A Data-Driven Decision Making Model for Managing Surgical Instruments in Hospitals

In order to perform a surgical procedure, surgeons need to have easy access to substantial numbers of sterile instruments through surgical trays and peel packs. After the procedure, all instruments in the opened containers, regardless of whether they have been used or not, must undergo the labor-intensive process of resterilization. Empirical studies have shown that the utilization rate of instruments within trays is very low. The purpose of this study is to analyze how surgical trays should be configured based on the likelihood of instruments being used. The problem is constructed upon an integer non-linear programming model. A decomposition-based heuristic and metaheuristic methods coupled with two novel local search algorithms are developed to solve the problem. The application of the model is illustrated through a case study. We also discuss how hospitals could benefit from our model for reducing the cost associated with unnecessary tray opening before the procedure