Exploiting new and abundant healthcare data to develop novel operational research methodologies

几十年来，与医疗保健服务相关的复杂性和挑战已被证明是实践运筹学 (OR) 和工业工程的一个富有成效的领域。研究项目和成果推进了这些学科的科学发展并改善了医疗保健系统。随着医疗保健提供商在数据分析（基础设施和专业人力资源）方面投入更多资金，并继续寻求大学帮助应对最复杂的挑战，这种伙伴关系的重要性将会日益增强。 医疗保健组织正在以惊人的速度创建数据 - 医疗保健数据量大约每 36 个月就会翻一番。这些数据有望改变决策的制定方式和医疗保健的提供方式。目前，数据量和所交付的改进量之间存在脱节。如何使用 OR 来利用新的、丰富的医疗数据源来做出更好的决策是本研究提案的首要目标。具体来说，在本提案中，我们正在研究：1）如何使用数据更准确地描述待研究系统（例如患者流动模式）以及2）如何使用数据更准确地描述随机变量。 因此，我们可以在更容易理解的系统结构上磨练我们的 OR 模型，并减少不确定性。 通过这个过程，我们希望为更好的医疗决策提供信息，推进 OR 方法，并比较、对比和结合分析和 OR 方法。 整合数据、分析和 OR 的总体方法将为希望利用新可用数据的其他研究人员和医疗保健组织提供一个框架。该研究计划的动机是医疗保健提供者面临的实际问题，因此将继续对新斯科舍省和世界各地的医疗保健服务产生积极影响。由于医疗保健问题需要不同的 OR 方法，该研究计划将通过识别新问题和开发新的解决方法来继续推进 OR 科学。

The complexity and challenges associated with healthcare delivery has proved a fruitful area to practice Operational Research (OR) and Industrial Engineering for several decades. Research projects and outputs have advanced the science of these disciplines and improved healthcare systems. The importance of this partnership is poised to grow as healthcare providers invest more in data Analytics (infrastructure and professional human resources) and continue to look to universities to help with their most complex challenges. Healthcare organizations are creating data at a fascinating pace - the volume of healthcare data doubles approximately every 36 months. This data promises to transform how decisions are made and how healthcare is delivered. There currently exists a disconnect between the amount of data and the amount of improvement being delivered. How to use OR to capitalize on new and abundant sources of healthcare data for making better decisions is the overarching thrust of this research proposal. Specifically, in this proposal we are investigating: 1) how to use data to more accurately describe the system understudy (e.g. patient flow patterns) and 2) how to use data to more accurately describe stochastic variables. As such we can hone our OR models in on better understood system structures with less uncertainty. Through this process, we expect to inform better healthcare decisions, to advance OR methods, and to compare, contrast, and combine Analytics and OR methodologies. The overall approach to incorporating data, Analytics and OR will provide a framework for other researchers and healthcare organizations looking to capitalize on newly available data. This program of research is motivated by real problems faced by healthcare providers and as such, will continue to positively impact healthcare delivery in Nova Scotia and around the world. As healthcare problems require different OR methods, this research program will continue to advance the science of OR by identifying new problems and developing novel solution approaches.