Analytics and Decision Support in Health Care Operations Management: (Jossey-Bass Public Health)

A compendium of health care quantitative techniques based in Excel Analytics and Decision Support in Health Care Operations is a comprehensive introductory guide to quantitative techniques, with practical Excel-based solutions for strategic health care management. This new third edition has been extensively updated to reflect the continuously evolving field, with new coverage of predictive analytics, geographical information systems, flow process improvement, lean management, six sigma, health provider productivity and benchmarking, project management, simulation, and more. Each chapter includes additional new exercises to illustrate everyday applications, and provides clear direction on data acquisition under a variety of hospital information systems. Instructor support includes updated Excel templates, PowerPoint slides, web based chapter end supplements, and data banks to facilitate classroom instruction, and working administrators will appreciate the depth and breadth of information with clear applicability to everyday situations. The ability to use analytics effectively is a critical skill for anyone involved in the study or practice of health services administration. This book provides a comprehensive set of methods spanning tactical, operational, and strategic decision making and analysis for both current and future health care administrators. Learn critical analytics and decision support techniques specific to health care administration Increase efficiency and effectiveness in problem-solving and decision support Locate appropriate data in different commonly-used hospital information systems Conduct analyses, simulations, productivity measurements, scheduling, and more From statistical techniques like multiple regression, decision-tree analysis, queuing and simulation, to field-specific applications including surgical suite scheduling, roster management, quality monitoring, and more, analytics play a central role in health care administration. Analytics and Decision Support in Health Care Operations provides essential guidance on these critical skills that every professional needs.

Table of Contents:
Tables and Figures xi Acknowledgments xxi The Author xxiii Introduction xxv Chapter-by-Chapter Revisions for the Third Edition xxvii Chapter 1: Introduction to Analytics and Decision Support in Health Care Operations Management 1 Learning Objectives 1 Historical Background and the Development of Decision Techniques 2 The Health Care Manager and Decision Making 3 Importance of Health Analytics: Information Technology (IT) and Decision Support Techniques 3 The Scope of Health Care Services, and Recent Trends 4 Health Care Services Management 5 Distinctive Characteristics of Health Care Services 5 Big Data and Data Flow in Health Care Organizations 7 Summary 9 Key Terms 9 Chapter 1 Supplement: Data Analytics in MS Excel: Creating and Manipulating Pivot Tables 10 Exercises 23 Chapter 2: Predictive Analytics 27 Learning Objectives 27 Steps in the Predictive Analytics Process 28 Predictive Analytics Techniques 29 Judgmental Predictions 29 Time-Series Technique 30 Techniques for Averaging 31 Techniques for Trend 41 Predictive Techniques for Seasonality 55 Accuracy of Predictive Analytics 61 Prediction Control 62 Summary 65 Key Terms 65 Exercises 66 Chapter 3: Decision Making in Health Care 85 Learning Objectives 85 The Decision Process 85 What Causes Poor Decisions? 87 The Decision Level and Decision Milieu 87 Decision Making under Uncertainty 88 Payoff Table 88 Decision Making under Risk 93 What If Payoff s Are Costs 97 The Decision Tree Approach 101 Analysis of the Decision Tree: Rollback Procedure 102 Sensitivity Analysis in Decision Making 103 Decision Analysis with Nonmonetary Values and Multiple Attributes 107 Clinical Decision Making and Implications for Management 110 Summary 114 Key Terms 114 Exercises 115 Chapter 4: Facility Location 135 Learning Objectives 135 Location Methods 137 Cost-Profit-Volume (CPV) Analysis 137 Factor Rating Methods 140 Multi-Attribute Methods 143 Center of Gravity Method 145 Geographic Information Systems (GIS) in Health Care 149 Summary 154 Key Terms 154 Exercises 155 Chapter 5: Facility Layout 169 Learning Objectives 169 Product Layout 170 Process Layout 171 Process Layout Methods 171 Method of Minimizing Distances and Costs 175 Computer-Based Layout Programs 175 Fixed-Position Layout 177 Summary 180 Key Terms 180 Exercises 181 Chapter 6: Flow Processes Improvement: Reengineering and Lean Management 197 Learning Objectives 197 Reengineering 198 Lean Management 199 Work Design in Health Care Organizations 203 Work Measurement Using Time Standards 207 Work Measurement Using Work Sampling 214 Work Simplification 223 Worker Compensation 237 Summary 237 Key Terms 238 Exercises 238 Chapter 7: Staffing 253 Learning Objectives 253 Workload Management Overview 254 Establishment of Workload Standards and Their Influence on Staffing Levels 254 Patient Acuity Systems 256 The Development of Internal Workload Standards 261 Procedurally Based Unit Staffing 263 Acuity-Based Unit Staffing 266 External Work Standards and Their Adjustments 270 Productivity and Workload Management 271 Summary 273 Key Terms 273 Exercises 273 Chapter 8: Scheduling 281 Learning Objectives 281 Staff Scheduling 281 Surgical Suite Resource Scheduling 290 Summary 294 Key Terms 295 Exercises 295 Chapter 9: Productivity and Performance Benchmarking 297 Learning Objectives 297 Trends in Health Care Productivity: Consequences of Reforms and Policy Decisions 298 Productivity Definitions and Measurements 299 Commonly Used Productivity Ratios 302 Adjustments for Inputs 304 Adjustments for Outputs 308 Case Mix Adjustments 310 Productivity Measures Using Direct Care Hours 312 The Relationships between Productivity and Quality in Hospital Settings 314 Dealing with the Multiple Dimensions of Productivity: New Methods of Measurement and Benchmarking 316 Data Envelopment Analysis 318 Overview on Improving Health Care Productivity 321 Summary 323 Key Terms 323 Exercises 323 Chapter 10: Resource Allocation 333 Learning Objectives 333 Linear Programming 333 Maximization Models 335 Minimization Models 345 Integer Programming 346 Summary 355 Key Terms 356 Exercises 356 Chapter 11: Supply Chain and Inventory Management 363 Learning Objectives 363 Health Care Supply Chain 363 Traditional Inventory Management 370 Economic Order Quantity Model 374 Classification System 379 Summary 384 Key Terms 384 Exercises 384 Chapter 12: Quality Control and Improvement 393 Learning Objectives 393 Quality in Health Care 393 Total Quality Management (TQM) and Continuous Quality Improvement (CQI) 397 Six-Sigma 398 Quality Measurement and Control Techniques 399 Monitoring Variation through Control Charts 401 Control Charts for Attributes 403 Control Charts for Continuous Variables 407 Investigation of Control Chart Patterns 412 Process Improvement 415 Tools for Investigating the Presence of Quality Problems and Their Causes 417 Summary 421 Key Terms 421 Exercises 421 Chapter 13: Project Management 431 Learning Objectives 431 The Characteristics of Projects 432 Planning and Scheduling Projects 434 The Network 436 Critical Path Method (CPM) 437 Probabilistic Approach 441 Project Compression: Trade-Off s Between Reduced Project Time and Cost 448 Project Management Applications in Clinical Settings: Clinical Pathways 461 Summary 464 Key Terms 464 Exercises 464 Chapter 14: Queuing Models and Capacity Planning 477 Learning Objectives 477 Queuing System Characteristics 479 Capacity Analysis and Costs 494 Summary 496 Key Terms 497 Exercises 497 Chapter 15: Simulation 507 Learning Objectives 507 Simulation Process 507 Monte Carlo Simulation Method 510 Performance Measures and Managerial Decisions 516 Excel-Based Simulation Templates with Performance Measures and Managerial Decisions 517 Multiphase Simulation Model 520 Summary 522 Key Terms 522 Exercises 522 Appendixes Appendix A: Standard Normal Distribution 527 Appendix B: Standard Normal Distribution 529 Appendix C: Cumulative Poisson Probabilities 533 Appendix D: t-Distribution 539 References 541 Index 549

About the Author :
The Author YASAR A. OZCAN, PhD, is Charles P. Cardwell, Jr. Professor and vice chair and director of the Master of Science in Health Administration program at Virginia Commonwealth University. Extensively published in health care performance assessment, he is the founding Editor-in-Chief of Health Care Management Science. Dr. Ozcan's massive work has applied data envelopment analysis to health care facilities including hospitals, nursing homes, mental health care organizations, and more. He has taught health analytics and decision support in VCU's MHA and Executive MSHA graduate programs for more than 30 years.