Data Awareness for Sending Help (DASH)

该项目探索整合新的和新兴的数据源，以期对应急响应产生潜在影响。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，并最终拯救生命。关于哪辆救护车应该对每个事故做出反应的决定需要迅速做出。然而，做出这样的决定是复杂的：事件可能在大范围内同时或短时间接连发生；救护车的位置不断变化；以及许多环境因素可能会影响反应时间，如交通和天气状况。在这样一个复杂和动态的环境中，经常安装一种形式的自动化决策支持，称为计算机辅助调度(CAD)，以帮助员工做出这些决策。近年来，可能与CAD相关联的数据源的数量和类型急剧扩大，为改进现有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做出更快的反应，改善紧急护理，降低成本，提高效率，并改善患者的健康状况。潜在有用的数据可能来自以下任何来源：普通人群(通过社交媒体和其他移动应用程序)；特定用户群(通过室内/可穿戴传感器，尤其是高风险患者群体)；城市基础设施(通过公共交通监视器、嵌入式道路传感器或气象站)；以及其他公共部门参与者(如合作的紧急响应机构或医疗保健提供者)。这项拟议的政策示范项目名为“发送帮助的数据意识”(DASH)，旨在探索这些“新数据”来源在改善救护车响应时间方面的潜力。该项目建立在伦敦国王学院(KCL)和伦敦救护车服务(LAS)之间的一项新的研究合作基础上，LAS正在评估救护车调度的新方法，方法是基于LAS系统历史日志模拟救护车呼叫。DASH将为将这项初步研究扩展到重要的新方向奠定基础，预测由于整合其他数据源而导致的响应时间的变化。DASH旨在解决一些挑战，包括可靠地访问和使用新数据源的可行性方面的技术挑战，以及以这种方式使用数据，特别是关于个人数据的可接受性和适当性方面的社会或伦理挑战。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？全面的文献回顾和有针对性的焦点小组将强调哪些新的数据源可以被利用，并将权衡与数据增强的应急响应相关的好处、成本和风险。(2)将新的和新兴的数据源与CAD技术联系起来以提供最重要的好处涉及哪些技术挑战？技术调查将考虑将新数据源连接到CAD的实际方面，并将探索可以以低成本但高影响和安全的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连接到伦敦救护车服务的研究中学习？DASH将产生一套旨在为从业者和政策制定者提供信息的产出，包括：概述我们的发现的政策简报；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；在以前工作的基础上构建的软件原型，展示数据增强型CAD系统可能如何工作；以及关于这些发现对英国其他应急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.