LOCATING AED ENABLED MEDICAL DRONES TO ENHANCE CARDIAC ARREST RESPONSE TIMES
LOCATING AED ENABLED MEDICAL DRONES TO ENHANCE CARDIAC ARREST RESPONSE TIMES
复制标题
DOI：
10.3109/10903127.2015.1115932
复制
发表时间：
2016-05-01
影响因子：
2.4
通讯作者：
Mann, Clay
中科院分区：
文献类型：
--
作者：
Pulver, Aaron;Wei, Ran;Mann, Clay
背景：院外心脏骤停（OOHCA）在美国很普遍。每年有18万至40万人死于心脏骤停。自动体外除颤器（AED）大大提高了OOHCA的生存率。然而，成功的心脏骤停治疗的重要组成部分之一是紧急医疗服务（EMS）响应时间（即，从EMS“车轮滚动”到到达OOHCA现场的时间）。无人机（UAV）经常用于遥感和航空图像收集，但也有新的机会将无人机用于医疗紧急情况。目的：本研究的目的是开发一种地理方法来放置医疗无人机网络，配备自动体外除颤器，旨在最大限度地减少医院外心脏骤停受害者的旅行时间。我们的目标是在一分钟内让一架无人机到达现场，满足至少90%的AED休克治疗需求，同时最大限度地降低实施成本。研究方法：在我们的研究中，使用地理信息系统（GIS）在盐湖县评估了当前的估计旅行时间，并将其与启用AED的医疗无人机网络的估计旅行时间进行了比较。我们采用了一个定位模型，即最大覆盖定位问题（MCLP），来确定无人机的最佳配置，以在一分钟内增加服务覆盖范围。结果如下：我们发现，使用传统车辆，只有4.3%的需求可以在一分钟内到达（旅行时间），而96.4%的需求可以在五分钟内到达，使用当前的EMS车辆和设施位置。分析显示，使用现有的EMS站发射无人机导致80.1%的心脏骤停需求在一分钟内达到。允许新的站点发射无人机导致90.3%的需求在一分钟内达到。最后，使用现有的EMS和新的站点，达到了90.3%的需求，同时大大降低了估计的总成本。结论：尽管仍有许多因素需要考虑，但无人机网络显示出极大减少心脏骤停受害者救生设备旅行时间的潜力。
Background: Out-of-hospital cardiac arrest (OOHCA) is prevalent in the United States. Each year between 180,000 and 400,000 people die due to cardiac arrest. The automated external defibrillator (AED) has greatly enhanced survival rates for OOHCA. However, one of the important components of successful cardiac arrest treatment is emergency medical services (EMS) response time (i.e., the time from EMS "wheels rolling" until arrival at the OOHCA scene). Unmanned Aerial Vehicles (UAV) have regularly been used for remote sensing and aerial imagery collection, but there are new opportunities to use drones for medical emergencies. Objective: The purpose of this study is to develop a geographic approach to the placement of a network of medical drones, equipped with an automated external defibrillator, designed to minimize travel time to victims of out-of-hospital cardiac arrest. Our goal was to have one drone on scene within one minute for at least 90% of demand for AED shock therapy, while minimizing implementation costs. Methods: In our study, the current estimated travel times were evaluated in Salt Lake County using geographical information systems (GIS) and compared to the estimated travel times of a network of AED enabled medical drones. We employed a location model, the Maximum Coverage Location Problem (MCLP), to determine the best configuration of drones to increase service coverage within one minute. Results: We found that, using traditional vehicles, only 4.3% of the demand can be reached (travel time) within one minute utilizing current EMS agency locations, while 96.4% of demand can be reached within five minutes using current EMS vehicles and facility locations. Analyses show that using existing EMS stations to launch drones resulted in 80.1% of cardiac arrest demand being reached within one minute Allowing new sites to launch drones resulted in 90.3% of demand being reached within one minute. Finally, using existing EMS and new sites resulted in 90.3% of demand being reached while greatly reducing estimated overall costs. Conclusion: Although there are still many factors to consider, drone networks show potential to greatly reduce life-saving equipment travel times for victims of cardiac arrest.