Methods and analytical tools to optimize patient flow

在本建议中，我将重点介绍医疗保健系统中与患者流相关的应用程序。患者流问题可以描述为：患者一次到达一个系统，等待预约。这个预约通常定义了他们访问的开始时间（或他们治疗的开始日期）。一个病人可能有多个预约。每个病人都有一个事先不知道的档案。概要文件被定义为一组活动和每个活动的持续时间。一个或多个资源可以执行每个活动，并且一些活动具有优先级约束。每天可能会发生一个或多个活动：它们可以一个接一个地被安排（单个约会），也可以一次全部安排（多个约会）。这些活动通常与资源有关，必须对这些资源进行安排，以确保患者能够获得这些资源。由于缺乏对这些有限资源的协调，往往会造成患者延误和瓶颈。病人的到达时间、护理需求和服务时间通常是未知的。

In this proposal, I will focus on applications related to patient flow in the healthcare system. The patient flow problem can be described as follows: Patients arrive in the system one at a time and wait for an appointment. This appointment usually defines the start time of their visit (or the start day of their treatment). One patient may have multiple appointments. Each patient has a profile that is not known in advance. The profile is defined as a set of activities and a duration time for each activity. One or more resources may perform each activity, and some activities have precedence constraints. Each day one or more activities may occur: they may be scheduled one after the other (single appointment) or all at once (multiple appointments). The activities are often related to resources, which must be scheduled to ensure their availability to the patients. Patient delays and bottlenecks are often caused by a lack of coordination of these limited resources. The arrival times, care needs, and service times of the patients are usually unknown. Patient flow problems are difficult to solve. Analysis of the literature shows that: 1) Most research focuses on single-resource scheduling and considers that the demand is known; 2) Uncertainty is poorly integrated and exploited; 3) Patient and resource scheduling problems are often solved sequentially and independently; and 4) Exact approaches have reached their limits when both problems are integrated. While it is not always possible to address these issues simultaneously, my research program aims to work towards addressing the patient flow problem as a whole (for an effective and integrated health system). To address these challenges, my research will be divided into three themes: A) dedicated algorithms for “partially” integrated patient and resource scheduling; B) the search for approaches to more efficient metaheuristics; and C) the search for efficient methods to integrate the solutions of dedicated algorithms. The projects in these areas aim to both tackle practical problems arising in the healthcare system, and to develop innovative methodological approaches that will advance knowledge and contribute to science. One of the objectives of this research is to provide state-of-the-art tools and good practices that can be used by the healthcare industry all over Canada. This research will benefit healthcare decision makers (and therefore the patients) through wait time reduction and facilitated access for patients. It should be able to relieve congestion in clinics and hospitals. My current network of collaborations allows me to have a privileged access to the data, knowledge of the challenges encountered in practice and a validation field for the algorithms. Finally, students that will participate in this research will gain experience in collaborating with industry. They will acquire expertise in the both of research and practice that will be of great assistance in their careers.