000			03874nam a22004935i 4500
001			978-1-4614-2068-2
003			DE-He213
005			20140220083244.0
007			cr nn 008mamaa
008			111130s2012 xxu| s |||| 0|eng d
020			_a9781461420682 _9978-1-4614-2068-2
024	7		_a10.1007/978-1-4614-2068-2 _2doi
050		4	_aRA5
072		7	_aMBPM _2bicssc
072		7	_aMED002000 _2bisacsh
072		7	_aMED043000 _2bisacsh
082	0	4	_a353.6 _223
100	1		_aKolker, Alexander. _eauthor.
245	1	0	_aHealthcare Management Engineering: What Does This Fancy Term Really Mean? _h[electronic resource] : _bThe Use of Operations Management Methodology for Quantitative Decision-Making in Healthcare Settings / _cby Alexander Kolker.
264		1	_aNew York, NY : _bSpringer New York, _c2012.
300			_aXIX, 121p. 26 illus., 20 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringerBriefs in Health Care Management and Economics
505	0		_aTraditional Management and Management Engineering -- Dynamic Supply and Demand Balance Problems -- Linear and Probabilistic Resource Optimization and Allocation Problems -- Forecasting of Time Series -- Business Intelligence and Data Mining -- The Use of Game Theory -- Summary of Some Fundamental Management Engineering Principles -- Concluding Remarks.
520			_aThis 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.
650		0	_aMedicine.
650		0	_aPractice of medicine.
650		0	_aBiomedical engineering.
650		0	_aIndustrial management.
650	1	4	_aMedicine & Public Health.
650	2	4	_aHealth Administration.
650	2	4	_aManagement/Business for Professionals.
650	2	4	_aBiomedical Engineering.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781461420675
830		0	_aSpringerBriefs in Health Care Management and Economics
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-4614-2068-2
912			_aZDB-2-SME
999			_c101194 _d101194