Data Awareness for Sending Help (DASH)

该项目探讨了新的和正在出现的数据源的整合，以便对应急反应产生潜在影响。在紧急医疗情况下，救护车必须尽快到达有需要的人那里，以便提供护理，并最终挽救生命。需要迅速决定哪辆救护车应对每起事故。然而，做出这样的决定是复杂的：事件可能在很大的区域内同时或短时间内发生;救护车的位置不断变化;并且有许多环境因素会影响响应时间，例如交通和天气条件。在这样一个复杂和动态的环境中，通常安装一种称为计算机辅助调度的自动化决策支持形式，以帮助工作人员做出这些决定，近年来，可能与计算机辅助调度相关联的数据源的数量和类型急剧增加，为改进当前的决策支持系统提供了新的可能性。这样做可以使救护车在紧急情况发展时更快地做出反应，改善紧急护理，降低成本，提高效率并改善患者的健康状况。可能有用的数据可能来自以下任何来源：（通过社交媒体和其他移动的应用程序）;特定用户群（通过家用/可穿戴传感器，特别是针对高危患者群体）;城市基础设施（通过公共交通监控器、嵌入式道路传感器或气象站）;和其他公共部门行为者（如合作的应急响应机构或医疗保健提供者）。这项拟议的政策示范项目，题为“数据意识发送帮助”（DASH），旨在探讨这些“新资料来源在改善救护车召达时间方面的潜力。该项目建立在国王学院伦敦（KCL）和伦敦救护车服务（LAS）之间的一项新的研究合作基础上，该研究正在评估基于历史LAS系统日志模拟救护车呼叫的救护车调度新方法。DASH将通过预测由于集成额外数据源而导致的响应时间的变化，为在重要的新方向上扩展这一初步研究奠定基础。DASH旨在解决许多挑战，包括技术方面的挑战，即可靠地访问和使用新数据源的可行性，以及社会或道德方面的挑战，即以这种方式使用数据的可接受性和适当性，尤其是关于个人的数据。DASH提出了三个具体的研究问题：（1）将新的和新兴的数据源与应急响应联系起来，对应急服务机构、医疗保健提供者和公众有什么好处和风险？全面的文献审查和有针对性的重点小组将突出可以利用哪些新的数据来源，并将权衡与各部门的数据强化应急反应有关的效益、成本和风险。(2)将新的和新兴的数据源连接到CAD技术以提供最重要的好处所涉及的技术挑战是什么？技术调查将考虑将新的数据源与计算机辅助设计联系起来的实际问题，并将探讨可以低成本、高影响力和安全方式应用的创新建模方法。(3)从业者和政策制定者如何从我们将新的和新兴的数据源与伦敦救护车服务联系起来的研究中学习？DASH将产生一组旨在告知从业者和政策制定者的输出，包括：概述我们的研究结果的政策简报;评估将新数据和相关方法与LAS的CAD系统联系起来的案例研究;建立在以前工作基础上的软件原型，演示数据增强的CAD系统如何工作;以及关于调查结果对英国其他应急响应机构的更广泛适用性的报告。

This project explores integration of new and emerging data sources for potential impact on emergency response. In an emergency medical situation, ambulances must get to those in need as quickly as possible in order to provide care and, ultimately, to save lives. Decisions about which ambulance should respond to each incident need to be made rapidly. However, making such decisions is complicated: incidents can occur simultaneously or in short succession over a wide area; the locations of ambulances are constantly changing; and there are many environmental factors that can affect response times, such as traffic and weather conditions. In such a complex and dynamic environment, a form of automated decision support, known as computer assisted dispatch (CAD), is often installed to help staff make these decisions.In recent years, there has been a sharp expansion in the volume and types of data sources that might potentially be linked to CAD, presenting new possibilities for improving current decision-support systems. Doing so could enable ambulances to respond faster as emergency situations develop, improving emergency care, lowering costs, increasing efficiency and improving health outcomes for patients. Potentially useful data might come from any of the following sources: the general population (via social media and other mobile Apps); specific user segments (via in-home/wearable sensors, particularly for high-risk patient groups); urban infrastructure (via public transport monitors, embedded road sensors or weather stations); and other public sector actors (such as collaborating emergency response agencies or healthcare providers).This proposed Policy Demonstrator Project, entitled "Data Awareness for Sending Help" (DASH), aims to explore the potential of these "new data" sources for improving ambulance response times. The project builds on a new research collaboration between King's College London (KCL) and the London Ambulance Service (LAS), which is evaluating novel methods for ambulance dispatch by simulating ambulance call-outs based on historical LAS system logs. DASH will lay the groundwork for extending this preliminary study in important new directions, by predicting changes in response times due to integration of additional data sources.There are a number of challenges that DASH aims to address, both technical, in terms of how feasible it is to access and use new data sources reliably, and social or ethical, in terms of how acceptable and appropriate it is to use data in this way, particularly data about individuals. DASH asks three specific research questions:(1) What are the benefits and risks for emergency service agencies, healthcare providers and the public related to linking new and emerging data sources to emergency response? A comprehensive literature review and targeted focus groups will highlight which new data sources could be tapped and will weigh benefits, costs and risks associated with data-enhanced emergency response, across various sectors.(2) What are the technical challenges involved in linking new and emerging data sources to CAD technologies to provide the most important benefits? A technical investigation will consider practical aspects of linking new data sources to CAD and will explore innovative modelling methods that could be applied in a low-cost but high-impact and secure manner.(3) How can practitioners and policymakers learn from our study of linking new and emerging data sources to the London Ambulance Service? DASH will produce a set of outputs designed to inform practitioners and policymakers, including: a Policy Brief outlining our findings; a Case Study that assesses linking new data and associated methodologies to LAS's CAD system; a Software Prototype, built on previous work, that demonstrates how a data-enhanced CAD system might work; and a report on the broader applicability of the findings to other emergency response agencies in the UK.