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

ERI：紧急医疗服务和其他急救系统的工作负载知情操作

• 批准号: 2138995
• 负责人: Laila Cure Vellojin
• 金额: $ 19.99万
• 依托单位: Wichita State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2138995&HistoricalAwards=false
• 关键词: ERI; Workload; Informed; Operations; Emergency

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.

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）专业人员和其他第一响应者提供公平工作系统的研究。EMS系统旨在通过响应911呼叫来挽救需要医院外紧急医疗护理的患者的生命。 这些专业人员往往长时间轮班工作，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，导致压力，倦怠和高水平的自然减员。 由此造成的美国护理人员短缺危及响应紧急呼叫的能力，并使生命处于危险之中。这项研究将评估EMS机组人员在真实的时间所经历的工作量，并将其纳入运营决策，如呼叫覆盖范围，任务和机组切换，EMS系统内。预计改善的运营环境将减少EMS专业人员中与工作有关的自然减员，从而确保社区获得高质量的院外紧急医疗保健，同时促进第一反应者的福祉。这项研究将影响工作系统科学的学科，通过改变工作如何测量和设计涉及高度可变，非重复性任务的工作，这些任务构成了当今美国的许多职业。 本研究将从一线人员的角度研究EMS操作，1）开发新的方法来近似个人工作量使用常规收集的过程数据，2）定义和建模新的实时操作策略，以平衡工作量之间的船员在一个班次。这项研究将开发和验证一种方法，实时工作负载评估的基础上跟踪驱动的模拟观察到的调度模式与任务分析数据增强。研究的工作量平衡策略包括：利用随机动态规划技术和基于需求预测的异构机组配置策略，通过轮班内机组交换来提高机组成员的工作量水平。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的机会。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，进入研究团队。在这个项目中开发的方法将被整合到PI提供的工作系统和数据挖掘课程中，并将用于通过与威奇托州立大学的乌尔里希艺术博物馆合作为社区外展活动创建材料。这个奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。