Theory Establishment and Data Preparedness for Modeling Emergency Medical Service in case of a Mass Casualty Incidents in Road Tunnels

The road system in Taiwan has expanded with remarkable speed resulting in great concern regarding the response to a mass casualty incident (MCI) by the Emergency Medical Services (EMSs). Accidents in road tunnels have the potential to cause major casualties due to their particular configurations and confined conditions. To meet this sudden demand involving huge uncertainties and complexities, EMSs provided by fire services need to be better prepared and more efficient. The recent research into EMS response to MCI aims at identifying effectiveness of life preservation and strategies of emergency mobility through outcome indicators to evaluate performance for different aspects of disaster management. However, the conducting of experimental studies is either impossible or ethically inappropriate. This study tries to use realistic injury statistics for EMS simulations based on medical records of a previous case study and an EMS database currently used in Taiwan. These statistics are temporarily used in a proposed trial MCI/EMS model where injury entities evolve in the medical response model, i.e. the model focuses only on the prehospital phase which includes triage, treatments at the scene and transportation processes - to understand the utilization of resources including Emergency Medical Technicians and ambulances. The outcome indicators also highlight the length of waiting including both before treatment at the Medical Post and before departure at the Delivery Post for each serious injury, and the total operation time to review the emergency response plan for an incident in Hsuehshan tunnel. This study also illustrates how such a model could be used to assess the impact on resource availability, implemented prioritization rule and various other strategies relating to emergency management.

Language

  • English

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Filing Info

  • Accession Number: 01662934
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Feb 15 2018 9:48AM