Discrete-event simulation and scheduling for Mohs micrographic surgery

Patrick Burns, Sailesh Konda and Michelle Alvarado

Journal of Simulation, 2022, vol. 16, issue 1, 43-57

Abstract: Mohs Micrographic Surgery (MMS) is a layer-by-layer, skin-saving surgical method for excising skin cancer. The number of excised layers is stochastic, which creates operational challenges for the clinic. We develop a discrete-event simulation of a MMS surgical clinic to investigate how appointment schedules impact clinic operations. The model simulates the patient flow for a single day with physician, procedure rooms, and histotechnicians as limiting resources. The process times, rate of no-shows, and number of excised layers are stochastic model inputs. The value of the MMS simulation is demonstrated through analysis of five scheduling methods, thirteen schedule templates, and three performance measures: clinic throughput, patient waiting time, and clinic overtime. The results show that the number of patients scheduled changes the ideal spacing between appointments. MMS clinics can benefit from using this simulation model to explore new scheduling templates, especially when reduced patient waiting time and clinic overtime is a priority.

Date: 2022
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DOI: 10.1080/17477778.2020.1750315

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