ERI: Workload-Informed Operations for Emergency Medical Services and other First-Responder Systems

该奖项全部或部分由《2021年美国救援计划法案》（公法117-2）资助。该工程研究启动（ERI）奖支持为紧急医疗服务（EMS）专业人员和其他急救人员提供公平工作系统的研究。EMS系统旨在通过响应911呼叫来挽救医院外需要紧急医疗保健的患者的生命。这些专业人士倾向于长时间轮班工作，在此期间，他们可能会接触到各种各样的情况，包括创伤性事件。然而，EMS专业人员所经历的实际工作量并没有得到很好的理解，这导致了压力、倦怠和高水平的人员流失。由此导致的美国护理人员短缺危及对紧急呼叫作出反应的能力，使生命处于危险之中。本研究将实时评估EMS机组人员所经历的工作量，并将其纳入EMS系统内的业务决策，如呼叫覆盖、任务和机组切换。工作环境的改善预计将减少紧急医疗服务专业人员与工作有关的人员流失，从而确保社区获得高质量的院外紧急保健，同时促进急救人员的福祉。这项研究将通过改变工作人员如何测量和设计涉及高度可变、非重复性任务的工作，从而影响工作系统科学的学科，这些任务构成了当今美国许多职业。本研究将从一线人员的角度研究EMS操作，1)开发新方法，使用常规收集的过程数据来估计个人工作量，2)定义和建模新的实时操作策略，以平衡轮班内机组人员的工作量。本研究将开发并验证一种实时工作量评估方法，该方法基于对观察到的调度模式的跟踪驱动模拟，并辅以任务分析数据。要研究的工作负载平衡策略包括使用随机动态规划技术的轮班内机组交换来平衡机组人员的工作量，以及基于需求预测的异构机组配置策略。该项目将为来自工业、系统和制造工程系的研究生和本科生团队提供机会，通过数据收集、分析和报告活动，与EMS专业人员和决策者合作。PI致力于招募和指导来自不同背景的学生，特别是女性和西班牙裔学生进入研究团队。该项目开发的方法将集成到PI提供的工作系统和数据挖掘课程中，并将通过与威奇托州立大学乌尔里希艺术博物馆合作，用于创建社区外展活动的材料。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).This Engineering Research Initiation (ERI) award supports research enabling a fair work system for Emergency Medical Service (EMS) professionals and other first responders. EMS systems aim at saving the lives of patients needing emergency health care outside the hospital by responding to 911 calls. These professionals tend to work long shifts during which they may be exposed to a great variety of situations, including traumatic events. However, the actual workload experienced by EMS professionals is not well understood, leading to stress, burnout, and high levels of attrition. The resulting shortage of paramedics in the United States endangers the ability to respond to emergency calls and puts lives at risk. This research will assess the workload experienced by EMS crewmembers in real time and incorporate that into operational decision-making, such as call coverage, task and crew switching, within EMS systems. An improved operating environment is expected to lead to a reduction in work-related attrition among EMS professionals, thereby ensuring that the community receives high-quality emergency out-of-hospital health care while promoting the well-being of first responders. This research will impact the discipline of work systems science by transforming how work one measures and designs work involving highly variable, non-repetitive tasks, which constitute many of today’s occupations in the United States. This research will study EMS operations from the perspective of frontline personnel by 1) developing new methods to approximate individual workload using routinely collected process data, and 2) defining and modeling new real-time operational strategies to balance workload among crewmembers within a shift. This research will develop and validate a methodology for real-time workload assessment based on trace-driven simulation of observed dispatch patterns augmented with task analysis data. The workload-balancing strategies to be investigated include intra-shift crew swapping to level crewmembers’ workload using stochastic dynamic programming techniques and a heterogeneous crew configuration strategy based on demand prediction. The project will provide a team of graduate and undergraduate students from the Department of Industrial, Systems and Manufacturing Engineering with the opportunity to collaborate with EMS professionals and decision-makers through data collection, analysis and reporting activities. The PI is committed to recruiting and mentoring students from diverse backgrounds, particularly women and Hispanic, into the research team. The methods developed in this project will be integrated into Work Systems and Data Mining courses offered by the PI, and will be used to create materials for community outreach activities through collaboration with Wichita State University’s Ulrich Museum of Art.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.