Quantitative Methods in Health Care Management E-Book

Yasar A. Ozcan

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Serie: Jossey-Bass Public Health/Health Services Text
• Sprache: Englisch

Seitenzahl: 549

Veröffentlichungsjahr: 2009

Beschreibung

Thoroughly revised and updated for Excel®, this secondedition of Quantitative Methods in Health Care Management offers acomprehensive introduction to quantitative methods and techniquesfor the student or new administrator. Its broad range of practicalmethods and analysis spans operational, tactical, and strategicdecisions. Users will find techniques for forecasting,decision-making, facility location, facility layout, reengineering,staffing, scheduling, productivity, resource allocation, supplychain and inventory management, quality control, projectmanagement, queuing models for capacity, and simulation. The book'sstep-by-step approach, use of Excel, and downloadable Exceltemplates make the text highly practical. Praise for the Second Edition "The second edition of Dr. Ozcan's textbook is comprehensive andwell-written with useful illustrative examples that give studentsand health care professionals a perfect toolkit for quantitativedecision making in health care on the road for the twenty-firstcentury. The text helps to explain the complex health caremanagement problems and offer support for decision makers in thisfield." --Marion Rauner, associate professor, School of Business,Economics, and Statistics, University of Vienna. "Quantitative Methods in Health Care Administration, SecondEdition covers a broad set of necessary and important topics. It isa valuable text that is easy to teach and learn from." --David Belson, professor, Department of IndustrialEngineering, Viterbi School of Engineering, University of SouthernCalifornia.

Leseprobe

Table of Contents

Title Page

Copyright Page

List of Tables

Table of Figures

Table of Exhibits

Dedication

Foreword

Acknowledgements

THE AUTHOR

Introduction

CHAPTER 1 - INTRODUCTION TO QUANTITATIVE DECISION-MAKING METHODS IN HEALTH ...

LEARNING OBJECTIVES:

HISTORICAL BACKGROUND AND THE DEVELOPMENT OF DECISION TECHNIQUES

THE HEALTH CARE MANAGER AND DECISION MAKING

INFORMATION TECHNOLOGY (IT) AND HEALTH CARE MANAGEMENT

THE SCOPE OF HEALTH CARE SERVICES, AND RECENT TRENDS

HEALTH CARE SERVICES MANAGEMENT

DISTINCTIVE CHARACTERISTICS OF HEALTH CARE SERVICES

SUMMARY

KEY TERMS

CHAPTER 2 - FORECASTING

LEARNING OBJECTIVES:

STEPS IN THE FORECASTING PROCESS

FORECASTING APPROACHES

SUMMARY

KEY TERMS

EXERCISES

CHAPTER 3 - DECISION MAKING IN HEALTH CARE FACILITIES

LEARNING OBJECTIVES:

THE DECISION PROCESS

THE DECISION TREE APPROACH

DECISION ANALYSIS WITH NONMONETARY VALUES AND MULTIPLE ATTRIBUTES

SUMMARY

KEY TERMS

EXERCISES

CHAPTER 4 - FACILITY LOCATION

LEARNING OBJECTIVES:

LOCATION METHODS

SUMMARY

KEY TERMS

EXERCISES

CHAPTER 5 - FACILITY LAYOUT

LEARNING OBJECTIVES:

PRODUCT LAYOUT

PROCESS LAYOUT

SUMMARY

KEY TERMS

EXERCISES

CHAPTER 6 - REENGINEERING

LEARNING OBJECTIVES:

WORK DESIGN IN HEALTH CARE ORGANIZATIONS

SUMMARY

KEY TERMS

EXERCISES

CHAPTER 7 - STAFFING

LEARNING OBJECTIVES:

WORKLOAD MANAGEMENT OVERVIEW

SUMMARY

KEY TERMS

EXERCISES

CHAPTER 8 - SCHEDULING

LEARNING OBJECTIVES:

STAFF SCHEDULING

SUMMARY

KEY TERMS

EXERCISES

CHAPTER 9 - PRODUCTIVITY

LEARNING OBJECTIVES:

TRENDS IN HEALTH CARE PRODUCTIVITY: CONSEQUENCES OF PPS

SUMMARY

KEY TERMS

EXERCISES

CHAPTER 10 - RESOURCE ALLOCATION

LEARNING OBJECTIVES:

LINEAR PROGRAMMING

SUMMARY

KEY TERMS

EXERCISES

CHAPTER 11 - SUPPLY CHAIN AND INVENTORY MANAGEMENT

LEARNING OBJECTIVES:

HEALTH CARE SUPPLY CHAIN

SUMMARY

KEY TERMS

EXERCISES

CHAPTER 12 - QUALITY CONTROL

LEARNING OBJECTIVES:

QUALITY IN HEALTH CARE

QUALITY MEASUREMENT AND CONTROL TECHNIQUES

SUMMARY

KEY TERMS

EXERCISES

CHAPTER 13 - PROJECT MANAGEMENT

LEARNING OBJECTIVES

THE CHARACTERISTICS OF PROJECTS

SUMMARY

KEY TERMS

EXERCISES

CHAPTER 14 - QUEUING MODELS AND CAPACITY PLANNING

LEARNING OBJECTIVES:

CAPACITY ANALYSIS AND COSTS

SUMMARY

KEY TERMS

EXERCISES

CHAPTER 15 - SIMULATION

LEARNING OBJECTIVES

SIMULATION PROCESS

PERFORMANCE MEASURES AND MANAGERIAL DECISIONS

SUMMARY

KEY TERMS

EXERCISES

APPENDIX A

APPENDIX B

APPENDIX C

APPENDIX D

REFERENCES

INDEX

Table of Figures

FIGURE 2.1. Seasonal Variation Characteristics.

FIGURE 2.2. Cycle Variation.

FIGURE 2.3. Random Variation and Trend.

FIGURE 2.4. Excel Template Solution: Moving Average (MA) for OB/GYN Clinic.

FIGURE 2.5. Excel Template Solution: Weighted Moving Average (WMA) for OB/GYN Clinic.

FIGURE 2.8. Linear Regression.

FIGURE 2.9A

FIGURE 2.9B. Excel Setup—Linear Regression for the Multihospital System Example.

FIGURE 2.10. Excel Solution to the Multihospital System Example.

FIGURE 2.11. Linear Regression as a Trend.

FIGURE 2.12. Excel Linear Trend Graphic Solution to the OB/GYN Example.

FIGURE 2.13. Excel Template Solution to the OB/GYN

FIGURE 2.14. Excel Template - SEST Solution to Example 2.9.

FIGURE 2.15. Seasonality-Removed Trend Data for Heal-Me Hospital Patient Demand.

FIGURE 2.16. Alternative Forecasting Methods and Accuracy, Measured by MAD and MAPE.

FIGURE 2.17. Linear Trend with Tracking Signal for Patient Visit Forecast, Heal-Me Hospital.

FIGURE 2.18. Tracking Signal for Patient Visit Forecast, Heal-Me Hospital.

FIGURE 3.1. Decision Tree.

FIGURE 3.2. Rollback Method.

FIGURE 3.3. Payoff Table Analysis Using Excel Template for Decision Analysis.

FIGURE 3.4. Decision Tree and Rollback Procedure Using Excel Template for Decision Analysis.

FIGURE 4.1. Total Cost of Alternative Imaging Sites.

FIGURE 4.2. Profit Evaluation of Alternative Sites.

FIGURE 4.3. Richmond Metropolitan Area Hospitals.

FIGURE 4.4. Richmond Metropolitan Area Blood Bank Locations.

FIGURE 4.5. Geographic Information Systems.

FIGURE 5.1. Available Space for Layout of Long-Term Care Facility.

FIGURE 5.2. Closeness Rating Chart for Long-Term Care Facility.

FIGURE 5.3. A and X Closeness Representation.

FIGURE 5.4. Layout Solution.

FIGURE 5.5. Excel Template Solution.

FIGURE 5.6. Excel Template Solution and Final Layout for a Small Hospital.

FIGURE 6.1. Work Design—A Systems Perspective.

FIGURE 6.2. Socio-Technical School Approach.

FIGURE 6.3. Random Observation Schedule.

FIGURE 6.4. Stabilized Dates and Times.

FIGURE 6.5. Valid Dates and Times.

FIGURE 6.6. Final Observation Schedule.

FIGURE 6.7. Flow Process Chart for Emergency Room Specimen Processing.

FIGURE 6.8. Commonly Used Flow Chart Symbols.

FIGURE 6.9. Flow Chart for Emergency Room Specimen Processing.

FIGURE 7.1. Workload Management.

FIGURE 7.2. Distribution of Daily Workload on a Nursing Unit.

FIGURE 7.3. Workload Standard Tolerance Ranges.

FIGURE 8.1. Comparison of Eight- and Ten-Hour Shifts.

FIGURE 8.2. Pattern of Alternating Eight- and Twelve-Hour Shifts.

FIGURE 9.1. Productivity and Quality Trade-Off.

FIGURE 9.2. Substitution of Physicians and Nurse Practitioners: A Look at Technical Efficiency.

FIGURE 9.3. Example of DEA Efficiency Frontier Formulation.

FIGURE 10.1. Graphic Solution for Insurance Company Problem.

FIGURE 10.2. Excel Setup for the Insurance Company Problem.

FIGURE 10.3. Excel Solver.

FIGURE 10.4. Identifying Constraints and Solution Cells.

FIGURE 10.5. Selection of Solution Reports.

FIGURE 10.6. Answer Report.

FIGURE 10.7. Sensitivity Report.

FIGURE 10.8. Limits Report.

FIGURE 10.9. Graphic Explanation of Sensitivity Analysis: Shadow Price and its Impact on Alternate Optimal Solutions.

FIGURE 10.10. Graphic Solution for Minimization Example.

FIGURE 10.11. Excel Setup for the Minimization Problem.

FIGURE 10.12. Solution to the Minimization Problem.

FIGURE 10.13. Minimization Problem Answer Report.

FIGURE 10.14. Minimization Problem Sensitivity Report.

FIGURE 10.15. Minimization Problem Limits Report.

FIGURE 10.16. Integer Programming: Excel Setup for the Staff Scheduling Problem.

FIGURE 10.17. Identifying Constraints and Integer Values.

FIGURE 10.18. Solution to the Staff Scheduling Problem.

FIGURE 10.19. Answer Report for the Staff Scheduling Problem.

FIGURE 11.1. Health Care Supply Chain.

FIGURE 11.2. The Inventory Order Cycle for Basic EOQ Model.

FIGURE 11.3. The Economic Ordering Quantity Model.

FIGURE 11.4. Excel Solution to the Syringe Problem.

FIGURE 11.5. Multi-Item Inventory EOQ and ABC Analysis.

FIGURE 12.1. Quality Measurement.

FIGURE 12.2. The Deming Wheel/Shewhart Cycle.

FIGURE 12.3. Process Capability.

FIGURE 12.4. Control Limits, Random and Nonrandom Sample Observations.

FIGURE 12.5. ABC Medical Center Infection Control Monitoring.

FIGURE 12.6. Holistic Care Corporation’s Quality Monitoring.

FIGURE 12.7. Use of Mean and Range Charts.

FIGURE 12.8. Identification of Runs.

FIGURE 12.9. Zone Test.

FIGURE 12.10. A Check Sheet and Corresponding Histogram for Emergency Room Wait Times.

FIGURE 12.11. Scatter Diagram.

FIGURE 12.12. A Flow Chart for the X-Ray Order Process in an Emergency Department.

FIGURE 12.13. Cause-and-Effect Diagram.

FIGURE 12.14. Pareto Diagram.

FIGURE 13.1. Network Representations.

FIGURE 13.2. AON Network Diagram for Radiation Oncology.

FIGURE 13.3. Activity Start and Finish Times.

FIGURE 13.4. Excel Setup and Solution to the Radiation Oncology Project, CPM Version.

FIGURE 13.5. Project Completion Probabilities by the Specified Time.

FIGURE 13.6. Completion Probabilities for Sixty-Five Weeks.

FIGURE 13.7. Excel Setup and Solution to the Probabilistic RadiationOncology Project.

FIGURE 13.8. Project Duration and Compression (Crashing) Costs.

FIGURE 13.9. Project Compression.

FIGURE 13.10. Total Cost of Compression.

FIGURE 14.1. Queue Phenomenon.

FIGURE 14.2. Health Care Service Capacity and Costs.

FIGURE 14.3. Queuing Conceptualization of Flu Inoculations.

FIGURE 14.4. Conceptualization of a Single-Line, Multiphase System.

FIGURE 14.5 .Multiple-Line Queuing System.

FIGURE 14.6. Emergency Room Arrival Patterns.

FIGURE 14.7. Measures of Arrival Patterns.

FIGURE 14.8. Poisson Distribution.

FIGURE 14.9. Service Time for ER Patients.

FIGURE 14.10. Excel Setup and Solution to the Diabetes Information Booth Problem.

FIGURE 14.11. System Probability Summary for Diabetes Information Booth.

FIGURE 14.12. System Performance for Expanded Diabetes Information Booth.

FIGURE 14.13. System Performance Summary for Expanded Diabetes Information Booth with M/M/3.

FIGURE 14.14. Capacity Analysis.

FIGURE 15.1. Random Numbers*. *Random numbers are generated using Excel.

FIGURE 15.2. Excel-Based Simulated Arrivals.

FIGURE 15.3. Excel Program for Simulated Arrivals.

FIGURE 15.4. Performance-Measure-Based Managerial Decision Making.

List of Tables

TABLE 1.1. Total Expenditures on Health as % GDP for 30 OECD Countries.

TABLE 1.2. Distribution of Health Providers and Health Workers in Health Services: 2006, and Expected Growth.

TABLE 1.3. Health Services by Occupation in 2006, and Projected Growth.

TABLE 2.1. Heal-Me Hospital Average Daily Patient Days.

TABLE 2.2. Quarterly Indexes for Heal-Me Hospital.

TABLE 2.3. Monthly Indexes for Heal-Me Hospital.

TABLE 2.4. Daily Indexes for Heal-Me Hospital.

TABLE 2.5. Monthly and Daily Adjusted Forecasts for Heal-Me Hospital.

TABLE 2.6. Error Calculations.

TABLE 3.1. Payoff Table.

TABLE 3.2. Demand for Additional MRIs.

TABLE 3.3. Maximin Solution.

TABLE 3.4. Maximax Solution.

TABLE 3.5. Sensitivity Analysis Using Hurwitz Optimism Parameters.

TABLE 3.6. Opportunity Losses (Regrets).

TABLE 3.7. Laplace Strategy.

TABLE 3.8. Payoff Table for EMV.

TABLE 3.9. Expected Opportunity Loss.

TABLE 3.10. Best Outcomes Under Certainty.

TABLE 3.11. Total Cost of Alternatives Under Various Demand Conditions.

TABLE 3.12. Regret Table Using Costs.

TABLE 3.13. Summary of Supplier Proposals.

TABLE 4.1. Factors to be Considered in Establishing a Satellite Clinic.

TABLE 4.2. Relative Scores on Factors for a Satellite Clinic.

TABLE 4.3. Relative Factor Scores and Weights.

TABLE 4.4 .composite scores

TABLE 4.5. Satellite Clinic Factor Rankings and Minimum Acceptable Levels.

TABLE 4.6. Satellite Clinic Factor Minimum Acceptable Levels.

TABLE 4.7. Satellite Clinic Factor Importance Rankings.

TABLE 4.8. Selected Richmond Metropolitan Area Hospitals.

TABLE 4.9. Selected Richmond Metropolitan Area Hospitals and Their Interaction with the Blood Bank.

TABLE 5.1. Distance and Flows Among Three Hospital Departments.

TABLE 5.2. Possible Assignment Configurations of Departmentsto Three Locations.

TABLE 5.3. Ranking Departments According to Highest Flow.

TABLE 5.4 Total Cost of a Layout.

TABLE 6.1. Typical Allowance Percentages for Varying Health Care Delivery Working Conditions.

TABLE 6.2. Observed Times and Performance Ratings for Nursing Unit Activities.

TABLE 6.3. Observed and Normal Time Calculations for Nursing Unit Activities.

TABLE 6.4. Abridged Patient Care Tasks in a Nursing Unit.

TABLE 6.5. Work Sampling Data Collection Form for Nursing Unit.

TABLE 6.6. Randon Numbers.

TABLE 6.7. Development of the Schedule for a Work Sampling Study.

TABLE 6.8. Final Work Sampling Schedule.

TABLE 6.9. Partial Work Distribution Chart for Nursing Unit.

TABLE 7.1. Examples of Work Standards.

TABLE 7.2. Daily Census, Required Labor Hours, and Acuity Level Statistics for a Medical or Surgical Floor.

TABLE 7.3. Average Census, Required Labor Hours, and Acuity Level Statistics for a Medical or Surgical Floor

TABLE 7.4. Weighted Average Utilization for a Laboratory Based on Workload Fluctuations by Shift.

TABLE 7.5. Workload Standards for Microscopic Procedures in Laboratory.

TABLE 7.6. Calculation of Staffing Requirements for Microscopic Procedures.

TABLE 7.7. The Effect of Shift Alternatives on Staffing—The Coverage Factor.

TABLE 10.1. Nurse Scheduling with Integer Programming.

TABLE 11.1. A-B-C Classification Analysis.

TABLE 12.1. Factors For Determining Control Limits for Mean and Range Charts (for Three-Sigma or 99.7 Percent-Confidence Level).

TABLE 13.1. Activity Precedence Relationships.

TABLE 13.2. Path Lengths for the Radiation Oncology Project.

TABLE 13.3. Probabilistic Time Estimates for Radiation Oncology Clinic.

TABLE 13.4. Calculation of Expected Time and Standard Deviations on Each Path for the Radiation Oncology Clinic.

TABLE 13.5. Path Completion Probabilities.

TABLE 13.6. Project Completion Probabilities.

TABLE 14.1. Summary Analysis for M/M/s Queue for Diabetes Information Booth.

TABLE 15.1. Simple Simulation Experiment for Public Clinic.

TABLE 15.2. Summary Statistics for Public Clinic Experiment.

TABLE 15.3. Patient Arrival Frequencies.

TABLE 15.4. Probability Distribution for Patient Arrivals.

TABLE 15.7. Monte Carlo Simulation Experiment for Public Health Clinic.

TABLE 15.8. Summary Statistics for Public Clinic Monte Carlo Simulation Experiment.

Table of Exhibits

EXHIBIT 5.1. From-To Chart for a Small Hospital.

EXHIBIT 8.1 Cyclical Staffing Schedules For Four and Five Week.

EXHIBIT 8.2. An Example of OR Block Schedule: Surgical Suite Scheduling Method.

EXHIBIT 13.1. Gantt Chart for Launching a New Radiation Oncology Service.

EXHIBIT 14.1 Queuing Model Classification.

Copyright © 2009 by John Wiley & Sons, Inc. All rights reserved.

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Library of Congress Cataloging-in-Publication Data

Ozcan, Yasar A.

p. ; cm.

Includes bibliographical references and index.

eISBN : 978-0-470-44903-5

1. Health services administration—Statistical methods. 2. Health services administration—Decision making. 3 Health services administration—Methodology. I. Title.

[DNLM: 1. Health Services Administration. 2. Statistics as Topic. 3. Decision Making, Organizational. 4. Decision Support Techniques. 5. Models, Theoretical.

WA 950 O99q 2009]

RA394..1072’7—dc22 2009001457

PB Printing

To my wife, Gulperi, and my daughters, Gunes and Nilufer

FOREWORD

I would like to congratulate Professor Yasar Ozcan on producing this excellent, comprehensive textbook, Quantitative Methods in Health Care Management. The field has needed such a textbook for a very long time, and Professor Ozcan is eminently qualified in bringing it to us.

The last textbook in this area was written over twenty years ago. To all of us in health services research and management, we know that health care delivery today bears little resemblance to that era. So too, the use, types, and depth of quantitative methods and techniques have progressed greatly in this time period. Professor Ozcan brings us not only the latest and best methods and techniques, but also illustrates their uses through current cases and examples.

And what I like best about this textbook is that it has been written by one of the leading and most knowledgeable health care management professors in the world. Professor Ozcan has been at the forefront in developing and applying many of the methods in the book, and as founding editor of the journal Health Care Management Science, he draws on the latest knowledge available from other areas.

For those of us who teach quantitative methods in health care management courses, this book will make our task far easier. More importantly, it will provide our students with a comprehensive text that they can draw on in their health care management careers. In addition, this text is a welcome, comprehensive, and up-to-date addition to the work of current managers and to all those who say, “There must be a better way to deliver health care.”

Indeed there is, and the application of the methods and ideas in this book will provide many, many answers.

William P. Pierskalla, Ph.D. Distinguished Professor and Dean Emeritus, The Anderson School, UCLA, and Ronald Rosenfeld Professor Emeritus, The Wharton School, University of Pennsylvania

ACKNOWLEDGMENTS

Writing this book could not have been achieved without the help and encouragement of many individuals. I take this opportunity to thank them; if I miss anyone, it is through authorial oversight only, as all the help received was deeply appreciated. First of all, I thank my colleague Ramesh K. Shukla, who provided valuable insights and material for the productivity chapter. Many thanks go to my graduate students from the MSHA Class of 2007 and MSHA Class of 2006 who received the first draft of the manuscript and pointed out many corrections. Similarly, graduate students from the MSHA Class of 2005 lent their real-life experiences with quantitative techniques and associated materials and data, which are used in the examples and exercises throughout the text. In that vein, more specifically, I thank Adrian Amedia, Joani Brough, Mark Cotter, Sandy Chung, Suzanne Coyner, Alan Dow, and Paulomi Sanyal for their resourcefulness.

I would like to acknowledge Dorothy Silvers for her diligent editing of the manuscript from cover to cover. I extend my sincere thanks as well to Jossey-Bass/Wiley staff members Andrew Pasternack and Seth Schwartz, for their cooperativeness and help in the production of this manuscript.

No book can be written on time without the support and encouragement of loved ones. I am indebted to my wife, Gulperi Ozcan, who became my sounding board for every example in this book. Moreover, she extended her support throughout the development of the manuscript even as I deprived her of my time in favor of my desktop. I thank her for the sustained support she has given me throughout my academic career and our personal life.

Yasar A. Ozcan, Ph.D. May 15, 2008 Richmond, Virginia

THE AUTHOR

Yasar A. Ozcan, Ph.D. is a professor in the Department of Health Administration, Virginia Commonwealth University (VCU), where he has served as a faculty member for over thirty years. Dr. Ozcan teaches quantitative health care management courses in graduate professional programs in health administration, and methodology courses at the doctoral level. He has served twice as president of the Health Applications Section in the Institute of Operations Research and Management Science. Professor Ozcan is the founding Editor in Chief of a highly regarded journal, Health Care Management Science, and coeditor of the Journal of Central Asian Health Services Research.

Dr. Ozcan has been principal and co-principal investigator on various federal and state grants and contracts. He has also provided management consultancy services to health care facilities and managed care organizations.

Dr. Ozcan’s scholarly work is in the areas of systems productivity, technical efficiency, financial efficiency, and effectiveness. Specifically, he has applied data envelopment analysis to measure efficiency across the range of health care facilities and practices, including hospitals, nursing homes, health maintenance organizations, mental health care organizations, physician practices, and other facilities. He has presented numerous papers in professional meetings and published extensively in these areas.

Dr. Ozcan has long been active in distance education, having taught quantitative techniques, the content of this book, both in the traditional and on-line graduate programs at VCU since 1988.

INTRODUCTION

This book is written to meet the need for a quantitative methods curriculum in health administration or health care management programs. It is designed so that it can be used for one-semester courses in graduate programs as well as for advanced undergraduate programs in health administration. Practical and contemporary examples from the field make it a useful reference book for health care managers, as well.

The quantitative techniques offered in this book are those more amenable to the health care management environment and those most frequently used. The second edition employs the use of Excel. Although the simpler examples are demonstrated in the text, their Excel solutions are also provided. As techniques increase in sophistication, as for example in queuing models, Excel template solutions are preferred to lengthy formulas and look-up tables. The second edition also incorporates learning objectives at the beginning of each chapter and key terms at the end of each chapter to facilitate the appropriate pedagogy for learning. Because the intent of the book is to make students into able users of quantitative methods for decision making, the interpretation of the results from hand-calculated or Excel solutions to guide for informed decision making is the foremost goal. Thus, students who have had basic algebra and introductory statistics courses should be able to follow the contents of this book.

The book has fifteen chapters including the introductory chapter. The presentation of quantitative techniques starts with forecasting, which provides the data for many of the other techniques discussed, as well as for planning in health care facilities. The chapter on decision making provides the decision techniques not only for single attribute decision theory, but also for the multi-attribute methods often used in health care management decisions, especially in evaluating new contracts or in requests for proposals.

Chapters Four and Five provide techniques for facility location and layout. The techniques discussed for layout also can be used to improve flows in facilities. Hence, in Chapter Six, reengineering is introduced as the means to identify bottlenecks in operational processes and to correct them. Chapters Seven and Eight cover staffing and resource scheduling management in health care facilities; surgical suite resource management is highlighted. These two chapters can be assigned and covered together in one session. Chapter Nine, on productivity, not only presents the traditional productivity concepts and their measurements in both inpatient and outpatient settings, but also discusses more contemporary methods of productivity measurements as conducted through data envelopment analysis.

Chapter Ten explains linear programming and its use in resource allocation. Furthermore, integer programming, an extension of linear programming, is discussed and illustrated for staff scheduling. Supply chain management in health care has become popular in recent decades, and the first part of Chapter Eleven discusses that; the second part of the chapter is devoted to traditional techniques for inventory management. Quality control, essential above all in health care, is discussed in Chapter Twelve. Types of control charts and their developments are illustrated. Several approaches to quality control, including total quality management, continuous quality improvement, and six-sigma, are discussed. The tools for quality improvement are presented.

Project management is the subject of Chapter Thirteen, where program evaluation and review technique/critical path method (PERT/CPM) techniques are discussed in detail, with examples of project compression. The last two chapters cover queuing and simulation techniques with emphasis on capacity decisions using those tools. Simple queuing methods are shown with detailed examples. More sophisticated ones are illustrated by Excel solutions.

The sequence of chapters has a certain logic. For example, in Chapter Four, the location of a new facility is identified; and in Chapter Five, layout of that facility can be explored. On the other hand, Chapter Five can be also used in an independent layout analysis for existing facilities to improve flow and productivity. Similarly, Chapters Six, Seven, Eight and Nine are built to feed the knowledge onward. Chapters Fourteen and Fifteen address capacity issues using different techniques. Regardless of this sequence, however, the chapters can be selected in any order and presented to students based on the professor’s preferences.

Developing exercises for the techniques explained in each chapter has been a consuming task. Any errors and oversights in that process are solely mine. I will appreciate reader comments to improve or correct the exercises, as well as suggestions for incorporating additional material in future editions.

There are on-line resources to accompany this book. On-line resources (password protected) are available to professors who adopt the book and to the students. Professors’ resources include PowerPoint lectures, solutions to exercises, prototype course syllabus, Excel templates, and additional exercises with solutions. Student resources include solutions to selected exercises, Excel templates, a subset of additional exercises with solutions, and other study guide materials. These resources can be accessed via www.josseybass.com/go/ozcan2e.

CHAPTER 1

INTRODUCTION TO QUANTITATIVE DECISION-MAKING METHODS IN HEALTH CARE MANAGEMENT

LEARNING OBJECTIVES:

• Recognize the quantitative techniques for decisions about delivering health care of high quality.

• Describe the historical background and the development of decision techniques.