EAGER: Improvability Theory for Hospital Emergency Department: A System-Theoretic Method to Reduce Crowding

这笔拨款为建立医院急诊科（ED）的可改进性分析理论提供资金。具体而言，它打算开发分析方法，可用于通过建模和分析患者流量，重新分配有限的资源，并通过识别和缓解瓶颈来提高急诊科的绩效。研究方法将基于对描述急诊科患者流动的随机过程的分析研究。从生产系统扩展而来的系统理论方法将用于将急诊科建模为一个复杂的网络。本研究的挑战在于找到ED复杂性的适当表征，发现导致最佳系统配置的指标，并根据临床信息系统获得的实时数据识别瓶颈。如果成功，本研究结果将建立一种新的分析方法来研究急诊科的患者流量。这种方法将使我们能够评估急诊科的绩效，识别瓶颈，优化资源分配和设计操作政策，以实现更少的拥挤和最佳的护理质量。这项研究的成功完成将导致卫生保健系统研究的新方法。它将为医院整体的综合研究和医疗保健供应链的研究提供坚实的基础。最后，所得结果不仅适用于卫生保健系统，也适用于其他具有高变异性、服务成本和高故障成本的系统，如民用应急响应系统、关键供应链、信息网络等。

This grant provides funding for the establishment of an analytical theory of improvability for the hospital's emergency department (ED). Specifically, it intends to develop analytical methods that can be used to improve the ED performance through modeling and analysis of patient flow, redistributing limited resources, and through identifying and mitigating bottlenecks. The approach of the research would be based on analytical investigation of the stochastic processes that describe the patient flow in ED. A system-theoretic method, extended from production systems, will be used to model ED as a complex network. The challenge of this research lies in finding appropriate characterization of the complexity in ED, discovering indicators leading to optimal system configurations, and identifying bottlenecks based on real-time data obtained from clinical information system.If successful, the results of this research will establish a novel analytical method to study patient flow in ED. Such a method will enable us to evaluate the ED performance, identify bottlenecks, distribute resources optimally and design operating policies to achieve less crowding and the best quality of care. The successful completion of this research will lead to new methodologies for health care systems research. It will provide a solid foundation for an integrated study of the hospital as a whole and for health care supply chain research. Finally, the results obtained will be applicable not only to health care systems but also to other systems with high variability, service cost and high cost of failure, such as civil emergency response systems, critical supply chains, information networks, etc.