Ontario Medical School Outcomes Research Collaborative

At the foundation of effective medical education big data scholarship is data sharing between institutions across the trajectory of training. This project is a data sharing collaboration with the six undergraduate medical programs in Ontario, the Medical Council of Canada (MCC), and the Canadian Residency Matching Service (CaRMS), to consider associations between admissions and assessment variables and performance on the MCC Qualifying Examination Part 1(MCCQE1) – a first step to licensing for physicians in Canada. At this stage, data for learners from the 6 medical schools who wrote MCCQE1 between 2015 and 2017 have been analyzed (n= 2668). With MCCQE1 scores as an outcome, a stepwise hierarchical model was used with five steps of predictor variables (learner demographic characteristics, admissions variables, pre-clinical training assessments, OSCE performance, clinical training assessments). Across the schools, the determination of best models differed by step of predictor variable. The FSG Medical Education Research Lab, led by Lawrence Grierson, is writing the results into two manuscripts for consideration as peer-reviewed publications. These papers will emphasize how data sharing collaborations can reveal variation between education programs while offering an opportunity for learning from each other.