Toronto Emergency Medical Services, Ontario, Canada.
Prehosp Emerg Care. 2010 Jan-Mar;14(1):109-17. doi: 10.3109/10903120903349754.
Many emergency medical services (EMS) systems dispatch nonparamedic firefighter first responders (FFRs) to selected EMS 9-1-1 calls, intending to deliver time-sensitive interventions such as defibrillation, cardiopulmonary resuscitation (CPR), and bag-mask ventilation prior to arrival of paramedics. Deciding when to send FFRs is complicated because critical cases are rare, paramedics often arrive before FFRs, and lights-and-siren responses by emergency vehicles are associated with the risk of en-route traffic collisions.
To describe a methodology allowing EMS systems to optimize their own FFR programs using local data, and reflecting local medical oversight policy and local risk-benefit opinion.
We constructed a generalized input-output model that retrospectively reviews EMS dispatch and electronic prehospital clinical records to identify a subset of Medical Priority Dispatch System (MPDS) call categories ("determinants") that maximize the opportunities for FFR interventions while minimizing unwarranted responses. Input parameters include local FFR interventions, the local FFR "first-on-scene" rate, and the locally acceptable ratio of risk to benefit. The model uses a receiver-operating characteristic (ROC) curve to identify the optimal mix of response specificity and sensitivity achieved by sending FFRs to progressively more categories of EMS calls while remaining within a defined risk-benefit ratio. The model was applied to a 16-month retrospective sample of 220,358 incidents from a large urban EMS system to compare the model's recommendations with the system's current practices.
The model predicts that FFR lights-and-siren responses in the sample could be reduced by 83%, from 93,058 to 16,091 incidents, by confining FFR responses to 27 of 509 MPDS dispatch determinants, representing 7.3% of incidents but 58.9% of all predicted FFR interventions. Of the 93,058 incidents, another 58,275 incidents could be downgraded to safer nonemergency FFR responses and 18,692 responses could be eliminated entirely, improving the specificity of FFR response from 57.8% to 93.0%.
This model provides a robust generalized methodology allowing EMS systems to optimize FFR lights-and-siren responses to emergency medical calls. Further validation is warranted to assess the model's generality.
许多紧急医疗服务（EMS）系统会派遣非医护消防员第一响应者（FFR）到选定的 EMS 9-1-1 电话，旨在在医护人员到达之前提供时间敏感的干预措施，如除颤、心肺复苏术（CPR）和面罩通气。决定何时派遣 FFR 是复杂的，因为危急病例很少见，医护人员通常会先于 FFR 到达，而紧急车辆的灯光和警笛声响应与途中交通碰撞的风险有关。
描述一种允许 EMS 系统使用本地数据优化其 FFR 计划的方法，反映本地医疗监督政策和本地风险收益意见。
我们构建了一个广义的输入输出模型，该模型回顾性地审查 EMS 调度和电子院前临床记录，以确定一组医疗优先调度系统（MPDS）电话类别（“决定因素”），这些类别最大限度地提高了 FFR 干预的机会，同时最小化不必要的响应。输入参数包括本地 FFR 干预、本地 FFR“第一现场”率以及本地可接受的风险收益比。该模型使用接收者操作特征（ROC）曲线来确定通过将 FFR 发送到越来越多的 EMS 电话类别来实现的响应特异性和敏感性的最佳组合，同时保持在定义的风险收益比内。该模型应用于一个大型城市 EMS 系统的 16 个月回顾性样本，以比较模型的建议与系统的当前实践。
该模型预测，通过将 FFR 灯光和警笛声响应限制在 509 个 MPDS 调度决定因素中的 27 个因素，将模型样本中的 FFR 灯光和警笛声响应减少 83%，从 93058 个事件减少到 16091 个事件，这些因素占事件的 7.3%，但占所有预测的 FFR 干预的 58.9%。在 93058 个事件中，另外 58275 个事件可以降级为更安全的非紧急 FFR 响应，18692 个响应可以完全消除，从而将 FFR 响应的特异性从 57.8%提高到 93.0%。
该模型提供了一种强大的通用方法，允许 EMS 系统优化对紧急医疗呼叫的 FFR 灯光和警笛声响应。需要进一步验证来评估模型的通用性。
