Application of Simulation in Healthcare Service Operations

Abstract

The health system is intricate due to its dynamic nature and critical service requirements. The involvement of multiple layers of health service providers quadrupled this complexity and results in a complicated operating environment. Simulation is often considered an apt technique to model and study complex systems in the literature. The popularity of simulation in the healthcare domain had only accelerated with time and resulted in a large number of articles intended to solve myriad healthcare problems. This article analyzes healthcare simulation literature of the past decade (2007--2016) that addresses operations management issues in various healthcare service delivery levels and categorizes the literature accordingly. In the next step, we attempt to assimilate the entire literature to capture specific health issues addressed, operations management concepts applied, and simulation methods used, and identify major research gaps. Finally, we develop the research agenda from dividing these gaps into the contextual, conceptual, and methodological genre that is consistent with the previous state-of-the-art literature reviews in operations management. Furthermore, this article demonstrates other minute aspects such as “sources of funding” and “tools used for the research” to maintain coherence with the previous reviews in the healthcare simulation. The objective of this work is twofold: to connect the knowledge continuum to the present, and to provide potential research directions for future academicians.

Simulation modeling to assess performance of integrated healthcare systems: Literature review to characterize the field and visual aid to guide model selection

“…Simulation modeling (SM) is a discipline with the features necessary to implement systems thinking when assessing performance of a health system [ 14 , 16 , 17 ]. A simulation is a virtual recreation of a real system.…”

“…Meanwhile, the paper by Günal & Pidd [ 19 ] starts by narrating the historic progression of simulation modeling an its applications in healthcare, giving some idea of the long history of the field. Most recently (2021), Roy et al [ 17 ] analyzed healthcare simulation literature of the past decade, addressing issues in various healthcare service delivery levels and categorizing the literature accordingly. Altogether, literature in the field provides a comprehensive characterization of simulation models in healthcare, including; the areas and types of application where the discipline has been used, the techniques available, data sources, simulation software [ 18 , 20 , 21 ], type of outputs and level of insight, inputs and resources required [ 22 ], relative frequency of use and level of implementation [ 23 ] and specific aspects of a care facility operations where techniques are most common [ 17 , 24 , 25 ].…”

“…Most recently (2021), Roy et al [ 17 ] analyzed healthcare simulation literature of the past decade, addressing issues in various healthcare service delivery levels and categorizing the literature accordingly. Altogether, literature in the field provides a comprehensive characterization of simulation models in healthcare, including; the areas and types of application where the discipline has been used, the techniques available, data sources, simulation software [ 18 , 20 , 21 ], type of outputs and level of insight, inputs and resources required [ 22 ], relative frequency of use and level of implementation [ 23 ] and specific aspects of a care facility operations where techniques are most common [ 17 , 24 , 25 ]. These topics are most commonly analyzed following a structure similar to the one best represented by Mielczarek et al [ 25 ], who creates a system of classification of health care topic areas assessed with simulation methods.…”

“…While authors add innovations to this common structure, such as the identification of research gaps influencing the limited uptake of the discipline [ 20 , 23 , 24 , 26 ] or exploring the link between interventions and key performance indicators (KPI) [ 26 ], complexities in the relationships of system components have been heavily underassessed. Roy [ 17 ] recognizes the complexity of the health system and the ability of simulation modeling to address this complexity, but his review focuses on capturing specific health issues addressed, operations management concepts applied, simulation methods used, and identifying major research gaps—a framework similar to the one by Mielczarek et al [ 25 ]. Vanbrabant et al [ 26 ] also acknowledges simulations as the technique most suitable to capture the randomness and complexity of patient flow through the emergency department.…”

“…However, it fails on providing a common framework to characterize and contrast the complexities that can be represented in each technique. Complexity is also indirectly mentioned in identified research gaps, when both Vanbrand et al and Yousefi et al [ 20 ] state the underuse of simulation models in multi-objective evaluations and Brailsford et al and Roy et al [ 17 , 24 ] suggests that healthcare is an area of application for hybrid simulation due in part to increasing system complexity.…”