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Discrete Event Simulation in R using the 'Simmer' Package for Health Economic Modelling: A Tutorial and Illustration
Koen Degeling1,2, Jonathan Karnon3, Michiel van de Ven4,5
1Cancer Health Services Research, Centre for Cancer Research and Centre for Health Policy, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Australia.
Applied Health Economics and Health Policy
|June 17, 2025
Summary
Discrete event simulation (DES) offers greater flexibility for health-economic modeling of complex pathways. This tutorial guides R users through implementing DES with the simmer package, simplifying its application.
Area of Science:
- Health economics
- Computational modeling
- Biostatistics
Background:
- Discrete event simulation (DES) is a flexible health-economic modeling technique for complex clinical pathways.
- DES can incorporate resource and capacity constraints, applicable to diverse research questions.
- DES is often perceived as more complex than traditional state-transition models.
Purpose of the Study:
- To provide a practical tutorial for implementing DES in R using the simmer package.
- To address the perceived complexity of DES for health-economic assessments.
- To guide users with conceptual models towards practical DES implementation.
Main Methods:
- Illustrates DES implementation in R with the open-source simmer package.
- Uses a colon cancer case study for practical demonstration.
- Covers methodological aspects, conceptual model structure, pseudocode, data analysis, and model analysis (deterministic and probabilistic).
Main Results:
- Provides documented R code with building blocks for various DES models.
- Offers practical guidance for implementing DES in health economics.
- Demonstrates the application of DES in a specific clinical context (colon cancer).
Conclusions:
- The tutorial simplifies DES implementation in R for health-economic research.
- The provided code and guidance facilitate the development of complex DES models.
- Empowers researchers to leverage DES for nuanced health-economic evaluations.
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