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Discrete-Event Simulation Modeling in Healthcare: A Comprehensive Review
Jesús Isaac Vázquez-Serrano1, Rodrigo E Peimbert-García1,2, Leopoldo Eduardo Cárdenas-Barrón1
1School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64849, Northeast Nuevo Leon, Mexico.
International Journal of Environmental Research and Public Health
|November 27, 2021
Summary
Discrete-event simulation (DES) is increasingly used in healthcare for operational improvements. However, few studies implement DES models, highlighting a need for research on real-world impact and hybrid model frameworks.
Area of Science:
- Healthcare Systems Engineering
- Operations Research
- Simulation Modeling
Background:
- Discrete-event simulation (DES) is a key stochastic modeling technique for complex healthcare systems.
- A systematic review of 231 papers was conducted to analyze DES applications in healthcare.
Purpose of the Study:
- To review and categorize existing research on DES in healthcare.
- To identify trends, common methodologies, and areas for future research in healthcare DES.
Main Methods:
- Systematic literature search of academic databases.
- Categorization of 231 identified papers by year, approach, setting, outcome, provenance, and software.
- Analysis of theoretical studies, reviews, and case studies.
Main Results:
- DES is often combined with optimization and lean/six sigma techniques.
- Emergency departments are the most frequent setting, with a focus on time and efficiency improvements.
- Arena and Simul8 are the most popular DES software; less than 10% of studies report actual implementation.
Conclusions:
- There is a growing trend in using DES for operational healthcare issues.
- Future research should prioritize the implementation of DES models to evaluate their impact on processes and patient outcomes.
- Further work is needed on methodological formulation and hybrid model frameworks.
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