Handbook of Healthcare Analytics

"This handbook provides a broad healthcare context for operational research/management science (OR/MS) researchers with an encyclopedic account of the most vexing international healthcare issues. In addition, the handbook features a practical guide for OR/MS researchers to learn the most important quantitative research tools in conducting healthcare research, including classical OR techniques enhanced with game theory (such as queuing games); classical economics methods enhanced by operational considerations (like matching markets); econometrics; and data-science methods (from statistics and machine learning). Over the past decade, a lively discussion on healthcare has touched virtually every stakeholder with the system, and three key issues have emerged from this discussion: cost, quality, and access, which are jointly referred to as the "iron triangle" of healthcare. There is an urgent need to study these three "big issues", and OR/MS researchers can contribute to this need given that so much has been done in analyzing and solving supply-demand mismatch problems of virtually any scale. This book fills a current gap in the healthcare operations management literature by focusing on the incentives issues in healthcare operations from an operations management. This focus on operations-level modeling is unique and needed since the current focus has been on applications of operations research techniques to specific healthcare scenarios, such as nurse scheduling, appointment scheduling, facility design, and patient flow management. Topical coverage includes: operations research tools with healthcare applications; economics tools with healthcare applications; econometrics tools with healthcare applications; data science tools with heathcare applications; healthcare analytics for patients; healthcare analytics for policy-makers; healthcare analytics for hospitals; healthcare analytics for clinicians; healthcare analytics for global health; healthcare operations for patient outcomes; changing faces of healthcare systems; data science opportunities and emerging techniques; and quantitative teaching cases"--