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Healthcare Management Engineering: What Does This Fancy Term Really Mean: The Use of Operations Management Methodology for Quantitative Decision-Making in Healthcare Settings

Kolker, Alexander
Healthcare Management Engineering: What Does This Fancy Term Really Mean: The Use of Operations Management Methodology for Quantitative Decision-Making in Healthcare Settings Cover Image
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Book Information
Edition: 1st
Publisher: Springer Nature
ISBN: 1-4614-2067-9 (1461420679)
ISBN-13: 978-1-4614-2067-5 (9781461420675)
New Edition: 3-031-53662-2
Binding: Softcover
Copyright: 2012
Publish Date: 01/12
Weight: 0.47 Lbs.
Pages: 121
Subject Class: M-A (Medical Administration and Health Policy)
Remarks:
A New Edition of this title is due 04/24
Return Policy: Returns accepted up to 12 months provided no other recalls or return restrictions apply.
Table Of Contents: View
Contributing Authors: View
 
Class Specifications
ISSN Series: Springer Briefs in Health Care Management and Economics
Discipline: Medical Prof
Subject Definition: Delivery of Health Care, Integrated-Organ & Admin
NLM Class: W 84
LC Class: RA971
Abstract: This Briefs Series book illustrates in depth a concept of healthcare management engineering and its domain for hospital and clinic operations. Predictive and analytic decision-making power of management engineering methodology is systematically compared to traditional management reasoning by applying both side by side to analyze 26 concrete operational management problems adapted from hospital and clinic practice. The problem types include: clinic, bed and operating rooms capacity; patient flow; staffing and scheduling; resource allocation and optimization; forecasting of patient volumes and seasonal variability; business intelligence and data mining; and game theory application for allocating cost savings between cooperating providers. Detailed examples of applications are provided for quantitative methods such as discrete event simulation, queuing analytic theory, linear and probabilistic optimization, forecasting of a time series, principal component decomposition of a data set and cluster analysis, and the Shapley value for fair gain sharing between cooperating participants. A summary of some fundamental management engineering principles is provided. The goal of the book is to help to bridge the gap in mutual understanding and communication between management engineering professionals and hospital and clinic administrators. The book is intended primarily for hospital/clinic leadership who are in charge of making managerial decisions. This book can also serve as a compendium of introductory problems/projects for graduate students in Healthcare Management and Administration, as well as for MBA programs with an emphasis in Healthcare.

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