Analytics and Decision Support in Health Care Operations Management / Edition 3 available in Paperback
Analytics and Decision Support in Health Care Operations Management / Edition 3
- ISBN-10:
- 1119219817
- ISBN-13:
- 9781119219811
- Pub. Date:
- 04/10/2017
- Publisher:
- Wiley
Analytics and Decision Support in Health Care Operations Management / Edition 3
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Overview
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.
Product Details
| ISBN-13: | 9781119219811 |
|---|---|
| Publisher: | Wiley |
| Publication date: | 04/10/2017 |
| Series: | Jossey-Bass Public Health |
| Edition description: | 3rd ed. |
| Pages: | 608 |
| Product dimensions: | 7.30(w) x 9.10(h) x 1.10(d) |
About 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.
Table of Contents
Tables and Figures xiAcknowledgments 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