Collaborative Research: Priority Dispatching of Patients in the Aftermath of a Mass-Casualty Event

合作研究：大规模伤亡事件后优先调度患者

• 批准号: 0927607
• 负责人: Nilay Argon
• 金额: $ 36.04万
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0927607&HistoricalAwards=false
• 关键词: Collaborative; Research; Priority; Dispatching; Patients

This grant provides funding for the development of simple but effective decision rules for allocating scarce resources (such as ambulances and operating rooms) to patients in the aftermath of mass-casualty incidents. The problem formulations are based on the model of Sacco Triage Method (STM), which was proposed to obtain a good patient allocation policy in real-time by solving a linear program. This research will significantly expand on the model of STM by introducing stochastic components that are highly relevant in practice and also by placing it within a dynamic programming framework for a better understanding of decisions for dynamic patient triage. Instead of using the model to obtain a solution in real time, it will be used to investigate structural characteristics of optimal or near-optimal policies and also to develop heuristic methods when optimal policies cannot be characterized or are not easy to implement. A comprehensive simulation model will be developed, which will be used in testing the performances of the proposed policies and guidelines.If successful, this research will provide scientific support for the emergency response community in their revived effort of developing effective emergency response policies. The main objective of this work is to identify effective but also simple rules so as to make them more appealing for practitioners. The research will identify broad guidelines that can be easily adopted in the field. These guidelines will essentially determine the type of the prioritization policy to be used depending on easily observable measures such as the approximate total number of casualties. The proposed work will also contribute to the classical job scheduling literature in Operations Research since it involves the analysis of a novel formulation for a job scheduling problem that arises in many different settings.

这笔赠款为制定简单而有效的决策规则提供资金，以便在大规模伤亡事件发生后将稀缺资源（如救护车和手术室）分配给病人。该问题的配方是基于模型的Sunday分诊方法（STM），提出了一个良好的病人分配政策，在实时通过求解线性规划。这项研究将显着扩大STM模型，通过引入随机组件，在实践中是高度相关的，也通过将其放置在一个动态规划的框架内，以更好地了解动态患者分流的决策。而不是使用该模型来获得一个解决方案，在真实的时间，它将被用来调查最佳或接近最佳的政策的结构特征，并制定启发式方法时，最佳的政策不能表征或不容易实现。研究将发展一个全面的模拟模式，用以测试拟议政策和指引的成效。如果成功，这项研究将为应急响应界重新努力制定有效的应急响应政策提供科学支持。这项工作的主要目标是确定有效但又简单的规则，使其对从业人员更具吸引力。这项研究将确定在该领域容易采用的广泛准则。这些准则基本上将根据容易观察到的措施，如伤亡的大致总数，确定将采用的优先次序政策的类型。拟议中的工作也将有助于经典的作业调度文献运筹学，因为它涉及到一个新的配方的作业调度问题，出现在许多不同的设置分析。