Outcomes-Based Selection Into Medical School: Predicting Excellence in Multiple Competencies During the Clinical...

Medical school selection committees aim to identify the best possible students and, ultimately, the best future doctors from a large, well-qualified, generally homogeneous pool of applicants. Constructive alignment of medical school selection, curricula, and assessment with the ultimate outcomes (e.g., CanMEDS roles) has been proposed as means to attain this goal. Whether this approach is effective has not yet been established. The authors addressed this gap by assessing the relationship between performance in an outcomes-based selection procedure and performance during the clinical years of medical school.

Two groups of students were compared: (1) those admitted into Maastricht University Medical School via an outcomes-based selection procedure and (2) those rejected through this procedure who were admitted into the program through a national, grade-point-average-based lottery. The authors compared performance scores of students from the 2 groups on all 7 CanMEDS roles, using assessment data gathered during clinical rotations. The authors examined data from 3 cohorts (2011-2013).

Students admitted through the local, outcomes-based selection procedure significantly outperformed the initially rejected but lottery-admitted students in all years, and the differences between groups increased over time. The selected students performed significantly better in the CanMEDS roles of Communicator, Collaborator, and Professional in the first year of clinical rotations; in these 3 roles-plus Organizer-in the second year; and in 2 additional roles (Advocate and Scholar-all except Medical Expert) at the end of their clinical training.

A constructively aligned selection procedure has increasing predictive value across the clinical years of medical school compared with a GPA-based lottery procedure. The data reported here suggest that constructive alignment of selection, curricula, and assessment to ultimate outcomes is effective in creating a selection procedure predictive of clinical performance.