OBJECTIVES: The purpose of this study was to use meta-analysis to establish which of the information available to the resident selection committee is associated with resident or doctor performance. METHODS: Multiple electronic databases were searched to 4 September 2012. Two reviewers independently selected studies that met the present inclusion criteria and extracted data in duplicate; disagreement was resolved by consensus. Risk for bias was assessed using a customised bias assessment tool. Measures of association were converted to a common effect size (Hedges' g). Meta-analysis was performed using the random-effects model for each selection strategy and all outcomes without pooling. Sensitivity analysis for each selection strategy-outcome pair was performed with pooling of effect size. RESULTS: Eighty studies involving a total of 41 704 participants were included in the meta-analysis. Seventeen different selection strategies and 17 outcomes were assessed across these studies. The strongest positive associations referred to examination-based selection strategies, such as the US Medical Licensing Examination (USMLE) Step 1, and examination-based outcomes, such as scores on in-training examinations. Moderate positive associations were present for medical school marks and both examination-based and subjective outcomes. Minimal or no associations were seen for the selection tools represented by interviews, reference letters and deans' letters. CONCLUSIONS: Standardised examination performance and medical school grades show the strongest associations with current measures of doctor performance. Deans' letters, reference letters and interviews all show a lower than expected strength of association given the relative value often assigned to them during resident doctor selection. Objective selection strategies are potentially the most useful to residency selection committees based on current evaluative methods. However, reports in the literature of validated long-term doctor performance outcomes are scant.
OBJECTIVES: The purpose of this study was to use meta-analysis to establish which of the information available to the resident selection committee is associated with resident or doctor performance. METHODS: Multiple electronic databases were searched to 4 September 2012. Two reviewers independently selected studies that met the present inclusion criteria and extracted data in duplicate; disagreement was resolved by consensus. Risk for bias was assessed using a customised bias assessment tool. Measures of association were converted to a common effect size (Hedges' g). Meta-analysis was performed using the random-effects model for each selection strategy and all outcomes without pooling. Sensitivity analysis for each selection strategy-outcome pair was performed with pooling of effect size. RESULTS: Eighty studies involving a total of 41 704 participants were included in the meta-analysis. Seventeen different selection strategies and 17 outcomes were assessed across these studies. The strongest positive associations referred to examination-based selection strategies, such as the US Medical Licensing Examination (USMLE) Step 1, and examination-based outcomes, such as scores on in-training examinations. Moderate positive associations were present for medical school marks and both examination-based and subjective outcomes. Minimal or no associations were seen for the selection tools represented by interviews, reference letters and deans' letters. CONCLUSIONS: Standardised examination performance and medical school grades show the strongest associations with current measures of doctor performance. Deans' letters, reference letters and interviews all show a lower than expected strength of association given the relative value often assigned to them during resident doctor selection. Objective selection strategies are potentially the most useful to residency selection committees based on current evaluative methods. However, reports in the literature of validated long-term doctor performance outcomes are scant.
Authors: Travis H Markham; Johanna B de Haan; Sara Guzman-Reyes; John F Zaki; Semhar J Ghebremichael; Carlos Artime; Evan G Pivalizza Journal: J Educ Perioper Med Date: 2020-07-01
Authors: Laura R Hopson; Michele L Dorfsman; Jeremy Branzetti; Michael A Gisondi; Danielle Hart; Jaime Jordan; James A Cranford; Sarah R Williams; Linda Regan Journal: AEM Educ Train Date: 2019-05-20