Discrete-Event Simulation Tools Applied to the Healthcare Context

Purpose – Healthcare is a field of activity in which decisions have very complex characteristics and require various types of knowledge to be made in the most assertive way possible. Searching for tools to support decision-making has been recurrent and inevitable in this complex scenario, such as optimization methods and simulation techniques.
Design/methodology/approach – Optimization methods aim to find the optimal solutions to the problems under investigation, and simulation techniques allow these solutions to be tested before they are implemented, guaranteeing the quality of the results, and minimizing the consequences of wrong decisions, inefficient physical interventions, and unnecessary costs. This paper identifies the most widely used Discrete-Event Simulation tools reported in the literature over the last ten years, outlining their applications and identifying possible gaps for future research.
Findings – The main technical characteristics have been pointed out, such as the most common software, the factors that determine their choice and the most suitable software for the problem situations presented. Specific simulation characteristics are also presented, such as the number of replications, the type of simulation adopted, the methods used to validate the models and integration with optimization tools.
Originality/value – The results of this work can contribute to the development of specific tools with a focus on healthcare, to other research aimed at filling the gaps found, to an attempt to standardize actions for recurring problems, and to the construction of a f

Healthcare, Optimization, Discrete-Event Simulation, Decision Support Tools