Department of Innovation and Technology Management, University of Vienna, Bruenner Str. 72, 1210, Vienna, Austria.
Health Care Manag Sci. 2012 Sep;15(3):254-69. doi: 10.1007/s10729-012-9198-7. Epub 2012 Jun 1.
Due to an increasing number of mass casualty incidents, which are generally complex and unique in nature, we suggest that decision makers consider operations research-based policy models to help prepare emergency staff for improved planning and scheduling at the emergency site. We thus develop a discrete-event simulation policy model, which is currently being applied by disaster-responsive ambulance services in Austria. By evaluating realistic scenarios, our policy model is shown to enhance the scheduling and outcomes at operative and online levels. The proposed scenarios range from small, simple, and urban to rather large, complex, remote mass casualty emergencies. Furthermore, the organization of an advanced medical post can be improved on a strategic level to increase rescue quality, including enhanced survival of injured victims. In particular, we consider a realistic mass casualty incident at a brewery relative to other exemplary disasters. Based on a variety of such situations, we derive general policy implications at both the macro (e.g., strategic rescue policy) and micro (e.g., operative and online scheduling strategies at the emergency site) levels.
由于越来越多的大规模伤亡事件，这些事件通常具有复杂性和独特性，我们建议决策者考虑基于运筹学的政策模型，以帮助应急人员为紧急现场的改进规划和调度做好准备。因此，我们开发了一个离散事件模拟政策模型，该模型目前正在奥地利的灾害响应救护车服务中应用。通过评估现实场景，我们的政策模型表明可以在操作和在线层面提高调度和结果。所提出的场景范围从小型、简单和城市到大型、复杂和偏远的大规模伤亡紧急情况。此外，可以在战略层面上改进高级医疗站的组织，以提高救援质量，包括增加受伤受害者的生存机会。特别是，我们考虑了一家啤酒厂的现实大规模伤亡事件与其他典型灾害。基于各种此类情况，我们得出了宏观（例如，战略救援政策）和微观（例如，紧急现场的操作和在线调度策略）层面的一般政策含义。
