Employing Operations Research to Improve Health Care Resource Utilization and Planning

我的总体目标是将运筹学方法应用于尚未解决的新问题，并扩大这些方法的范围，以解决新的关系、约束或其他系统参数，以开发可用于为决策提供信息并提高卫生保健系统效率的量化、基于证据的工具。特别是，我寻求开发工具，以支持改善卫生保健资源的使用、规划和可获得性。 在接下来的五年里，我的目标是特别关注系统动力学(SD)建模的应用、范围和方法。SD是一种随机、连续的建模方法，它将系统模拟为一系列库存和流动，实体队列通过这些库存和流动；这些流动可能会受到反馈循环的影响。这种强大的计算机模拟方法尚未在卫生保健部门得到广泛应用；因此，无论是在新的应用领域还是在改进建模方法方面都有很大的机会。 我建议的研究计划将包括至少四项主要的SD研究，包括(1)加拿大整形外科医生队伍的模型；(2)磁共振成像(MRI)资源需求和分配的模型；(3)全省骨关节炎(OA)患者流动模型；(4)萨斯卡通卫生区的癌症护理路径模型。这些研究中的每一项都扩大了可持续发展模型在各自领域的范围和用途。整形外科医生劳动力模型将在以前的外科医生劳动力模型的基础上进行扩展，包括需求积压、手术和临床需求相互作用以及提供者移民的影响。拟议的MR资源模型也将是新颖的，因为尚未使用可持续发展开发出这种资源分配模型。OA模型是第一个将共病和生活质量结果包括在病人流动模型中的模型，该模型跨越了对慢性病的完整连续护理。癌症模型将是第一个模拟所有类型癌症患者流动的模型，也将是第一个纳入和模拟有限资源竞争以及由此导致的护理延误的模型。

My overall objective is to apply operations research methods to novel issues not yet addressed and extend the scope of these methods to address new relationships, constraints, or other system parameters for the purpose of developing quantitative, evidence based tools which can be used to inform decisions and improve the efficiency of the health care system. In particular, I seek to develop tools to support the improved use, planning and accessibility of health care resources. For the next five years, I aim to particularly focus on the application, scope and methods of system dynamics (SD) modelling. SD is a stochastic, continuous modelling method which simulates systems as a series of stocks and flows through which entity cohorts flow; the flows can be affected by feedback loops. This powerful computer simulation method has not been extensively applied within the health care sector; hence there is substantial opportunity for both new areas of application and for advancing modelling methods. My proposed research program will include at least four major SD research studies including (1) a model of the Canadian orthopaedic surgeon workforce; (2) a model for magnetic resonance imaging (MRI) resource demand and allocation; (3) a province-wide osteoarthritis (OA) patient flow model; and (4) a cancer care pathway model in the Saskatoon Health Region. Each of these studies expands the scope and use of SD modelling in their respective areas. The orthopaedic surgeon workforce model will expand on previous surgical workforce models by including the effects of demand backlogs, surgery and clinical demand interactions, and provider emigration. The MR resource model proposed will also be novel, as no such resource allocation model has yet been developed using SD. The OA model is the first to include co-morbidities and quality of life outcomes in a patient flow model spanning the complete continuum of care for a chronic condition. The cancer model will be the first to simulate the flow of all types of cancer patients, and will be the first to incorporate and simulate the competition that exists for constrained resources and the resulting delays in care.