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Preventing Opioid Exposure Training (POET) for First Responders

Preventing Opioid Exposure Training (POET) for First Responders
急救人员预防阿片类药物暴露培训 (POET)
批准号:
9753662
负责人:
Margaret Andrews Rush
金额:
$10.0万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-04-02 至 2021-03-31

项目摘要

项目成果

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中文摘要
翻译
项目摘要/摘要 美国的阿片类药物危机,指的是2010年代两种处方的迅速增加 在美国,非处方阿片类药物滥用是一个主要的公共卫生问题, 阿片类药物过量死亡达到流行水平,超过与枪支有关的死亡人数 2016年的死亡人数。虽然海洛因仍然是美国滥用的主要非法阿片类药物,但最近发生了戏剧性的 合成阿片类药物(主要是芬太尼和芬太尼类物质)可获得性增加 比吗啡强10,000倍的药效使急救人员面临意外 服药过量,甚至死亡。这些物质的极端效力,可能会意外地 通过皮肤或与粘膜接触摄入、吸入或吸收,意味着 即使是极少量的意外接触也可能对First构成严重威胁 响应者。应答者不仅在应对过量服药时会暴露于芬太尼, 也可以在执行搜查令或逮捕令期间以及在处理毒品或 受污染的非毒品证据。社区中显然需要对产品进行培训 急救员如何在履行职责的同时有效地保护自己 提供及时和适当的护理。基于计算机的预防阿片类药物暴露 培训(PEET)将是一种创新的学习产品,向急救人员传授关于 阿片类药物接触的风险以及如何识别和管理工作中的这些风险。培训 参与者将学习识别他们可能遇到潜在危险的警告信号 基于患者的体征和症状和/或观察到的材料的芬太尼暴露 在一个场景里。然后,培训将审查风险评估和个人防护措施的选择 暴露后处理、清理和去污的设备(PPE)和指南。 对于第一阶段,将根据公布的暴露指南制定培训课程 通过联邦机构和其他机构,以及与利益攸关方的面谈。这将是 然后是原型的可用性测试,以及第一次 在培训结束和三个月后,响应者的知识会有所增加。这将有助于 改变新培训技术如何通过以下方式推动应答者做好准备的范式 使用虚拟世界教急救人员如何识别和管理职业风险。 POTE应用程序的潜在商业应用包括执法人员 在地方、州和联邦一级,医疗专业人员(包括急救人员、护理人员和 医院工作人员)和面临职业阿片类药物暴露风险的其他应答者。
英文摘要
PROJECT SUMMARY/ABSTRACT The United States opioid crisis, referring to the rapid increase in the 2010s of both prescription and non-prescription opioid abuse in the United States, is a major public health issue, with overdose deaths from opioids reaching epidemic levels, surpassing the number of gun-related deaths in 2016. While heroin remains the main illicit opioid abused in the U.S., a recent dramatic increase in the availability of synthetic opioids (mainly fentanyl and fentanyl-like substances) up to 10,000 times more potent than morphine has placed first responders at risk of accidental overdose and even death. The extreme potency of these substances, which can be accidentally ingested, inhaled, or absorbed through the skin or via contact with mucous membranes, means that accidental contact with even a minuscule amount can pose a severe threat to first responders. Responders can be exposed to fentanyl not only when responding to overdoses, but also during the execution of search or arrest warrants and during the processing of drug or contaminated non-drug evidence. There is a clear need in the community for products to train first responders on how to effectively protect themselves while still performing their duties and providing timely and appropriate care. The computer-based Preventing Opioid Exposure Training (POET) will be an innovative learning product that teaches first responders about the risks of opioid exposures and how to recognize and manage these risks on the job. Training participants will learn to identify warning signs that they may be encountering a potential fentanyl exposure based on the signs and symptoms of a patient and/or the material observed at a scene. Then, the training will review risk assessment and selection of personal protective equipment (PPE) and guidelines for post-exposure treatment, clean-up, and decontamination. For Phase I, the training curriculum will be developed based on exposure guidelines published by federal agencies and other institutions, as well as interviews with stakeholders. This will be followed by usability testing of the prototype as well as a pre- and post-assessment of first responder knowledge gains at the end of training and three months later. This will contribute to shifting the paradigm of how novel training technologies can drive responder preparedness by using virtual worlds to teach first responders how to recognize and manage occupational risks. The potential commercial application of the POET application includes law enforcement officers at the local, state, and federal level, medical professionals (including EMTs, paramedics, and hospital staff), and other responders who face occupational opioid exposure risks.
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Develop and Test a Tool for Training Research Responders in Emergency Operations
  • 批准号:
    8898456
  • 项目类别:
  • 资助金额:
    $9.98万
  • 财政年份:
    2015
  • 负责人:
    Margaret Andrews Rush
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  • 项目类别:
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  • 财政年份:
    2011
  • 负责人:
    Margaret Andrews Rush
  • 依托单位:
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