Methods and analytical tools to optimize patient flow

在本提案中，我将重点介绍与医疗保健系统中的患者流相关的应用程序。病人流动问题可以描述为：病人一次一个地到达系统，等待预约。这种预约通常定义他们探视的开始时间(或他们治疗的开始日期)。一名患者可能会有多个预约。每个患者都有一个事先不知道的个人资料。配置文件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，并且某些活动具有优先约束。每天可能发生一项或多项活动：它们可以一个接一个地安排(单一预约)或一次性安排(多个预约)。这些活动通常与资源有关，必须对资源进行安排，以确保患者可以使用这些资源。患者延误和瓶颈往往是由于这些有限的资源缺乏协调造成的。病人的到达时间、护理需求和服务时间通常是未知的。病人流动问题很难解决。对文献的分析表明：1)大多数研究集中在单一资源调度上，认为需求是已知的；2)不确定性没有得到很好的整合和利用；3)病人和资源调度问题往往是按顺序独立解决的；4)当这两个问题整合时，精确的方法已经达到了极限。虽然并不总是可以同时解决这些问题，但我的研究计划旨在努力解决患者流动问题作为一个整体(为了一个有效和集成的卫生系统)。为了应对这些挑战，我的研究将分为三个主题：A)“部分”整合患者和资源调度的专用算法；B)寻找更有效的元启发式方法；以及C)寻找有效的方法来整合专用算法的解决方案。这些领域的项目旨在解决医疗保健系统中出现的实际问题，并开发创新的方法方法，以促进知识和对科学的贡献。这项研究的目标之一是提供最先进的工具和良好做法，可供加拿大各地的医疗保健行业使用。这项研究将通过减少等待时间和为患者提供便利，使医疗决策者(因此也是患者)受益。它应该能够缓解诊所和医院的拥堵。我目前的合作网络使我能够特权地访问数据，了解实践中遇到的挑战，并为算法提供验证领域。最后，将参与这项研究的学生将获得与行业合作的经验。他们将获得研究和实践方面的专业知识，这将对他们的职业生涯有很大帮助。

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.