Literature DB >> 22168201

Review of modeling approaches for emergency department patient flow and crowding research.

Jennifer L Wiler1, Richard T Griffey, Tava Olsen.   

Abstract

Emergency department (ED) crowding is an international phenomenon that continues to challenge operational efficiency. Many statistical modeling approaches have been offered to describe, and at times predict, ED patient load and crowding. A number of formula-based equations, regression models, time-series analyses, queuing theory-based models, and discrete-event (or process) simulation (DES) models have been proposed. In this review, we compare and contrast these modeling methodologies, describe the fundamental assumptions each makes, and outline the potential applications and limitations for each with regard to usability in ED operations and in ED operations and crowding research.
© 2011 by the Society for Academic Emergency Medicine.

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Year:  2011        PMID: 22168201     DOI: 10.1111/j.1553-2712.2011.01135.x

Source DB:  PubMed          Journal:  Acad Emerg Med        ISSN: 1069-6563            Impact factor:   3.451


  21 in total

Review 1.  Computer modeling of lung cancer diagnosis-to-treatment process.

Authors:  Feng Ju; Hyo Kyung Lee; Raymond U Osarogiagbon; Xinhua Yu; Nick Faris; Jingshan Li
Journal:  Transl Lung Cancer Res       Date:  2015-08

2.  Using discrete event computer simulation to improve patient flow in a Ghanaian acute care hospital.

Authors:  Allyson M Best; Cinnamon A Dixon; W David Kelton; Christopher J Lindsell; Michael J Ward
Journal:  Am J Emerg Med       Date:  2014-05-20       Impact factor: 2.469

3.  Comparison of emergency department crowding scores: a discrete-event simulation approach.

Authors:  Virginia Ahalt; Nilay Tanık Argon; Serhan Ziya; Jeff Strickler; Abhi Mehrotra
Journal:  Health Care Manag Sci       Date:  2016-10-04

4.  Reducing COPD readmissions through predictive modeling and incentive-based interventions.

Authors:  Xiang Zhong; Sujee Lee; Cong Zhao; Hyo Kyung Lee; Philip A Bain; Tammy Kundinger; Craig Sommers; Christine Baker; Jingshan Li
Journal:  Health Care Manag Sci       Date:  2017-11-25

5.  Lessons Learned From the Development and Parameterization of a Computer Simulation Model to Evaluate Task Modification for Health Care Providers.

Authors:  Parastu Kasaie; W David Kelton; Rachel M Ancona; Michael J Ward; Craig M Froehle; Michael S Lyons
Journal:  Acad Emerg Med       Date:  2017-11-11       Impact factor: 3.451

6.  Understanding Emergency Care Delivery Through Computer Simulation Modeling.

Authors:  Lauren F Laker; Elham Torabi; Daniel J France; Craig M Froehle; Eric J Goldlust; Nathan R Hoot; Parastu Kasaie; Michael S Lyons; Laura H Barg-Walkow; Michael J Ward; Robert L Wears
Journal:  Acad Emerg Med       Date:  2017-09-21       Impact factor: 3.451

7.  A system model of work flow in the patient room of hospital emergency department.

Authors:  Junwen Wang; Jingshan Li; Patricia K Howard
Journal:  Health Care Manag Sci       Date:  2013-04-16

8.  A Markov Chain Model for Transient Analysis of Handoff Process in Emergency Departments.

Authors:  Wenjun Zhu; Brian W Patterson; Maureen Smith; Anne C Rifleman; Pascale Carayon; Jingshan Li
Journal:  IEEE Robot Autom Lett       Date:  2020-05-20

9.  A dedicated neurologist at the emergency department during out-of-office hours decreases patients' length of stay and admission percentages.

Authors:  M Christien van der Linden; Crispijn L van den Brand; Ido R van den Wijngaard; Roeline A Y de Beaufort; Naomi van der Linden; Korné Jellema
Journal:  J Neurol       Date:  2018-01-12       Impact factor: 4.849

10.  Using the Collective System Design Methodology to Improve a Medical Center Emergency Room Performance.

Authors:  David Cochran; Joseph Swartz; Behin Elahi; Joseph Smith
Journal:  J Med Syst       Date:  2018-10-18       Impact factor: 4.460

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