Handbook of healthcare analytics : theoretical minimum for conducting 21st century research on healthcare operations / edited by Tinglong Dai and Sridhar Tayur.

"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 heathcare applications; data science tools with healthcare 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"-- Provided by publisher.

"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)"-- Provided by publisher.

List of Contributors xvii Preface xix Glossary of Terms xxvii Acknowledgments xxxv Part I Thrusts Macro-level Thrusts (MaTs) 1 Organizational Structure 1; Jay Levine 1.1 Introduction to the Healthcare Industry 2 1.2 Academic Medical Centers 6 1.3 Community Hospitals and Physicians 16 1.4 Conclusion 19 2 Access to Healthcare 21; Donald R.

Fischer 2.1 Introduction 21 2.2 Goals 27 2.3 Opportunity for Action 29 3 Market Design 31; Itai Ashlagi 3.1 Introduction 31 3.2 Matching Doctors to Residency Programs 31 3.2.1 Early Days 31 3.2.2 A Centralized Market and New Challenges 32 3.2.3 Puzzles andTheory 33 3.3 Kidney Exchange 35 3.3.1 Background 35 3.3.2 Creating a Thick Marketplace for Kidney Exchange 36 3.3.3 Dynamic Matching 38 3.3.4 The Marketplace for Kidney Exchange in the United States 41 3.3.5 Final Comments on Kidney Exchange 43 References 44 Meso-level Thrusts (MeTs) 4 Competing Interests 51; Joel Goh 4.1 Introduction 51 4.2 The Literature on Competing Interests 53 4.2.1 Evaluation of Pharmaceutical Products 53 4.2.1.1 Individual Drug Classes 54 4.2.1.2 Multiple Interventions 55 4.2.1.3 Review Articles 56

4.2.2 Physician Ownership 56 4.2.2.1 Physician Ownership of Ancillary Services 57 4.2.2.2 Physician Ownership of Ambulatory Surgery Centers 59 4.2.2.3 Physician Ownership of Speciality Hospitals 60 4.2.2.4 Physician-Owned Distributors 61 4.2.3 Medical Reporting 62 4.2.3.1 DRG Upcoding 63 4.2.3.2 Non-DRG Upcoding 64 4.3 Examples 65 4.3.1 Example 1: Physician Decisions with Competing Interests 66 4.3.2 Example 2: Evidence of HAI Upcoding 70 4.4 Summary and FutureWork 72 References 73 5 Quality of Care 79; Hummy Song and Senthil Veeraraghavan 5.1 Frameworks for Measuring Healthcare Quality 79 5.1.1 The Donabedian Model 79 5.1.2 The AHRQ Framework 81 5.2 Understanding Healthcare Quality: Classification of the Existing OR/MS Literature 82 5.2.1 Structure 82 5.2.2 Process 85 5.2.3 Outcome 91 5.2.4 Patient Experience

92 5.2.5 Access 94 5.3 Open Areas for Future Research 95 5.3.1 Understanding Structures and Their Interactions with Processes and Outcomes 95 5.3.2 Understanding Patient Experiences andTheir Interactions with Structure 96 5.3.3 Understanding Processes andTheir Interactions with Outcomes 97 5.3.4 Understanding Access to Care 98 5.4 Conclusions 98 Acknowledgments 99 References 99 6 PersonalizedMedicine 109; Turgay Ayer and Qiushi Chen 6.1 Introduction 109 6.2 Sequential Decision Disease Models with Health Information Updates 111 6.2.1 Case Study: POMDP Model for Personalized Breast Cancer Screening 113 6.2.2 Case Study: Kalman Filter for Glaucoma Monitoring 116 6.2.3 Other Relevant Studies 118 6.3 One-Time Decision Disease Models with Risk Stratification 120 6.3.1 Case Study: Subtype-Based Treatment for DLBCL 121 6.3.2 Other Applications 124

6.4 Artificial Intelligence-Based Approaches 125 6.4.1 Learning from Existing Health Data 126 6.4.2 Learning from Trial and Error 127 6.5 Conclusions and Emerging Future Research Directions 128 References 130 7 Global Health 137; Karthik V. Natarajan and Jayashankar M.

Swaminathan 7.1 Introduction 137 7.2 Funding Allocation in Global Health Settings 139 7.2.1 Funding Allocation for Disease Prevention 139 7.2.2 Funding Allocation for Treatment of Disease Conditions 143 7.2.2.1 Service Settings 143 7.2.2.2 Product Settings 146 7.3 Inventory Allocation in Global Health Settings 147 7.3.1 Inventory Allocation for Disease Prevention 147 7.3.2 Inventory Allocation for Treatment of Disease Conditions 149 7.4 Capacity Allocation in Global Health Settings 153 7.5 Conclusions and Future Directions 155 References 156 8 Healthcare Supply Chain 159; Soo-Haeng Cho and Hui Zhao 8.1 Introduction 159 8.2 Literature Review 162 8.3 Model and Analysis 164 8.3.1 Generic Injectable Drug Supply Chain 164 8.3.1.1 Model 166 8.3.1.2 Analysis 168 8.3.2 Influenza Vaccine Supply Chain 171 8.3.2.1 Model 172

CemRanda 9.1 Introduction 187 9.2 The Deceased-Donor Organ Allocation system: Stakeholders and Their Objectives 189 9.3 Research Opportunities in the Area 199 9.3.1 Past Research on the Transplant Candidate’s Problem 199 9.3.2 Challenges in Modeling Patient Choice 201 9.3.3 Past Research on the Deceased-donor Organ Allocation Policy 202 9.3.4 Challenges in Modeling the Deceased-donor Organ Allocation Policy 206 9.3.5 Research Problems from the Perspective of Other Stakeholders 206 9.4 Concluding Remarks 208 References 209 Micro-level Thrusts (MiTs) 10 Ambulatory Care 217; Nan Liu 10.1 Introduction 217 10.2 How Operations are Managed in Primary Care Practice 218 10.3 What Makes Operations Management Difficult in Ambulatory Care 220 10.3.1 Competing Objectives 220 10.3.2 Environmental Factors 221 10.4 Operations ManagementModels 222

10.4.1 System-Wide Planning 222 10.4.2 Appointment Template Design 226 10.4.3 Managing Patient Flow 231 10.5 New Trends in Ambulatory Care 234 10.5.1 Online Market 234 10.5.2 Telehealth 235 10.5.3 Retail Approach of Outpatient Care 236 10.6 Conclusion 237 References 237 11 Inpatient Care 243; Van-Anh Truong 11.1 Modeling the InpatientWard 244 11.2 InpatientWard Policies 246 11.3 Interface with ED 247 11.4 Interface with Elective Surgeries 248 11.5 Discharge Planning 250 11.6 Incentive, Behavioral, and Organizational Issues 251 11.7 Future Directions 252 11.7.1 Essential Quantitative Tools 253 11.7.2 Resources for Learners 253 References 253 12 Residential Care 257; Nadia Lahrichi,