Evidence map›Paper›PMID 40258384›Full record

SynthesisApplied clinical informatics2025

Effectiveness of Mathematical and Simulation Models for Improving Quality of Care in Emergency Departments: A Systematic Literature Review.

Thamer A Almohaya, James Batchelor, Edilson Arruda

Abstract readSystematic Review
In one paragraph

Synthesis in Applied clinical informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Thamer A AlmohayaFaculty of Medicine, University of Southampton, Southampton, United Kingdom.ORCID 0000-0001-6368-6968
James BatchelorClinical Informatics and Healthcare Innovation, Faculty of Medicine, University of Southampton, Southampton, United Kingdom.ORCID 0000-0002-5307-552X
Edilson ArrudaCentre for Healthcare Analytics, Southampton Business School, University of Southampton, Southampton, United Kingdom.ORCID 0000-0002-9835-352X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this systematic literature review is 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 emphasizes the critical need for quality enhancement in health care systems, with a specific focus on EDs.This review incorporates studies that have investigated 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 synthesize the findings, focusing on outcome classification, simulation, and modelling. There are six outcome dimensions: safety, effectiveness, patient-centeredness, timeliness, efficiency, and equity.This review analyzed 112 studies, uncovering a distinct focus on a set of key performance measures within ED operations, accounting for 222 instances across these studies. Measures assessing timeliness were most frequent, occurring 111 times, indicative of 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, with a specific focus on identifying and addressing operational bottlenecks and optimizing resource utilization. On the other hand, safety, patient-centeredness, and effectiveness were not as commonly represented, with only 3, 4, 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-centeredness were underrepresented, while equity was absent across the studies, indicating a clear need for further research. These findings emphasize 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.

Indexed as

Computer SimulationEmergency Service, HospitalModels, TheoreticalQuality ImprovementQuality of Health CareHumans

Identifiers

PMID40258384
PMCPMC12373464

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.