Medical student selection process enhanced by improving selection algorithms and changing the focus of interviews in Australia: a descriptive study

Journal of educational evaluation for health professions(2022)

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摘要
PURPOSE:The study investigates the efficacy of new features introduced to the selection process for medical school at the University of New South Wales, Australia: (1) considering the relative ranks rather than scores of the Undergraduate Medicine and Health Sciences Admission Test and Australian Tertiary Admission Rank; (2) structured interview focusing on interpersonal interaction and concerns should the applicants become students; and (3) embracing interviewers’ diverse perspectives. METHODS:Data from 5 cohorts of students were analyzed, comparing outcomes of the second year in the medicine program of 4 cohorts of the old selection process and 1 of the new process. The main analysis comprised multiple linear regression models for predicting academic, clinical, and professional outcomes, by section tools and demographic variables. RESULTS:Selection interview marks from the new interview (512 applicants, 2 interviewers each) were analyzed for inter-rater reliability, which identified a high level of agreement (kappa=0.639). No such analysis was possible for the old interview since it required interviewers to reach a consensus. Multivariate linear regression models utilizing outcomes for 5 cohorts (N=905) revealed that the new selection process was much more effective in predicting academic and clinical achievement in the program (R2=9.4%–17.8% vs. R2=1.5%–8.4%). CONCLUSION:The results suggest that the medical student selection process can be significantly enhanced by employing a non-compensatory selection algorithm; and using a structured interview focusing on interpersonal interaction and concerns should the applicants become students; as well as embracing interviewers’ diverse perspectives.
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关键词
Algorithms,Consensus,Linear models,Medical schools,School admission criteria
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