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

EARLY概念探索性研究（EAGER）奖为医院急诊科（艾德）建立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，可用于提高艾德的性能，通过建模和分析的病人流量，重新分配有限的资源，并通过识别和缓解瓶颈。研究的方法将是基于随机过程的分析调查，描述了病人流量在ED。一个系统理论的方法，从生产系统扩展，将被用来模拟艾德作为一个复杂的网络。本研究的挑战在于找到合适的表征艾德的复杂性，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，本研究的结果将建立一种新的分析方法来研究急诊患者流。这种方法将使我们能够评估艾德的性能，识别瓶颈，最佳分配资源，并设计业务政策，以减少拥挤和实现最佳护理质量。这项研究的成功完成将为医疗保健系统的研究带来新的方法。这将为医院整体的综合研究和医疗保健供应链研究提供坚实的基础。最后，所获得的结果将不仅适用于医疗保健系统，而且也适用于其他系统的高可变性，服务成本和高成本的故障，如民事应急响应系统，关键供应链，信息网络等。

This EArly-concept Grant for Exploratory Research (EAGER) award 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.