For years a client used data aggregated in ProgressIQ to create a prediction model of how competitive students are for each residency specialty, based on previous match data for that college. The results are displayed as a dashboard called the “Residency Advisor” for each student within ProgressIQ. (See related use case on Residency Advisor.) Each specialty is color-coded “green”, “yellow”, or “red”, for each student, depending on the likelihood of matching to each, respective program. The Residency Advisor is available to medical students as early as six weeks from the start of medical school, and updated continuously throughout their academic journey. This early warning dashboard is unique relative to tools made available by national organizations, as it is based on data specific to that medical school and gives students ample time to “course correct” during their studies leading to the match.
The underlying mathematical model was used by a particular client for years. Then Student Dr. L contacted ProgressIQ with a hypothesis that the model was reaching too far back in time; painting too rosy a picture for students targeting competitive specialties. Student Dr. L worked with ProgressIQ to analyze, test, and rework newer algorithms, so that the prediction model is more conservative and an even better gauge of competitiveness. ProgressIQ encouraged Student Dr. L to write up her work. She was accepted for a poster presentation at the American Association of Colleges of Osteopathic Medicine’s national conference, with ProgressIQ covering her registration and travel costs.
Student Dr. L is now Dr. L, and – we are happy to report – matched to her first choice.