Optimizing operating room scheduling considering instrument sterilization processing

Abstract

The United States healthcare system represents approximately 18% of the nation's GDP and its numerous challenges continue to receive significant attention from researchers. Within healthcare, operating rooms (ORs) often represent the largest source of revenue and costs in a hospital. Consequently, OR surgical scheduling strategies have been thoroughly examined from a wide variety of performance measures such as overtime, patient waiting time, and utilization rates. ORs are a complex system, and researchers have begun to consider the upstream and downstream resources involved in the surgical process such as the Post Anesthesia Care Unit, Intensive Care Unit, and bed availability. However, two factors that have only begun to be examined are the sterilization process of OR instrumentation and the assignment of instruments into trays and preference cards, either by surgical procedure or individual surgeon preference. Using both collected and historical data, this research 1) examined and improved how the block schedule of an OR suite affected the Sterilization Processing Department (SPD) and 2) examined and improved preference cards for surgical cases. A series of mathematical models optimized surgical block schedules while considering the impact on the SPD and a goal programming model was developed for the tray optimization problem. A comprehensive simulation model of the OR suite and SPD tested the output of the mathematical models. The simulation results confirmed block scheduling does affect SPD performance. A linear goal programming formulation that smoothed SPD workload across block times was the most effective type of model to optimize block scheduling. A goal programming tray optimization model improved expected instrument utilization rates. For practical applications, this research suggests reducing SPD staff turnover is a more effective method for improving SPD performance than rearranging the OR block schedule. This research is among the first of its kind to consider SPD workload as an objective in OR block scheduling models, to consider expected instrument non-usage rates in the tray optimization problem, and to develop a comprehensive simulation model of an OR suite and its SPD to test the results of mathematical models.