Validating Triage for Chemical Mass Casualty Incidents - A First Step

验证化学大规模伤亡事件的分类——第一步

• 批准号: 8919744
• 负责人: Joan Marie Culley
• 金额: $ 52.07万
• 依托单位: UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8919744
• 关键词: Accident and Emergency department; Accounting; Address; Advisory Committees; Algorithms; Ammonia; Breathing; Caring; Chemical Exposure; Chemicals; Chlorine; Cities; Communicable Diseases; Computers; Confusion; Data; Data Reporting; Development; Disasters; Disease Outbreaks; Early Diagnosis; Early identification; Effectiveness; Emergency Department patient; Emergency Situation; Evaluation; Event; Exercise; Feedback; Funding; Goals; Gold; Guidelines; Hazardous Substances; Health care facility; Hospital Personnel; Hospitals; Informatics; Information Systems; Injury; Lead; Liquid substance; Measures; Medical Records; Methods; Monitor; Outcome; Oxygen; Patient Triage; Patients; Pattern; Phase; Process; Pulse Oximetry; Randomized; Recommendation; Reporting; Research; Research Design; Science; Severities; Signs and Symptoms; Solutions; Staging; Symptoms; System; Technology; Testing; Triage; United States National Institutes of Health; Wireless Technology; abstracting; base; computerized tools; design; emergency service responder; experience; flexibility; foodborne; hazard; improved; indexing; injured; innovation; killings; mass casualty; standard measure; tool

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.

描述（由申请人提供）：为了减少大规模伤亡事件 (MCI) 后进入医疗机构的伤亡人数“激增”，应急响应人员和医院工作人员使用分类来快速评估患者并优先考虑他们的护理，以挽救尽可能多的患者活出一种可能。在治疗有毒吸入危险化学品（TIH 化学品）MCI 受害者时遇到三个主要挑战：1) 快速识别 MCI 的发生，2) 快速检测所涉及的化学品，以及 3) 准确识别、分类和处理接触者，精确有效地改善患者的治疗效果。美国每年生产和运输近 170 万辆危险材料的轨道车。此类化学物质在穿过城市时发生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国家指南并未充分考虑到涉及化学品的事件。我们之前 NIH/NLM R21LM10833 资助的南卡罗来纳州格兰尼特维尔氯灾难研究的结果发现： 1) 紧急严重程度指数 (ESI) 医院分诊系统对接触氯的受害者的预测质量较差； 2) 在获得任何化学品暴露信息之前，大量受害者涌入急诊室，导致受害者处理混乱和困难；并且存在更敏感的分类评估（例如，通过脉搏血氧仪 [SpO2] 测量的氧饱和度）。目前，没有信息学工具可以快速识别激增的早期阶段， 有效处理受害者，也不为 TIH 化学品或任何其他 MCI 提出分类建议。我们提出了一种新的 ED 信息学计算工具（EDICT），它结合了新的分诊算法（TIH 化学分诊算法），并将 NLM 紧急救援人员无线信息系统（WISER）系统与真实灾害数据相结合，以更准确、精确和高效地进行分诊ED 患者，首先使用化学 MCI。 SpO2 监测将用于 TIH 化学品分类算法，以更好地评估 TIH 化学品暴露中常见的损伤潜伏期。基于计算机的信息学解决方案可改善 MCI 后入院急诊科患者的早期识别、处理和分诊，从而增强灾难信息学的科学性。在常规急诊实践中使用 EDICT 可能会导致信息学技术的一般使用取得突破，从而显着改善急诊室处理患者的方式。灵活、强大且可扩展的信息学计算解决方案有可能在其他类型的 MCI（例如食源性和传染病爆发）以及急诊科的日常使用中得到更广泛的应用。这项研究是开发新的急诊信息学工具的第一步，该工具可以改变所有急诊患者的处理方式。