Literature DB >> 22990085

Modeling using discrete event simulation: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-4.

Jonathan Karnon1, James Stahl2, Alan Brennan3, J Jaime Caro4, Javier Mar5, Jörgen Möller6.   

Abstract

Discrete event simulation (DES) is a form of computer-based modeling that provides an intuitive and flexible approach to representing complex systems. It has been used in a wide range of health care applications. Most early applications involved analyses of systems with constrained resources, where the general aim was to improve the organization of delivered services. More recently, DES has increasingly been applied to evaluate specific technologies in the context of health technology assessment. The aim of this article is to provide consensus-based guidelines on the application of DES in a health care setting, covering the range of issues to which DES can be applied. The article works through the different stages of the modeling process: structural development, parameter estimation, model implementation, model analysis, and representation and reporting. For each stage, a brief description is provided, followed by consideration of issues that are of particular relevance to the application of DES in a health care setting. Each section contains a number of best practice recommendations that were iterated among the authors, as well as the wider modeling task force.

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Year:  2012        PMID: 22990085     DOI: 10.1177/0272989X12455462

Source DB:  PubMed          Journal:  Med Decis Making        ISSN: 0272-989X            Impact factor:   2.583


  50 in total

1.  An empirical comparison of Markov cohort modeling and discrete event simulation in a capacity-constrained health care setting.

Authors:  L B Standfield; T A Comans; P A Scuffham
Journal:  Eur J Health Econ       Date:  2015-12-29

2.  Myths and Misconceptions of Within-Cycle Correction: A Guide for Modelers and Decision Makers.

Authors:  Elamin H Elbasha; Jagpreet Chhatwal
Journal:  Pharmacoeconomics       Date:  2016-01       Impact factor: 4.981

3.  The flex track: flexible partitioning between low- and high-acuity areas of an emergency department.

Authors:  Lauren F Laker; Craig M Froehle; Christopher J Lindsell; Michael J Ward
Journal:  Ann Emerg Med       Date:  2014-06-18       Impact factor: 5.721

4.  Economic evaluations with agent-based modelling: an introduction.

Authors:  Jagpreet Chhatwal; Tianhua He
Journal:  Pharmacoeconomics       Date:  2015-05       Impact factor: 4.981

5.  Climate influences on the cost-effectiveness of vector-based interventions against malaria in elimination scenarios.

Authors:  Paul E Parham; Dyfrig A Hughes
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2015-04-05       Impact factor: 6.237

Review 6.  An Educational Review About Using Cost Data for the Purpose of Cost-Effectiveness Analysis.

Authors:  Matthew Franklin; James Lomas; Simon Walker; Tracey Young
Journal:  Pharmacoeconomics       Date:  2019-05       Impact factor: 4.981

7.  Building better models: if we build them, will policy makers use them? Toward integrating modeling into health care decisions.

Authors:  Jeanne Mandelblatt; Clyde Schechter; David Levy; Ann Zauber; Yaojen Chang; Ruth Etzioni
Journal:  Med Decis Making       Date:  2012 Sep-Oct       Impact factor: 2.583

Review 8.  A systematic review of the quality of economic models comparing thrombosis inhibitors in patients with acute coronary syndrome undergoing percutaneous coronary intervention.

Authors:  Maximilian H M Hatz; Reiner Leidl; Nichola A Yates; Björn Stollenwerk
Journal:  Pharmacoeconomics       Date:  2014-04       Impact factor: 4.981

Review 9.  When to use discrete event simulation (DES) for the economic evaluation of health technologies? A review and critique of the costs and benefits of DES.

Authors:  Jonathan Karnon; Hossein Haji Ali Afzali
Journal:  Pharmacoeconomics       Date:  2014-06       Impact factor: 4.981

10.  Regional Evaluation of the Severity-Based Stroke Triage Algorithm for Emergency Medical Services Using Discrete Event Simulation.

Authors:  Brittany M Bogle; Andrew W Asimos; Wayne D Rosamond
Journal:  Stroke       Date:  2017-09-15       Impact factor: 7.914

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