Submission ID 93820
Poster Code | HR-P-53 |
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Title of Abstract | Residency matches with couples: are we leaving something on the table? |
Abstract Submission | The residency match is one of the most important steps in a clinician-in-training's career. The Canadian Residency Matching Service (CaRMS) and other residency matches around the world allow for graduates to apply to residency as pairs or couples. While this is desirable for participants of the match for obvious personal reasons, it introduces several computational issues into the matching algorithm. The residency match is an instance of the stable matchings problem, a well-known problem studied in mathematics, economics, and computer science. The goal is to find a stable matching, which is roughly a matching that respects participants' preferences. It can be shown theoretically that a stable matching always exists, and there is a simple algorithm to find it, which is currently in use around the world. However, when incorporating couples, it is known that a stable matching may not exist, and even if it does, it is not guaranteed to be found by the typical algorithm. Recent work has shown that reformulating the matching with couples problem as an instance of the Boolean satisfiability (SAT) problem, one of the most famous problems in computer science, and using general SAT solving algorithms, recovers many of the desirable properties from the no-couples setting. I review and compare these two approaches and argue that there are significant welfare benefits to match participants in switching to SAT algorithms, while explainability may suffer. |
Please indicate who nominated you | Kendra Hawke (University of Toronto) |
What Canadian Institutes of Health Research (CIHR) institute is your research most closely aligned? | Health Services and Policy Research |
What Canadian Institutes of Health Research (CIHR) pillar of health research does your research fall under? | Health systems services |
PDF of abstract | No file |
Presenter and Author(s) | Muhammad Maaz Muhammad Maaz |