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

点击翻译按钮获取中文摘要

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.