Discrete-event simulation (DES) is a stochastic modeling approach widely used to address dynamic and complex systems, such as healthcare. In this review, academic databases were systematically searched to identify 231 papers focused on DES modeling in healthcare. These studies were sorted by year, approach, healthcare setting, outcome, provenance, and software use. Among the surveys, conceptual/theoretical studies, reviews, and case studies, it was found that almost two-thirds of the theoretical articles discuss models that include DES along with other analytical techniques, such as optimization and lean/six sigma, and one-third of the applications were carried out in more than one healthcare setting, with emergency departments being the most popular. Moreover, half of the applications seek to improve time- and efficiency-related metrics, and one-third of all papers use hybrid models. Finally, the most popular DES software is Arena and Simul8. Overall, there is an increasing trend towards using DES in healthcare to address issues at an operational level, yet less than 10% of DES applications present actual implementations following the modeling stage. Thus, future research should focus on the implementation of the models to assess their impact on healthcare processes, patients, and, possibly, their clinical value. Other areas are DES studies that emphasize their methodological formulation, as well as the development of frameworks for hybrid models.

Discrete-Event Simulation Modeling in Healthcare: A Comprehensive Review.

With the growing demand for hospital resources worldwide, healthcare facilities, including Emergency Departments (EDs), look for opportunities to enhance patient care efficiency and streamline healthcare processes. To achieve this, simulation techniques, including Discrete-Event Simulation (DES) and Agent-Based Simulation (ABS), started gaining awareness; however, little is known regarding their applications and integration with various optimization methods and scenario-generation techniques in EDs. To address this research gap, we used bibliometric analysis and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework to narrow the publications to 62 articles and conduct a comprehensive review. During the evaluation of each article, three dimensions, namely the area of application, outcomes, and Key Performance Indicators (KPIs), were reviewed to understand the development and implementation of simulation techniques in EDs. The results shed light on the vital impact of process and time variations on simulation quality and the importance of involving healthcare professionals in simulation validation and verification. Furthermore, this study provided a conceptual framework that identified gaps and solutions related to the model scopes, approaches, technologies, and implementation of the DES and ABS in EDs. These findings could prove useful for healthcare researchers, practitioners, and managers in advancing the future research directions of DES and ABS and practical implications in the decision-making process. 

Comprehensive review and future research agenda on discrete-event simulation and agent-based simulation of emergency departments

The COVID-19 pandemic has strongly affected the dynamics of Emergency Departments (EDs) worldwide and has accentuated the need for tackling different operational inefficiencies that decrease the quality of care provided to infected patients. The EDs continue to struggle against this outbreak by implementing strategies maximizing their performance within an uncertain healthcare environment. The efforts, however, have remained insufficient in view of the growing number of admissions and increased severity of the coronavirus disease. Therefore, the primary aim of this paper is to review the literature on process improvement interventions focused on increasing the ED response to the current COVID-19 outbreak to delineate future research lines based on the gaps detected in the practical scenario. Therefore, we applied the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to perform a review containing the research papers published between December 2019 and April 2021 using ISI Web of Science, Scopus, PubMed, IEEE, Google Scholar, and Science Direct databases. The articles were further classified taking into account the research domain, primary aim, journal, and publication year. A total of 65 papers disseminated in 51 journals were concluded to satisfy the inclusion criteria. Our review found that most applications have been directed towards predicting the health outcomes in COVID-19 patients through machine learning and data analytics techniques. In the overarching pandemic, healthcare decision makers are strongly recommended to integrate artificial intelligence techniques with approaches from the operations research (OR) and quality management domains to upgrade the ED performance under social-economic restrictions.

/pdf/process-improvement-approaches-for-increasing-the-response-3zgrulci0s.pdf

Process Improvement Approaches for Increasing the Response of Emergency Departments against the COVID-19 Pandemic: A Systematic Review.

Emergency department (ED) overcrowding is a common issue in emergency medicine of Canada Previous studies indicate that adding a physician in triage (PIT) can increase accuracy and efficiency in the initial process of patient evaluations However, the PIT concept should be thoroughly researched before its widespread implementation can be recommended This paper introduces the evaluation of impact of PIT on ED patient wait times and length of stay (LOS) using simulation modeling A discrete-event simulation model of ED is built to simulate and predict the effect of PIT intervention The model performance is validated using current-state ED flow metrics to quantitatively test multiple alternatives for ED improvements Results show that the PIT implementation can reduce the ED patient LOS by an average of 34% and Waiting to be Seen time by 49% across all scenarios studied The proposed method can be applied to improve the operation efficiency of healthcare systems in the current pandemic, COVID-19 (C) 2020 by the authors;licensee Growing Science, Canada

/pdf/evaluation-of-physician-in-triage-impact-on-overcrowding-in-5f4lscxjjb.pdf

Evaluation of physician in triage impact on overcrowding in emergency department using discrete-event simulation

Paramedics in Ontario have largely been limited to transporting those with mental health or addiction (MHA)-related emergencies to the emergency department (ED). The ED has repeatedly been identified as a problematic and challenging setting for people with MHA needs. This article examines an innovative patient care model (PCM) established by the Middlesex–London Paramedic Service and its partners for specific MHA emergencies where patients were given options for care that included transportation to a Canadian Mental Health Association (CMHA) Crisis Centre or information for support. Qualitative and quantitative data that were utilized for regular reporting to the Ministry were included in the analysis. The findings indicated that the goals of reducing pressures on EDs and paramedic services, enhancing paramedics’ ability to address MHA calls, and improving patient care experiences were met. This model improves patient autonomy and options for care, improves the means for addressing patients’ social determinants of health, and offers transportation to a non-medicalized facility.

Examining an Alternate Care Pathway for Mental Health and Addiction Prehospital Emergencies in Ontario, Canada: A Critical Analysis

Overcrowding is a common problem in hospital emergency departments (EDs) where the ED service cannot meet care demands within reasonable time frames. This paper introduces a quantitative approach using computer simulation modeling for hospital decision makers to explore trade-offs between efficiency, workload and capacity of EDs. A computer simulation model is built based on the ED of a local hospital to improvement efficiency of the ED patient flow. Bottlenecks of the emergency care process are detected using the built model. The ED performance is examined by applying alternative strategies to reduce patient waiting time and length of stay. The proposed method can be applied to improve the operation efficiency of healthcare systems in the current pandemic, COVID -19.

Bottleneck Detection and Reduction Using Simulation Modeling to Reduce Overcrowding of Hospital Emergency Department

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Jie Yang

Author Tools

Chat about Author

Papers

Evaluation of physician in triage impact on overcrowding in emergency department using discrete-event simulation

Bottleneck Detection and Reduction Using Simulation Modeling to Reduce Overcrowding of Hospital Emergency Department