Simulation Modeling as a Decision Tool for Capacity Allocation in Breast Surgery

Abstract

Increased surgeon workload can result in prolonged access times for patients and may lead to surgeon burnout. Management of access times through investments in care capacity and hiring of providers require an understanding of the patient access times resulting from a given level of care capacity under different patient demand scenarios. We explore the effectiveness of a simulation-based framework in providing workforce planning insights. Our framework involves modeling of patient demand by considering different groups of surgical procedures, a simulation model that allows calibration of certain parameters through the use of data, and consideration of different demand and capacity scenarios to provide an understanding of the range of patient access times that can be expected over the immediate future during the time horizon. Our results show that such a simulation-based framework can help ground workforce planning and capacity investment decisions on operational data, and help healthcare institutions manage such costs.