Handbook of Healthcare Analytics

How can analytics scholars and healthcare professionals access the most exciting and important healthcare topics and tools for the 21^st century'

Editors Tinglong Dai (Johns Hopkins) and Sridhar Tayur (Carnegie Mellon), aided by a team of internationally acclaimed experts, have curated this timely volume to help newcomers and seasoned researchers alike to rapidly comprehend a diverse set of thrusts and tools in this rapidly growing cross-disciplinary field. The Handbook covers macro-, meso- and micro-level thrusts, spanning organizational structure, market design, access to (and quality of) care, competing interests, personalized medicine, global health, organ transplantation, healthcare supply chains, ambulatory care, inpatient care, residential care and concierge medicine. No other book in the field matches its scope. It is also the first book to synthesize what has been a highly fragmented research area--an uncoordinated accumulation of papers--and to structure it into a coherent scientific discipline. As Poincare remarked, an accumulation of facts is no more a science than a heap of stones is a house.

The handbook also provides an easy-to-comprehend introduction to five essential research tools--Markov decision process, game theory and information economics, queueing theory (with and without game theory), econometric methods, and data sciences (including machine learning)--by illustrating their uses and applicability on examples from diverse healthcare settings, thus connecting tools with thrusts.

The primary audience of the Handbook includes analytics scholars interested in healthcare and healthcare practitioners interested in analytics. This Handbook:

• Instills analytics scholars with a way of thinking that incorporates behavioral, incentive, and policy considerations in various healthcare settings. This change in perspective--a shift in gaze away from narrow, local and one-off operational improvement efforts that do not replicate, scale or remain sustainable--can lead to new knowledge and innovative solutions that healthcare has been seeking so desperately.
• Facilitates collaboration between healthcare experts and analytics scholars--to frame and tackle their pressing concerns through appropriate modern mathematical tools designed for this very purpose--ranging from queuing models imbedded with game theory ( queuing games ) to game theory methods enhanced by operational considerations ( market design ), from tailored econometric methods to current day data-science methods that include algorithms from machine learning.

While the handbook is designed to be accessible to the independent reader, it may be used in a variety of settings, from a short lecture series on specific topics to a semester-long course covering the entire field.