Abstract

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 materialThe online version of this article (doi:10.1007/s10916-016-0633-z) contains supplementary material, which is available to authorized users.

Highlights

  • IntroductionThe health community defines a disaster or mass casualty incident (MCI) as an event in which the medical needs exceed, at

  • COMOPSMED/B Spec Sp, Medical Component, Belgian ArmedForces, Brussels, BelgiumThe health community defines a disaster or mass casualty incident (MCI) as an event in which the medical needs exceed, atPage 2 of 15 least temporarily, the response capacities in the affected area, mainly due to a large number of victims and/or severity of the injuries

  • To the best of our knowledge, this study shows for the first time that triage can decrease the mortality in a specific MCI scenario, taking into account a number of disaster medical response (DMR) interventional factors

Read more

Summary

Introduction

The health community defines a disaster or mass casualty incident (MCI) as an event in which the medical needs exceed, at. Page 2 of 15 least temporarily, the response capacities in the affected area, mainly due to a large number of victims and/or severity of the injuries. This imbalance can be due to a quantitative and/or a qualitative shortage of resources (manpower and materials), and to organizational or operational shortcomings. The disaster medical response system (DMRS) is an essential part of the overall disaster management system It is responsible for providing appropriate interventions for the physical, mental and public health of the affected population

Objectives
Methods
Results
Discussion
Conclusion

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.