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End-to-end solution to maximizing efficiency of surgical care

Waitlists for orthopaedic surgery, particularly hip and knee replacement are growing. Significant resources are required to run an operating room, making it one of the most valuable departments for hospitals and health care systems. Therefore, as resources – both physical and human – are limited across the public system in Canada, efficient management is crucial to the timely delivery of care. Assigning a specific date, time, operating room, surgeon, nurses, recovery bed and ward bed quickly becomes a daunting task for administrators due to the large volumes of cases. Our research challenges the tradition of tackling the highly complex orthopaedic surgery scheduling tasks using solely manual approaches based on surgeons’ estimates of operative time. Instead, we aim to design a comprehensive solution that leverages patient data, case volumes and patient-specific operative times to optimize the scheduling process in an automated way. Machine learning and mathematical optimization methods will be developed to enable both accurate predictions of operative time and optimal scheduling. In addition to financial benefits, optimized schedules would decrease patient waitlist times by facilitating more surgeries within the same amount of operating room time.