Discrete Event Simulation for Prediction of Patient Flow and Capacity in HollandPTC

Master thesis (2021)

Authors

J. Eijkenduijn Mechanical Engineering

Contributors

Yvonne Klaver HollandPTC (mentor)
Mischa Hoogeman Erasmus MC (mentor)
Faculty
Mechanical Engineering
Copyright: © 2021 Joep Eijkenduijn
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Published Date

20-09-2021

Language

English

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Faculty

Mechanical Engineering

Abstract

AimTreatment with Proton Beam Therapy (PBT) is highly complex due to a variety of activities integrated into the workflow to ensure treatment quality and patient safety. The effects of changes to the workflow with the intend to scale up a PBT facility are therefore hard to predict. The purpose of this study was to develop a forecasting simulation-based application which could predict the effects of systematic optimisation of the healthcare processes within a PBT facility.
Methods
A Discrete Event Simulation application was developed which modelled the entire workflow of a PBT facility. The simulation was validated using real-world historical data. Scenarios were simulated according to a waterfall approach to predict potential capacity bottlenecks. A list of recommended modifications to the current processes was developed which can be used as guidelines towards a systemic increase in capacity.
Results
The first simulated scenario extrapolated the patient distribution of 2020 to match a target of 600 patients treated. A total number of 475.8±12.67 patients were simulated to be treated. The capacity bottlenecks were caused by retention of the planning resources. The second scenario simulated 556.3±11.97 treated patients. The capacity bottlenecks were caused by too little availability of radiation oncologists. The third scenario simulated 588.3±4.26 patients. The capacity bottlenecks were caused by too little availability of the gantries. The fourth scenario simulated the target: 601.4±7.72 patients.
Conclusion
In this project, we employed a validated DES simulation to model the in-house workflow of HollandPTC and to make predictions on capacity, throughput, patient flow, and availability of resources. The developed simulation is expected to be applicable to other PBT facilities around the world. The extent to which the simulation is applicable should be further explored.