify and assess diversity within neurosurgery. The authors sought to 1) assess the diversity of neurosurgery residents using Simpson’s Diversity Index and Sullivan’s Composite Diversity Index (CDI) and 2) determine if a medical school’s intrinsic academic opportunities and resources, indicated by US News & World Report’s (USNWR’s) best research medical schools ranking, are related to the number of neurosurgery residents produced per medical school.

METHODS

A cross-sectional study of all neurosurgery residents (projected graduation years 2020–2026) and 1st-year medical students (matriculating years 2016–2019) was undertaken. Biographical diversity data (gender and matriculation data) were collected from institutional websites between December 2019 and June 2020. The CDI expresses the diversity of a given population by representing the effective proportion of categories present across all diversity attributes and was calculated for neurosurgery residents and medical students. Statistical results are reported as the median and interquartile range.

RESULTS

Neurosurgery residency program CDI (0.21, IQR 0.16–0.25) was significantly less (p < 0.001) than medical school CDI (0.42, 0.37–0.48). There was no significant difference in CDI between top-40 and non–top 40 Doximity ranked research output neurosurgery residency programs (p = 0.35) or between top-40 and non–top 40 USNWR ranked research medical schools (p = 0.11). Over a 7-year period, top-40 ranked research medical schools produced significantly more (p < 0.001) neurosurgery residents (11.9, IQR 7.1–18.9) than the non–top 40 ranked research medical schools (5.6, IQR 2.6–8.5).

CONCLUSIONS

The authors demonstrated the feasibility of using a multidimensional statistical model as a measure to understand the complex issues of diversity. Their preliminary data suggested that neurosurgery’s challenge in achieving the desired diversity relates to uneven attraction and/or recruitment across an increasingly diverse medical student body. In recent years, neurosurgery has made great progress in the arena of diversity and has shown a strong desire to do more. Utilization of these diversity measures will help the neurosurgery field to monitor progress along this valuable journey.

ABBREVIATIONS

AAMC = American Association of Medical Colleges; CDI = Composite Diversity Index; MSAR = Medical Student Admissions Requirements; NRMP = National Resident Matching Program; USMLE = United States Medical Licensing Examination; USNWR = US News & World Report; WINS = Women in Neurosurgery.

Schematics of transseptal interforniceal resection of a superiorly recessed colloid cyst. ©Mark Souweidane, published with permission. See the article by Tosi et al. (pp 813–819).

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