Michael Pinedo, Professor, Stern School of Business, New York University: Scheduling Operating Rooms with Elective and Emergency Surgeries


【Speaker】 Michael Pinedo, Professor, Stern School of Business, New York University

【Title】Scheduling Operating Rooms with Elective and Emergency Surgeries

【Time】Jan.3, Wednesday, 10:00-11:30

【Venue】Room 453, Weilun Building, Tsinghua SEM 

【Language 】English

【Organizer】Department of Management Science and Engineering


Abstract

Operating rooms (ORs) are the greatest source of revenues for hospitals, while also being their largest cost centers.   When scheduling surgeries, hospitals face a trade-off between the need to conduct scheduled elective surgeries as planned and the need to be responsive to emergency cases.   However, scheduling ORs, especially at level-1 trauma hospitals, is challenging due to the significant uncertainties in the arrivals of patients requiring emergent surgery. The issue of allocating limited capacity to emergent surgery cases while scheduling elective patients has major policy implications for Level-1 trauma centers including most large academic medical centers.

We develop  a  model  that allocates the OR capacity to elective  patients in such a way that the emergency patients who arrive randomly can be accommodated without incurring excessive delays. The objective is to develop a framework for aggregate weekly schedules and generate detailed daily schedules that minimize a weighted sum of the ORs' expected operating time, idle time, and overtime. Optimization procedures are developed to devise effective schedules while a rescheduling procedure adjusts the schedules of elective patients who are affected  by an emergency arrival. Initially, the procedures assume deterministic surgery times for the elective patients and then they are extended to include stochastic surgery times as well.  We apply our methodology to specialized ORs for trauma cases related to neurosurgery. We show that for a given arrival rate of emergency patients, the total expected cost is convex in the weekly load of elective surgeries scheduled. Numerical experiments are devised to obtain the total expected cost curves for various  arrival rates of emergency patients. Using these cost curves the optimal capacity allocation of ORs to elective patients can be determined  as a function of  the arrival rate of emergency patients.