Healthcare Analytics (Nov 2022)
Multi-criteria surgery scheduling optimization using modeling, heuristics, and simulation
Abstract
This paper seeks to model and solve a surgery scheduling problem in hospitals subject to a constraint that surgeries can only be started at or after the scheduled start time, and to evaluate the effects of proposed changes to improve operating room (OR) efficiency and utilization using a Monte Carlo simulation approach. The surgery scheduling problem is to assign surgeries to ORs and assign surgery start times so as to minimize the sum of idle times of ORs and late start times for surgeries. Employing historical data provided by a large university hospital, this research provides a mathematical formulation for the problem, proposes a series of heuristics, and develops a Monte Carlo simulation model for planned surgeries to minimize the penalty. Our research demonstrates that the changes proposed can shorten the delayed start duration for surgeries and the idle times for ORs. The results can be helpful to the decision makers in hospital settings who are considering minimizing delays in surgeries start times and ORs idle times while dealing with the stochastic nature of surgery times.