Blue, A.V., Gilbert, G.E., Elam, C.L., & Basco, W.T., Jr. (2000). Does Institutional Selectivity Aid in the Prediction of Medical School Performance? Academic Medicine, 75, S31-S33.

PURPOSE: Institutional validity studies of admission decision-making data help to determine which characteristics should be accorded highest importance in applicant selection. Given the reliance upon institutional selectivity as an important admission characteristic and the different types of selectivity classifications available for medical schools to use, the purpose of this study was to examine how well three measures of institutional selectivity could predict medical students' performances, specifically their performances on the USMLE Step 1 and Step 2 and their final medical school GPAs.

METHODS: Admission and medical school performance data were obtained for the 199201995 matriculants at the study institution, the Medical University of South Carolina (MUSC). Admission data for each student consisted of his or her MCAT scores, undergraduate GPA, undergraduate institution, three institutional selectivity categorization indices (the 1983 HERI Index, Barron's Admissions Selector Rating, and the Carnegie Classification), age, gender, and underrepresented minority (URM) status. Medical school performance data consisted of USMLE Step 1 and 2 scores and final GPA. Students admitted under the institution's existing Early Assurance Program (EAP) were excluded from analysis because an MCAT score was not required for their admission. Descriptive statistics were performed for all variables. Stepwise linear regression (adjusted R-square method) was used to assess which control variables (undergraduate GPA, gender, URM status, age) contributed significantly to predicting USMLE Step 1 and 2 scores and final GPA. Age was the only control variable that did not contribute significantly to predicting any of the dependent variables. Multiple linear regression was then performed with each of the institutional selectivity or categorization indices, controlling for URM status and gender. The powers of the multiple regression equations ranged from 88.2% to 96.0% for an alpha of 0.05 and with estimating of small effect sizes.

RESULTS: All models predicted statistically significant variations in the dependent variables. Uniformly, the worst-fitting model was that which consisted of only the three control variables GPA, gender, and URM status. The amounts of explained variation ranged from 17% to 32%. Addition to the model of any institutional selectivity index or categorization slightly improved prediction (as measured by proportion of variance explained) above the prediction provided with GPA and demographic characteristics alone. When the MCAT score was added to the model involving the control variables and the GPA, it improved predictive ability of the equation by 6-13%. The addition of the institutional selectivity indices or categorization after the MCAT score was in the model added nothing to the predictive ability. Control variables plus MCAT score accounted for 38% of the variation in USMLE Step 1 scores, 38% of the variation in final GPA, and 28% of the variation in USMLE Step 2 scores.

CONCLUSIONS: Our results show that none of the three institutional selectivity indices or categorizations and any GPA adjustment that would follow will improve correlations with performances on USMLE Step 1 and Step 2 and final GPA if MCAT scores and unadjusted GPA are used in conjunction. Our findings suggest that using institutional selectivity indices or categorizations as an admission characteristic may not be necessary. In addition, use of institutional selectivity indices or categorizations may discriminate against applicants with other desirable characteristics who have been granted degrees from less selective undergraduate institutions. Our results reassure admissions officers that the performances of students who attend smaller undergraduate institutions or community colleges are predictable when using their MCAT scores and undergraduate GPAs. In summary, our results indicate that the characteristics of the degree-granting undergraduate institution, as measured by three different types of institutional selectivity or categorization, do not add to the ability to predict performances on USMLE Steps 1 and 2 and overall medical school GPA if the MCAT score and unadjusted undergraduate GPA are available. The result also further support the predictive validity of the scores on the MCAT examination for medical school performance.

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