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

这一早期概念探索性研究(AGUGER)奖为医院急诊科(ED)建立可改进分析理论提供了资金。具体地说，它打算开发分析方法，通过对患者流进行建模和分析，重新分配有限的资源，以及通过识别和缓解瓶颈，来改进急诊工作的绩效。研究的方法将基于对描述急诊室病人流动的随机过程的分析研究。从产生式系统延伸而来的系统论方法将ED建模为一个复杂的网络。本研究的挑战在于寻找急诊室复杂性的适当表征，发现导致系统最优配置的指标，并根据从临床信息系统获得的实时数据识别瓶颈。如果研究成功，本研究结果将建立一种新的分析方法来研究急诊室的病人流。这种方法可让我们评估急症室的表现、找出瓶颈、最佳地分配资源，以及制订运作政策，以达致纾缓挤迫和提供最佳护理质素的目标。这项研究的成功完成将导致卫生保健系统研究的新方法。这将为医院整体的综合研究和医疗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可变性、高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 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.