Effectiveness of mathematical and simulation models for improving quality of care in emergency departments: a systematic literature review

Abstract

This systematic literature review aims to critically evaluate the use of mathematical and simulation models within emergency departments (EDs) and assess their potential to improve the quality of care. This review emphasises the critical need for quality enhancement in healthcare systems, specifically focusing on EDs. This review incorporates studies investigating the quality of care provided in ED settings, employing assorted mathematical and simulation models for adult populations. Based on the selected studies, a narrative approach was used to synthesise the findings, focusing on outcome classification, simulation, and modelling. There are six outcome dimensions: safety, effectiveness, patient-centeredness, timeliness, efficiency, and equity. This review analysed 112 studies, uncovering a distinct focus on a set of key performance measures within emergency department (ED) operations, accounting for 222 instances across these studies. Measures assessing timeliness were most frequent, occurring 111 times, indicating a strong emphasis on operational efficiency aspects such as waiting times and patient flow. A total of 75 examinations were conducted on efficiency-related measures, specifically focusing on identifying and addressing operational bottlenecks and optimising resource utilisation. On the other hand, safety, patient-centeredness, and effectiveness were not as commonly represented, with only three, four, and 29 instances, respectively. This review highlights the considerable potential of mathematical and simulation models to enhance ED operations, particularly regarding timeliness and efficiency. However, aspects such as patient safety, effectiveness, and patient-centredness were under-represented, while equity was absent across the studies, indicating a clear need for further research. These findings emphasise the importance of adopting a more thorough approach to evaluating and improving the quality of emergency care. Future research should also concentrate on refining data management practices, incorporating observational studies, and exploring various simulation tools to develop a more balanced and inclusive understanding of these models' applications.

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Identifiers

ORCID for Thamer A. Almohaya: orcid.org/0000-0001-6368-6968

ORCID for James Batchelor: orcid.org/0000-0002-5307-552X

ORCID for Edilson Arruda: orcid.org/0000-0002-9835-352X

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