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。库存系统接收的产品比运送的多，会耗尽存储空间。接听电话的速度快于结束电话的速度，呼叫中心的等待时间变得无限长。如果医疗保健机构接受的新患者数量超过了其积极治疗的能力，就会出现拥堵和/或加班。使这些系统复杂化的是不确定性，因此设置容量等于需求是不够的，并导致需要将闲置容量作为缓冲。这个缓冲对可持续性和性能至关重要，但通常设置较低，以尽量减少“未使用”的容量。其中，确定缓冲区的大小和设计更聪明的方法（例如池化）来减少使用是设计可持续系统的重大挑战。**该研究项目将侧重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病人流动、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情况。通过研究其他服务行业的成功案例，我们相信基于排队的方法有望开发出这样的方法。排队理论特别适合描述和设计一般情况下的系统。这样的结果通常跨越应用领域，可以提供一般的见解和概述具体的行动方案。这在电信行业和最近的呼叫中心的研究和设计中都可以看到。尽管医疗保健具有高度随机性和日益增长的需求，但使用排队理论来支持加拿大医疗保健系统并不常见。医疗保健的服务特点是独特的，需要开发新的排队模型和方法。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.****