Validating Triage for Chemical Mass Casualty Incidents - A First Step

描述(由申请人提供)：为了缓解大规模伤亡事件(MCI)后涌入医疗机构的伤亡人数，急救人员和医院人员使用分诊来快速评估患者并确定他们的护理优先顺序，目标是尽可能挽救更多的生命。在治疗有毒吸入危险化学品(TIH化学品)受害者方面遇到三个主要挑战：1)快速识别已发生MCI，2)快速检测涉及的化学品，3)准确、准确和高效地识别、分类和处理接触到的化学品，以改善患者的预后。美国每年生产和运输近170万节危险材料的火车车厢。这类化学品在城市中流动时的泄漏可能会导致数十万人受伤或死亡。然而，拟议的现有大规模伤亡分类的国家指南并没有完全考虑到包括化学品在内的事件。我们之前由NIH/NLM R21LM10833资助的对南卡罗来纳州格兰尼特维尔氯气灾难的研究发现：1)紧急严重程度指数(ESI)医院分流系统对暴露在氯气中的受害者的预测能力很差；2)在获得任何化学品暴露信息之前，受害者涌入急诊室，导致混乱和难以处理受害者；并且存在更敏感的分流评估(例如，脉搏血氧仪[SpO2]测量的血氧饱和度)。目前，还没有信息学工具来快速识别激增的早期阶段， 有效地处理受害者，也不为TIH化学品或任何其他MCIS提供分类建议。我们提出了一种新的ED信息学计算工具(EDICT)，它结合了一种新的分诊算法(TIH化学分流算法)，并将NLM应急响应无线信息系统(WISER)与真实灾难数据相集成，以化学MCI为第一步，更准确、准确和高效地对急诊患者进行分诊。SpO2监测将用于TIH化学品分类算法，以更好地评估TIH化学品暴露常见的损伤潜伏期。以计算机为基础的信息学解决方案将提高灾害信息学的科学水平，改善MCI后急诊室入院患者的早期识别、处理和分类。在常规急诊实践中使用EDICT可能会导致信息学技术的普遍使用取得突破，从而显著改善急诊室处理患者的方式。灵活、稳健和可扩展的信息学计算解决方案有可能在其他类型的MCIS(例如食源性和传染性疾病暴发)中得到更广泛的应用，以及在急救系统中的日常使用。这项研究是开发新的ED信息学工具的第一步，它可以改变所有ED患者的处理方式。

DESCRIPTION (provided by applicant): To mitigate the "surge" of casualties into a healthcare facility after a mass casualty incident (MCI), emergency responders and hospital personnel use triage to rapidly assess patients and prioritize their care with the goal of saving as many lives a possible. Three main challenges are encountered in the treatment of victims of toxic inhalation hazard chemicals (TIH chemicals) MCIs: 1) quickly identifying that a MCI has occurred, 2) rapidly detecting the chemical involved, and 3) identifying, triaging and processing those exposed accurately, precisely and efficiently to improve patient outcomes. The US produces and transports nearly 1.7 million railcars of hazardous materials each year. A spill of such chemicals as they move through a city could injure or kill hundreds of thousands of people. However, the proposed national guideline for existing mass casualty triage does not fully account for events that include chemicals. Findings from the our previous NIH/NLM R21LM10833 funded study of the Graniteville, SC chlorine disaster, found that: 1) The Emergency Severity Index (ESI) hospital triage system had poor predictive quality for victims exposed to chlorine; 2) the surge of victims into the ED came before any chemical exposure information was available, leading to confusion and difficult victim processing; and there exists more sensitive triage assessments (e.g., oxygen saturation measured by pulse oximetry [SpO2]). Currently, there are no informatics tools to rapidly identify the early stages of a surge, process victims efficiently, nor make triage recommendations for TIH chemicals or any other MCIs. We propose a new ED Informatics Computational Tool (EDICT) that incorporates a new triage algorithm (TIH Chemical Triage Algorithm), and integrates the NLM Wireless Information System for Emergency Responders (WISER) system with real disaster data to more accurately, precisely and efficiently triage ED patients, using a chemical MCI as a first step. SpO2 monitoring will be used in the TIH Chemical Triage Algorithm to better assess injury latency common with TIH chemical exposures. Computer-based informatics solutions that improve early identification, processing, and triage for patients admitted to the ED following a MCI will enhance the science of disaster informatics. Using EDICT in routine ED practice could potentially lead to a breakthrough in the general use of informatics technology to dramatically improve the way patients are processed in EDs. A flexible, robust and scalable informatics computational solution has the potential for broader applications in other types of MCIs (e.g., foodborne and communicable disease outbreaks), as well as day-to-day use in EDs. This study is the first step to developing new ED informatics tools, which can change all ED patient processing.