A dual bin-packing approach to scheduling surgical cases at a publicly-funded hospital

Abstract

Publicly-funded hospitals are typically allocated an annual budget by the government based on the number of enrollees in the region. Given tight budget constraints, the capacity of resources is fairly fixed. Such hospitals strive to maximize the utilization of their resources through continuous improvement and optimization techniques. We address a surgical case scheduling problem experienced at a publicly-funded hospital and conceptualize this multi-period, multi-resource, priority-based case scheduling problem as an unequal-sized, multi-bin, multi-dimensional dual bin-packing problem. A mixed integer programming model and a heuristic based on the first fit decreasing algorithm are presented. Resource availability, case priorities, and variation in surgery times are key features included in our model. Our proposed approach led to substantial savings, 20% reduction in number of days and up to 20% increase in operating room utilization, when compared to real schedules obtained from the surgical department at a publicly-funded hospital.