Hannoun Gaby Joe, Menéndez Mónica
Division of Engineering, New York University Abu Dhabi, Saadiyat Island, Abu Dhabi, United Arab Emirates.
Transp Res Part C Emerg Technol. 2022 Jul;140:103694. doi: 10.1016/j.trc.2022.103694. Epub 2022 May 18.
While advancements in vehicular and wireless communication technologies are shaping the future of our transportation system, emergency medical services (EMS) are not receiving enough research attention. Their operations are still plagued by response delays that can often be life-threatening. Dispatching and redeployment systems identify the best practices regarding the allocation of the resources to emergencies and stations. Yet, the existing systems are unfortunately insufficient, and there is a growing need to embrace new technological solutions. This research introduces a smart system for EMS by leveraging the modular vehicle technology initially developed for transit systems. The proposed system relies on the design of vehicular modules that can couple and decouple to transfer patients from one module to another during transport. A fleet of medical transport vehicles is deployed to cooperate with the life support vehicles by providing, for example, transport and hospital admission tasks, thus allowing life support vehicles to answer pending emergency calls earlier. This is especially useful when there is a large demand for EMS (e.g. under the COVID-19 pandemic or other disasters such as the recent explosion in Beirut). This paper introduces a mathematical programming model to determine the optimal assignment decisions in a deterministic setting. This work is a proof of concept that demonstrates the applicability of the modular vehicle technology to EMS, evaluating the upper bound EMS performance that can be ultimately reached. A sensitivity analysis is conducted to provide insights and recommendations that are useful when selecting the weighting coefficients for the optimization function, to ensure a more efficient implementation of the modular vehicle technology for EMS. Also, the results of a comparative analysis show that the proposed system can adapt and offer larger benefits, in terms of response times and times to hospital, as demand increases and/or resources become more limited.
虽然车辆和无线通信技术的进步正在塑造我们交通系统的未来，但紧急医疗服务（EMS）却没有得到足够的研究关注。其运营仍然受到响应延迟的困扰，而这种延迟往往会危及生命。调度和重新部署系统确定了将资源分配到紧急情况和站点的最佳做法。然而，遗憾的是，现有系统并不完善，因此越来越需要采用新的技术解决方案。本研究通过利用最初为公交系统开发的模块化车辆技术，引入了一种用于紧急医疗服务的智能系统。所提出的系统依赖于车辆模块的设计，这些模块在运输过程中可以耦合和解耦，以便将患者从一个模块转移到另一个模块。部署了一批医疗运输车辆，通过提供例如运输和住院登记任务等，与生命支持车辆合作，从而使生命支持车辆能够更早地响应未处理的紧急呼叫。当对紧急医疗服务有大量需求时（例如在新冠疫情期间或其他灾难，如最近贝鲁特的爆炸事件），这尤其有用。本文介绍了一个数学规划模型，用于在确定性环境中确定最优分配决策。这项工作是一个概念验证，展示了模块化车辆技术在紧急医疗服务中的适用性，评估了最终能够达到的紧急医疗服务性能上限。进行了敏感性分析，以提供在为优化函数选择加权系数时有用的见解和建议，以确保更有效地将模块化车辆技术应用于紧急医疗服务。此外，对比分析结果表明，随着需求增加和/或资源变得更加有限，所提出的系统在响应时间和住院时间方面能够适应并提供更大的益处。
