Preface	6
	Contents	9
	About the Editors	12
	Part I Overview	13
	1 A Taxonomy of Operations Research Studies in Healthcare Management	14
	1.1 Introduction	14
	1.2 OR Studies in Healthcare Management	15
	1.3 Necessity for a Taxonomy: A Discussion	16
	1.4 A Taxonomy for OR Studies in Healthcare Management	18
	1.5 Results of the Taxonomy with Selected Articles	18
	1.6 Conclusions and Further Suggestions	21
	Appendix	21
	References	26
	2 A Comprehensive Survey on Healthcare Management	33
	2.1 Introduction	33
	2.2 Sub-classifications of HCM Studies	34
	2.2.1 HCM Papers Making Literature Review	36
	2.2.2 Quantitative and Qualitative Techniques in HCM	37
	2.2.3 Case Studies in HCM	38
	2.2.4 Performance Measurement in HCM	39
	2.3 Classification of Techniques Used in Healthcare Management	39
	2.3.1 Simulation	39
	2.3.2 Multicriteria Decision Making	43
	2.3.3 Mathematical Programming	43
	2.3.4 Probabilistic and Statistical Decision Making	45
	2.3.5 Data Envelopment Analysis (DEA)	46
	2.3.6 Data Mining (DM)	46
	2.3.7 Economic Decision Making and Engineering Economics	47
	2.3.8 Human Factors Engineering	48
	2.3.9 Structural Equation Modeling (SEM)	48
	2.3.10 Design of Experiments (DOE)	49
	2.3.11 System Dynamics	49
	2.3.12 Qualitative Approaches	50
	2.3.13 Other Approaches	51
	2.3.13.1 Cost Analysis in Healthcare	51
	2.3.13.2 Quality in Healthcare	51
	2.3.13.3 Information Technologies in Healthcare	52
	2.3.13.4 Tactical and Strategic Decision-Making in Healthcare	53
	2.3.13.5 Lean Management in Healthcare	53
	2.3.13.6 Environmental Management in Healthcare	54
	2.3.13.7 Risk Analysis in Healthcare	54
	2.4 Conclusions	54
	References	55
	Part II Medical Units in Hospital	62
	3 The Real Time Management of Operating Rooms	63
	3.1 Introduction	63
	3.2 The Management of Elective and Non-elective Patients	66
	3.3 Ex-Ante Approach: The Online Solution	67
	3.3.1 The RTM with only Elective Patients	67
	3.3.2 The RTM with Elective and Non-elective Patients	69
	3.4 Ex-Post Approach: The Offline Solution	71
	3.5 Quantitative Analysis	74
	3.5.1 The Simulated Surgical Clinical Pathway	75
	3.5.2 Scenarios and Indices	76
	3.5.3 Results	77
	3.5.4 Computational Remarks	80
	3.6 Sharing Resources Among Surgical Pathways	80
	3.6.1 Policies for Sharing ORs	81
	3.6.2 Policies for Sharing Overtime	82
	3.6.3 Quantitative Analysis	82
	3.7 Conclusions	85
	References	86
	4 Mixed Fuzzy Clustering for Deriving Predictive Models in Intensive Care Units	88
	4.1 Introduction	88
	4.2 Adverse Events in the ICU	89
	4.2.1 Septic Shock: Vasopressors Administration and Mortality	90
	4.2.2 Early Readmissions	91
	4.3 Mixed Fuzzy Clustering	91
	4.4 Fuzzy Modeling Based on Mixed Fuzzy Clustering	93
	4.4.1 Takagi-Sugeno Fuzzy Modeling	93
	4.4.2 Proposed TS Fuzzy Models	94
	4.5 Data Description	95
	4.5.1 Data Processing	95
	4.5.2 Vasopressors Administration	97
	4.5.3 Mortality in Abdominal Septic Shock	98
	4.5.4 Readmissions	98
	4.6 Results	99
	4.6.1 Vasopressors Administration	101
	4.6.2 Mortality Prediction	102
	4.6.3 Readmissions	103
	4.7 Conclusions	103
	References	104
	5 Operations Research for Occupancy Modeling at Hospital Wards and Its Integration into Practice	107
	5.1 Introduction	107
	5.2 Hospital Ward Types and Terminology	109
	5.2.1 Taxonomy	109
	5.2.2 Terminology	111
	5.3 Ward-Related OR Models	115
	5.3.1 Intensive Care Unit	116
	5.3.2 Acute Medical Unit	118
	5.3.3 Obstetrics Ward	119
	5.3.4 Weekday Ward	122
	5.3.5 General Ward	122
	5.4 Illustrations of OR Model Use	125
	5.4.1 ICU Case Study	125
	5.4.2 OBS Case Study	127
	5.4.3 AMU Case Study	128
	5.4.4 WDW Case Study	130
	5.5 Implemented OR Results	132
	5.6 Challenges and Directions for Further Research	134
	Appendix: OR Model Types	135
	References	138
	Part III Care Process: Preparedness	144
	6 Evaluating Healthcare System Efficiency of OECD Countries: A DEA-Based Study	145
	6.1 Introduction	145
	6.2 DEA	148
	6.3 LE, Infant Mortality and Efficiency	150
	6.3.1 2008 Models with Respect to LE and Infant Mortality	151
	6.3.2 2012 Models with Respect to LE and Infant Mortality	153
	6.3.3 Discussion of Results	154
	6.4 Survival from Major Causes of Death and Efficiency	155
	6.4.1 2008 Models with Respect to Survival from Major Causes of Death	157
	6.4.2 2012 Models with Respect to Survival From Major Causes of Death	157
	6.5 Conclusion	159
	References	161
	7 Healthcare Expenditure Prediction in Turkey by Using Genetic Algorithm Based Grey Forecasting Models	163
	7.1 Introduction	163
	7.2 Literature Review	165
	7.2.1 Health Care Expenditure Literature	165
	7.2.2 Grey Forecasting Literature	166
	7.3 Grey Forecasting	172
	7.3.1 GM (1,1) Model	177
	7.3.2 Nonlinear Grey Bernoulli Model	178
	7.3.3 Data Set	180
	7.4 Methodology	180
	7.4.1 Healthcare Expenditure Forecasting with Proposed Models	183
	7.5 Conclusion	190
	References	191
	8 The Impact of Social Networks in Developing and Managing Chronic Care Models	195
	8.1 Introduction	195
	8.2 The Literature Debate	196
	8.2.1 The General Framework	196
	8.2.2 The Primary Care Stream	197
	8.2.3 The Chronic Care Model and Beyond	198
	8.3 Case Study	201
	8.3.1 Data and Methods	202
	8.4 Discussion of Results	204
	8.5 Conclusion	209
	A.1 Appendix 1	210
	References	211
	Part IV Care Process: Precaution	213
	9 Design and Planning of Organ Transplantation Networks	214
	9.1 Introduction to Organ Transplantation Network Management	214
	9.1.1 Importance and Drivers	214
	9.1.2 Definitions and Scope	215
	9.2 Literature Review	218
	9.3 Selected Mathematical Programming Models	224
	9.3.1 A Multi-period Location-Allocation Model for Organ Transplant Centers	224
	9.3.2 A Credibility-Based Fuzzy Programming Approach to Multi-period Location-Allocation of Organ Transplant Centers Under Uncertainty	230
	9.3.3 A Scalable, Data-Driven Method for Designing Fair and Efficient Kidney Allocation Policies	233
	9.4 Case Study	237
	9.5 Future Research Directions	241
	References	242
	10 Blood Supply Chain Management and Future Research Opportunities	244
	10.1 Introduction	244
	10.2 Existing Literature on Blood Supply Chain	248
	10.3 Future Research Opportunities	251
	10.3.1 Matching Supply with Demand via Donation Tailoring	251
	10.3.2 Scheduling Collection Operations	257
	10.4 Conclusion	263
	References	263
	11 Vaccine Supply Management	270
	11.1 Introduction	270
	11.2 An Introduction to Vaccine Supply Chain Networks	271
	11.2.1 Vaccine Supply Chain Effectiveness and Efficiency	272
	11.2.2 Vaccine Supply Chain Costs	274
	11.3 Vaccine Supply Problems	275
	11.3.1 Vaccine Sourcing	275
	11.3.2 Vaccine Demand Forecasting	276
	11.3.3 Vaccine Shortage	277
	11.3.3.1 Vaccine Production	278
	11.3.3.2 Purchasing and Distribution	280
	11.3.3.3 Provision	280
	11.3.4 Vaccine Cold Chains	281
	11.4 Vaccine Supply Chain Coordination	282
	11.5 Stockpiling Vaccine Supplies for Pandemics	289
	11.6 Conclusion Remarks	291
	Appendix A	292
	References	295
	Part V Care Process: Diagnosis and Prognosis	298
	12 OR Applications in Disease Screening	299
	12.1 Introduction	299
	12.1.1 Assessing Population Level Screening	300
	12.2 OR Models for Evaluation and Optimization of Screening Policies	302
	12.2.1 Modeling at the Individual Level	303
	12.2.2 Modeling at the Cohort Level	305
	12.2.3 Stochastic Models for Screening Program Evaluation	309
	12.2.4 OR Models for Medical Decision Making	310
	12.3 OR Models for Management of Screening Services	317
	12.3.1 Location Models for Screening Facilities	317
	12.3.2 Resource Allocation for Screening Services	319
	12.4 Conclusion	321
	Appendix	322
	References	323
	13 Classification of Cancer Data: Analyzing Gene Expression Data Using a Fuzzy Decision Tree Algorithm	328
	13.1 Introduction	328
	13.2 Related Work	330
	13.3 Fuzzy Decision Tree Classifier	331
	13.4 Experiments and Results	332
	13.4.1 Data Sets	335
	13.4.2 Evaluation Measures	335
	13.4.3 Comparison Algorithms	335
	13.4.4 Experimental Results	337
	13.5 Conclusion	341
	References	346
	Part VI Care Process: Treatment	349
	14 Efficiency of Diabetes Treatment	350
	14.1 Introduction	350
	14.2 Literature Review	352
	14.3 Methodology	354
	14.3.1 TOPSIS	355
	14.3.2 A Neural Network Approach to Predicting Efficiency	356
	14.4 Results and Discussion	357
	14.5 Conclusion	362
	Appendix 1: Contextual Variables and Their Descriptives	365
	Appendix 2: Efficiency Ranking	367
	References	372
	15 A Multiobjective Solution Method for Radiation TreatmentPlanning	377
	15.1 Introduction	377
	15.2 Background	379
	15.3 Problem Formulation	380
	15.4 Results	383
	15.5 Conclusions	388
	References	388
	Part VII Medical Issues	391
	16 OR Models for Emergency Medical Service (EMS) Management	392
	16.1 Introduction to Emergency Medical Services	392
	16.2 EMS Strategic Planning Models	395
	16.2.1 Backup Coverage Problems (BACOP)	398
	16.2.2 Nonlinear Integer Programming Model for Real-Time EMS Vehicle Dispatching Model	400
	16.3 EMS Operational Planning Models	404
	16.3.1 Joint Ground and Air Emergency Medical Services Coverage Model	406
	16.4 EMS Models Under Uncertainty	408
	16.5 Case Study	411
	16.6 Future Research Directions	414
	References	416
	17 Health Informatics	419
	17.1 Introduction	419
	17.2 Optimizational Computing in Bioinformatics	422
	17.3 Variational Methods in Image Segmentation	427
	17.4 Image Registration	430
	17.5 Strategic Reorganization Planning Among Healthcare System Units	434
	17.5.1 MCDM in Unit Investment Ordering	435
	17.5.2 ANP Method	436
	17.5.3 An Example of Private Hospital in Turkey	439
	17.5.3.1 The Identification of Criteria and Sub-criteria	439
	17.5.3.2 Evaluation of the Problem by ANP	442
	17.6 Medical Decision Making: Device Selection Problem	446
	17.6.1 MCDM in Medical Decision Making	447
	17.6.2 VIKOR Method	447
	17.6.3 A Case Study	450
	17.6.3.1 Criteria for Medical Imaging Device Selection and Alternatives	450
	17.6.3.2 Evaluation of MDS Problem by VIKOR	450
	17.7 Conclusion	453
	References	455
	18 OR Applications in Pharmaceutical Supply Chain Management	457
	18.1 Introduction to Pharmaceutical Supply Chain Management	457
	18.1.1 Characteristics and Importance of Pharmaceutical Industry	457
	18.1.2 Pharmaceutical Supply Chain	459
	18.1.2.1 Importance and Drivers	459
	18.1.2.2 Characteristics and Scope	460
	18.1.2.3 Differences of PSCs with Other SCs	462
	18.2 Classification of Problems and Challenges	463
	18.2.1 General Aspects	463
	18.2.2 Strategic Decisions	465
	18.2.2.1 Supply Chain Network Design and Planning	465
	18.2.2.2 Capacity Planning	467
	18.2.3 Tactical Decisions	468
	18.2.3.1 Product Portfolio Selection	469
	18.2.3.2 Inventory Management	470
	18.2.4 Operational Decisions	471
	18.2.5 Integrated Approaches	472
	18.3 Solution Approaches and Challenges	473
	18.3.1 Finding Solution	474
	18.3.2 Uncertainty	475
	18.4 *-17pt	477
	18.5 Future Research Directions	483
	References	484
	19 A Categorical DEA Framework for Evaluating Medical Tourism Efficiency of “Top Destinations”	488
	19.1 Introduction	488
	19.2 Literature Review	490
	19.3 Data Envelopment Analysis	492
	19.3.1 Data Envelopment Analysis with Categorical Data	493
	19.3.1.1 CCR Model with Categorical Variables	493
	19.4 Application of the Proposed DEA Framework for Evaluating Medical Tourism Efficiency of Top Destination Countries	494
	19.5 Hypothesis Testing	502
	19.6 Conclusions	503
	References	504
	Part VIII Health Care Management	507
	20 Healthcare Human Resource Planning	508
	20.1 Importance of Healthcare Human Resource Planning	508
	20.2 Elements of Healthcare Human Resource Projections	509
	20.3 Challenges of Healthcare Human Resource Projections	511
	20.4 Healthcare Human Resource Planning Frameworks	513
	20.5 Survey of Analytical Methods	515
	20.5.1 System Dynamics	515
	20.5.2 Linear Programming	515
	20.5.3 Data Driven Forecasting	516
	20.5.4 Microsimulation	516
	20.5.5 Econometrics	517
	20.6 Considerations for Selecting Healthcare Human Resource Planning Approach	519
	20.7 Case Study 1: Future Requirements for and Supply of Ophthalmologists for an Aging Population in Singapore (Ansah et al. 2015)	521
	20.7.1 Background	521
	20.7.2 Methods	522
	20.7.3 Singapore Eye Care Workforce Model	523
	20.7.4 Scenarios	523
	20.7.5 Key Findings	524
	20.7.6 Insights from the Case Study	525
	20.8 Case 2: Using Linear Programming to Optimize the Dental Team Skill-Mix for England (Harper et al. 2013)	526
	20.8.1 Background	526
	20.8.2 Demand Model	526
	20.8.3 Supply Model	527
	20.8.4 Optimization of Workforce Skill Mix	527
	20.8.5 Results	528
	20.8.5.1 Demand Model	528
	20.8.5.2 Comparison of Supply and Demand	528
	20.8.5.3 Skill-Mix Optimization Model	528
	20.8.6 Recommendations	529
	20.9 Future Research Directions	530
	References	530
	21 Lean Healthcare	535
	21.1 An Introduction to Lean Management	535
	21.1.1 Types of Activities	537
	21.1.1.1 Value Added (VA) Activities	537
	21.1.1.2 Required Non-value Added (RNVA) or Type I Non-value Added Activities	537
	21.1.1.3 Non-value Added (NVA) or Type II Non-value Added Activities	537
	21.1.2 Lean Principles	537
	21.1.2.1 Value	538
	21.1.2.2 Value Stream Mapping	538
	21.1.2.3 Flow	538
	21.1.2.4 Pull Versus Push	538
	21.1.2.5 Perfection	539
	21.1.2.6 Respect for People	539
	21.2 Healthcare Wastes	539
	21.2.1 Over Production	539
	21.2.2 Waiting (Delay)	540
	21.2.3 Transportation	540
	21.2.4 Inappropriate Processing	541
	21.2.5 Unnecessary Inventory	541
	21.2.6 Unnecessary Motion	541
	21.2.7 Defects	542
	21.3 Lean Management in Healthcare Systems	542
	21.3.1 Lean Tools and Techniques	543
	21.3.1.1 Root-Cause Analysis	543
	21.3.1.2 Batch Size Reduction	545
	21.3.1.3 The A3 Problem-Solving Report	545
	21.3.1.4 Takt Time	545
	21.3.1.5 Kaizen Blitz (Kaizen Event)	545
	21.3.1.6 Quick Changeover	546
	21.3.1.7 Total Productive Maintenance (TPM)	547
	21.3.1.8 Kanban (Pull)	547
	21.3.1.9 Industrial Housekeeping (5S)	547
	21.3.1.10 The Five Whys Technique	547
	21.3.1.11 Poka-Yoke/Jidoka (Mistake-Proofing)	548
	21.3.1.12 Standardized Work	548
	21.3.1.13 Visual Controls	548
	21.3.2 Lean System from Employees' Perspectives	549
	21.3.2.1 Task Identity	549
	21.3.2.2 Feedback	550
	21.3.2.3 Work Facilitation	550
	21.3.2.4 Responsible Autonomy	550
	21.3.2.5 Choice Autonomy	550
	21.4 Strategic and Operational Challenges in Hospitals	550
	21.4.1 Organizational Challenges	551
	21.4.2 Defining Waste	551
	21.4.3 Cultural Barriers	551
	21.4.4 Fear of Losing Jobs	551
	21.4.5 Slow Engagement of the Physicians	552
	21.4.6 Sustaining Lean System	552
	21.4.7 Negative Connotations	552
	21.4.8 Defining the Customer	552
	21.4.9 Measuring Value	552
	21.5 Using Operations Research Tools for Lean Healthcare	553
	21.6 Case Studies	555
	21.6.1 ThedaCare, Northeastern Wisconsin, USA	555
	21.6.2 F. Miulli Hospital, Italy	555
	21.6.3 Flinders Medical Centre, Adelaide, Australia	556
	21.6.4 A Primary Care Trust of National Health Service, UK	556
	21.6.5 Royal Bolton Hospital, Bolton, United Kingdom	556
	21.6.6 Three Hospital Sites, New Zealand	557
	21.7 Conclusion	557
	References	558
	22 Procurement Management in Healthcare Systems	561
	22.1 Introduction	561
	22.1.1 Definitions and Scope	562
	22.1.2 Importance, Advantages and Drivers	563
	22.2 Characteristics of Procurement Management in Health Systems	564
	22.2.1 Limitations: Public and Political Pressures	564
	22.2.2 Procurement in Healthcare Supply Chains	565
	22.3 Healthcare Procurement Management Problems and Modelling Methods	566
	22.3.1 Planning Problems Related to Group Purchasing Organizations (GPOs)	566
	22.3.1.1 A Game Theoretic-Based GPO Problem	571
	22.3.2 Supplier Selection and Order Splitting	573
	22.3.3 Bundling Products	576
	22.3.3.1 Supplier Selection and Order Allocation of Bundled Products	577
	22.3.4 E-Procurement	579
	22.3.5 Performance Measurement	580
	22.4 Case Study	582
	22.5 Conclusions	586
	References	587
	Index	591