Predicting Academic Career Placement via Development of Novel Intra-residency Metrics

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Abstract

Objective: Increasing centralization of high-level neurosurgical practice at academic centers has increased the need for academic neurosurgeons. The lack of systematic metrics-based analyses among neurosurgery trainees and the recent pass/fail U.S. Medical Licensing Examination system necessitates a multiparametric approach to assess academic success among trainees. Methods: We conducted a comprehensive analysis of the University of Miami residency program using 2 data sets, one containing applicants' pre-residency metrics and a second containing trainees' intra-residency metrics. Intra-residency metrics were subjectively and anonymously assessed by faculty. Univariate and multivariate logistic regression analyses were performed to determine differences among academic and non-academic neurosurgeons and identify predictors of academic careers. Results: Academic neurosurgeons had a significantly higher median Step 1 percentile relative to non-academic neurosurgeons (P = 0.015), and medical school ranking had no significant impact on career (P > 0.05). Among intra-residency metrics, academic neurosurgeons demonstrated higher mean rating of leadership skills (mean difference [MD] 0.46, P = 0.0011), technical skill (MD 0.42, P = 0.006), and other intra-residency metrics. Higher administrative and leadership skills were significantly associated with increased likelihood of pursuing an academic career (odds ratio [OR] 9.03, 95% CI [2.296 to 49.88], P = 0.0044). Clinical judgment and clinical knowledge were strongly associated with pursuit of an academic career (OR 9.33 and OR 9.32, respectively, with P = 0.0060 and P = 0.0010, respectively). Conclusions: Pre-residency metrics had little predictive value in determining academic careers. Furthermore, medical school ranking does not play a significant role in determining a career in academic neurosurgery. Intra-residency judgment appears to play a significant role in career placement, as academic neurosurgeons were rated consistently higher than their non-academic peers in multiple key parameters by their attending physicians.

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Govindarajan, V., Shah, A. H., Morell, A. A., Borowy, V., Ingle, S. M., Mendez Valdez, M. J., … Levi, A. D. (2023). Predicting Academic Career Placement via Development of Novel Intra-residency Metrics. World Neurosurgery, 174, e35–e43. https://doi.org/10.1016/j.wneu.2023.02.080

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