Establishing generic problem structures and repeatable solution approaches for healthcare delivery problems

设计长期可行（即可持续）的系统是许多行业面临的问题。库存系统收到的产品比他们运送的产品多，会耗尽空间。呼叫中心接收呼叫的速度比结束呼叫的速度快，等待时间无限增长。接受比他们能够积极治疗的更多新患者的医疗保健实践将经历拥塞和/或超时。不确定性使这些系统复杂化，因此，将能力设定为等于需求是不够的，并导致需要将闲置能力作为缓冲。这一缓冲对于可持续性和性能至关重要，但通常设置得较低，以尽量减少"未使用"的容量。除其他外，确定这一缓冲区的大小和设计聪明的方法（例如汇集），以获得更少的是设计可持续系统的重大挑战。该研究计划将专注于设计可持续的医疗保健服务系统。具体来说，我们将解决许多医院常见的患者流量、拥挤和容量规划问题。为了扩大运筹学对这些问题的影响，我们将制定全面的问题定义和结构，使解决方案的方法适用于多种环境。通过研究其他服务行业的成功案例，我们认为基于服务的方法很有希望发展这样的方法。认知理论特别适合于描述和设计一般环境下的系统。这些结果通常跨越应用领域，可以提供一般性见解并概述具体的行动方案。这在电信行业以及最近在呼叫中心的研究和设计中已经看到。尽管医疗保健的高度随机性和不断增长的需求，使用的假设理论来支持加拿大的医疗保健系统是不常见的。医疗保健的服务特性是独特的，需要开发新的服务模式和方法。从这项研究中，对具体干预措施的一般见解和建议将有助于设计可持续的医疗保健系统。

Designing systems that are viable over the long term (i.e. sustainable) is a problem faced in many industries. Inventory systems which receive more products than they ship run out of space. Call centres receiving calls faster than they end calls see waiting times grow unbounded. Healthcare practices that accept more new patients than they can actively treat will experience congestion and/or overtime. Complicating these systems is uncertainty, thus setting capacity equal to demand is insufficient and results in the need to incorporate idle capacity as a buffer. This buffer is crucial for sustainability and performance but is often set low in order to minimize "unused" capacity. Among others, determining the size of this buffer and designing clever ways (e.g. pooling) to get by with less are substantial challenges to designing sustainable systems. This research program will focus on designing sustainable healthcare delivery systems. Specifically we will solve patient flow, congestion and capacity planning problems that are common in many hospitals. To broaden the impact of operations research on these problems, we will develop comprehensive problem definitions and structures such that the solutions methodologies are applicable in multiple settings. From studying successes in other service industries, we believe that a queueing based approach is promising for developing such methodologies. Queueing theory is particularly apt at characterizing and designing systems for general settings. Such results typically span application areas and can provide general insights and outline specific courses of action. This has been seen in the telecommunications industry and more recently in the study and design of call centres. Despite the highly stochastic nature of healthcare and the growing need, the use of queueing theory to support the Canadian healthcare system is not commonplace. The service characteristics of healthcare are unique and will require the development of new queueing models and methodology. From this research, general insights and recommendations for specific interventions will contribute to the design of a sustainable healthcare system.