Evaluation of the Requirements and Critical Features of a Drone-Deployed AED Network to Improve Community-Level Survival after OHCA

摘要 院外心脏骤停每年影响超过35万美国人，存活率非常高 很低。在衰竭后恢复有效心功能的过程中，每延迟1分钟， 存活率下降了10%。旁观者可以通过执行胸部手术来帮助紧急治疗uchA患者 并使用自动体外除颤器(AED)。然而，目前旁观者使用静态 AEDs非常低，除颤主要由急救人员和急救人员实施 服务(EMS)，其到达时间的中位数(8分钟)太晚，无法挽救大多数uchA患者。使用无人机 在拨打911电话后的3到5分钟内将AEDs送到HCA受害者手中是一个令人兴奋的新概念，它基于 关于无人机目前的技术能力。早期对模拟模型的研究已经证明了 一个经过战略设计的无人机网络，可以比EMS更快地将AED交付给uchA 实现。然而，这些早期的模拟假设AED的使用在交付给 在没有考虑旁观者变量的情况下出现的一个场景。众所周知，旁观者可能会犹豫 实施心肺复苏并应用AED，并选择人口统计学和邻里因素(年龄、性别、 种族/性别、教育)可以预测这种治疗的可变性。一个旁观者需要的时间 AED并将其成功应用于uchA可能会严重影响及时使用无人机AED获得的总体生存收益 送货。对潜在治疗效果的准确理解应考虑到预期 旁观者的表演。该应用程序的总体目标是利用数据科学和模拟 用于评估无人机网络的最终用户性能和治疗效果的研究 社区、第一响应者和EMS性能。目标一号将确定无人机的最佳位置 站点确保AED及时到达整个北部的高危地区(3至5分钟内) 卡罗莱纳。目标2将定义和确定uchA上的群落表型群之间的关联 北卡罗来纳州高发社区的治疗模式。AIM 3将使用模拟的无人机AED uchA场景来 在社区表型群(例如，少数民族、农村、 低教育程度，老年人)，在高风险的北卡罗来纳州社区。AIMS 2和AIMS 3的结果将用于改进 我们的优化模型(目标1)用于估计治疗效果和效率。拟议的工作将是 在斯塔克斯博士导师团队的直接监督下进行：导师(丹尼尔·马克博士)，共同导师 克里斯托弗·格兰杰博士和她的顾问团队(比利·威廉姆斯和格雷厄姆·尼科尔博士)。这个K23 在她的指导团队和咨询委员会的支持和指导下，申请将使她的职位。 斯塔克斯最终将领导由美国国立卫生研究院资助的独立研究，重点是uchA的社区治疗，包括 开发/测试干预措施，以改善ahA和务实临床试验中AED的使用，以确定我们的 基于模型的EMS无人机AED递送系统显著改善了uchA受害者的经验结果。

Abstract Out-of-hospital cardiac arrest (OHCA) affects over 350,000 Americans annually and survival rates are very low. For every 1-minute delay in achieving return of effective heart function after collapse, the chance of survival drops by 10%. Bystanders can aid in the emergency treatment of OHCA victims by performing chest compressions and by using automated external defibrillators (AEDs). However, current bystander use of static AEDs is very low and defibrillation is primarily administered by first responders and emergency medical services (EMS) whose median arrival time (8 minutes) is too late to save most OHCA patients. Using a drone to deliver AEDs to OHCA victims within 3 to 5 minutes of the 911 call is an exciting new concept that is based on current technical capabilities of drones. Early work with simulation models has demonstrated the potential of a strategically designed drone network to deliver an AED to an OHCA substantially more rapidly than EMS can achieve. However, these early simulations assumed complete effectiveness of AED use when delivered to an OHCA scene without considering the bystander variables. It is well-known that bystanders may hesitate to perform CPR and to apply an AED, and that select demographic and neighborhood factors (age, sex, race/gender, education) may be predictive of such treatment variability. The time it takes a bystander to extract an AED and apply it successfully in OHCA may critically impact overall survival gains from timely drone AED delivery. An accurate understanding of potential treatment effectiveness should account for expected bystander performance. The overarching aim of this application is to utilize data science and simulation research to estimate end-user performance and treatment-effectiveness of a drone network accounting for community, first responder, and EMS performance. Aim 1 will determine the optimal placement of drone stations to ensure timely AED arrival in high-OHCA risk geographic areas (within 3 to 5 minutes) across North Carolina. Aim 2 will define and determine the association of community phenotypic clusters on OHCA treatment patterns in high-incidence NC communities. Aim 3 will use simulated drone AED OHCA scenarios to define drone-AED-bystander treatment intervals among community phenotypic clusters (e.g., minority, rural, low education, elderly) in high-OHCA risk NC neighborhoods. Results from Aims 2 and 3 will be used to refine our optimization model (Aim 1) to estimate treatment effectiveness and efficiency. The proposed work will be carried out under the direct supervision of Dr. Starks mentorship team: mentor (Dr. Daniel Mark), co-mentor (Dr. Christopher Granger), and her advisory team (Drs. Billy Williams and Graham Nichol). This K23 application with the support and guidance of her mentorship team and advisory committee will position Dr. Starks to eventually lead independent NIH funded studies focused on community treatment of OHCA, including developing/testing interventions to improve AED use in OHCA and pragmatic clinical trials to determine if our model-based EMS drone AED delivery system measurably improves empirical outcomes in OHCA victims.