Service Operations Management

本研究将探讨统计和数学模型，以告知一般和紧急医疗服务（EMS）系统的排队系统的规划和管理。我们将研究预测EMS呼叫量随时间和空间变化的方法，系统负载影响护理人员在紧急情况现场花费的时间以及他们是否将患者运送到医院的方式，以及平衡城市急诊部门EMS负载的方法。在更一般的层面上，我将制定和分析排队等候的数学模型，该模型结合了最近的实证研究结果，表明客户和服务器会根据负载的变化调整他们的行为。例如，服务器最初会随着负载的增加而加速，但如果负载长时间保持高水平，则最终会由于疲劳而减慢速度。另一个例子是，服务器可能会在轮班结束时改变他们的行为。我还将研究将实证发现转化为可用于支持规划的易于处理的数学模型的过程。在学术层面上，本研究计划将有助于运筹学、医疗保健和服务部门的运营管理以及EMS计划和管理领域。它将解决关于排队系统的实证研究（量化平均服务时间如何取决于各种因素）和排队系统的数学模型（根据服务率制定）之间相互作用的基本问题。在实践层面上，本研究将有助于发展EMS系统和其他服务系统的改进规划方法。在加拿大和其他地方，特别是接受紧急护理的病人和一般接受服务的顾客将受益于更有效和高效地匹配供需的规划。

This research  will investigate statistical and mathematical models to inform planning and management of systems of waiting lines in general and emergency medical services (EMS) systems in particular.  We will investigate methods to forecast EMS call volumes over time and space, the way in which system load impacts the time paramedics spend at the scene of an emergency and whether they transport the patient to a hospital, and methods to balance EMS load across the emergency departments in a city.  At a more general level, I will formulate and analyse mathematical models of waiting lines that incorporate recent empirical findings indicating that customers and servers adapt their behaviour in response to changes in load.  For example, servers initially speed up as load increases but eventually slow down due to fatigue if load remains high for an extended period.  As another example, servers might change their behaviour towards the end of their shift.  I will also study the process of translating empirical findings into tractable mathematical models that can be used to support planning. At an academic level, this research program will contribute to the fields of operations research, operations management in the healthcare and service sectors, and EMS planning and management.  It will address fundamental issues regarding the interplay between empirical studies of queueing systems, which quantify how mean service times depend on various factors, and mathematical models of queueing systems, which are formulated in terms of service rates. At a practical level, this research will contribute to the development of improved planning methods for EMS systems and other service systems. Patients receiving emergency care in particular and customers receiving service in general, in Canada and elsewhere, will benefit from planning that matches supply and demand more effectively and efficiently.