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SIMEDIS: a Discrete-Event Simulation Model for Testing Responses to Mass Casualty Incidents

It is recognized that the study of the disaster medical response (DMR) is a relatively new field. To date, there is no evidence-based literature that clearly defines the best medical response principles, concepts, structures and processes in a disaster setting. Much of what is known about the DMR re...

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Autores principales: Debacker, Michel, Van Utterbeeck, Filip, Ullrich, Christophe, Dhondt, Erwin, Hubloue, Ives
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5069323/
https://www.ncbi.nlm.nih.gov/pubmed/27757716
http://dx.doi.org/10.1007/s10916-016-0633-z
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author Debacker, Michel
Van Utterbeeck, Filip
Ullrich, Christophe
Dhondt, Erwin
Hubloue, Ives
author_facet Debacker, Michel
Van Utterbeeck, Filip
Ullrich, Christophe
Dhondt, Erwin
Hubloue, Ives
author_sort Debacker, Michel
collection PubMed
description It is recognized that the study of the disaster medical response (DMR) is a relatively new field. To date, there is no evidence-based literature that clearly defines the best medical response principles, concepts, structures and processes in a disaster setting. Much of what is known about the DMR results from descriptive studies and expert opinion. No experimental studies regarding the effects of DMR interventions on the health outcomes of disaster survivors have been carried out. Traditional analytic methods cannot fully capture the flow of disaster victims through a complex disaster medical response system (DMRS). Computer modelling and simulation enable to study and test operational assumptions in a virtual but controlled experimental environment. The SIMEDIS (Simulation for the assessment and optimization of medical disaster management) simulation model consists of 3 interacting components: the victim creation model, the victim monitoring model where the health state of each victim is monitored and adapted to the evolving clinical conditions of the victims, and the medical response model, where the victims interact with the environment and the resources at the disposal of the healthcare responders. Since the main aim of the DMR is to minimize as much as possible the mortality and morbidity of the survivors, we designed a victim-centred model in which the casualties pass through the different components and processes of a DMRS. The specificity of the SIMEDIS simulation model is the fact that the victim entities evolve in parallel through both the victim monitoring model and the medical response model. The interaction between both models is ensured through a time or medical intervention trigger. At each service point, a triage is performed together with a decision on the disposition of the victims regarding treatment and/or evacuation based on a priority code assigned to the victim and on the availability of resources at the service point. The aim of the case study is to implement the SIMEDIS model to the DMRS of an international airport and to test the medical response plan to an airplane crash simulation at the airport. In order to identify good response options, the model then was used to study the effect of a number of interventional factors on the performance of the DMRS. Our study reflects the potential of SIMEDIS to model complex systems, to test different aspects of DMR, and to be used as a tool in experimental research that might make a substantial contribution to provide the evidence base for the effectiveness and efficiency of disaster medical management. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10916-016-0633-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-50693232016-11-02 SIMEDIS: a Discrete-Event Simulation Model for Testing Responses to Mass Casualty Incidents Debacker, Michel Van Utterbeeck, Filip Ullrich, Christophe Dhondt, Erwin Hubloue, Ives J Med Syst Systems-Level Quality Improvement It is recognized that the study of the disaster medical response (DMR) is a relatively new field. To date, there is no evidence-based literature that clearly defines the best medical response principles, concepts, structures and processes in a disaster setting. Much of what is known about the DMR results from descriptive studies and expert opinion. No experimental studies regarding the effects of DMR interventions on the health outcomes of disaster survivors have been carried out. Traditional analytic methods cannot fully capture the flow of disaster victims through a complex disaster medical response system (DMRS). Computer modelling and simulation enable to study and test operational assumptions in a virtual but controlled experimental environment. The SIMEDIS (Simulation for the assessment and optimization of medical disaster management) simulation model consists of 3 interacting components: the victim creation model, the victim monitoring model where the health state of each victim is monitored and adapted to the evolving clinical conditions of the victims, and the medical response model, where the victims interact with the environment and the resources at the disposal of the healthcare responders. Since the main aim of the DMR is to minimize as much as possible the mortality and morbidity of the survivors, we designed a victim-centred model in which the casualties pass through the different components and processes of a DMRS. The specificity of the SIMEDIS simulation model is the fact that the victim entities evolve in parallel through both the victim monitoring model and the medical response model. The interaction between both models is ensured through a time or medical intervention trigger. At each service point, a triage is performed together with a decision on the disposition of the victims regarding treatment and/or evacuation based on a priority code assigned to the victim and on the availability of resources at the service point. The aim of the case study is to implement the SIMEDIS model to the DMRS of an international airport and to test the medical response plan to an airplane crash simulation at the airport. In order to identify good response options, the model then was used to study the effect of a number of interventional factors on the performance of the DMRS. Our study reflects the potential of SIMEDIS to model complex systems, to test different aspects of DMR, and to be used as a tool in experimental research that might make a substantial contribution to provide the evidence base for the effectiveness and efficiency of disaster medical management. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10916-016-0633-z) contains supplementary material, which is available to authorized users. Springer US 2016-10-18 2016 /pmc/articles/PMC5069323/ /pubmed/27757716 http://dx.doi.org/10.1007/s10916-016-0633-z Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Systems-Level Quality Improvement
Debacker, Michel
Van Utterbeeck, Filip
Ullrich, Christophe
Dhondt, Erwin
Hubloue, Ives
SIMEDIS: a Discrete-Event Simulation Model for Testing Responses to Mass Casualty Incidents
title SIMEDIS: a Discrete-Event Simulation Model for Testing Responses to Mass Casualty Incidents
title_full SIMEDIS: a Discrete-Event Simulation Model for Testing Responses to Mass Casualty Incidents
title_fullStr SIMEDIS: a Discrete-Event Simulation Model for Testing Responses to Mass Casualty Incidents
title_full_unstemmed SIMEDIS: a Discrete-Event Simulation Model for Testing Responses to Mass Casualty Incidents
title_short SIMEDIS: a Discrete-Event Simulation Model for Testing Responses to Mass Casualty Incidents
title_sort simedis: a discrete-event simulation model for testing responses to mass casualty incidents
topic Systems-Level Quality Improvement
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5069323/
https://www.ncbi.nlm.nih.gov/pubmed/27757716
http://dx.doi.org/10.1007/s10916-016-0633-z
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