................................................................

HEALTH CARE................................................................

OPERATIONS AND SUPPLY................................................................

CHAIN MANAGEMENT................................................................

................................................................

HEALTH CARE................................................................

OPERATIONS AND SUPPLY................................................................

CHAIN MANAGEMENT................................................................

Operations, Planning, and Control

JOHN F. KROS

EVELYN C. BROWN

Cover image: @ Nitipong Ballapavanich/iStockphotoCover design: Michael Rutkowski

Copyright © 2013 by John Wiley & Sons, Inc. All rights reserved.

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Library of Congress Cataloging-in-Publication Data

Kros, John F.Health care operations and supply chain management : operations, planning, and

control / John F. Kros, Evelyn C. Brown.—First edition.pages cm

Includes bibliographical references and index.ISBN 978-1-118-10977-9 (pbk.); ISBN 978-1-118-41884-0 (ebk.);ISBN 978-1-118-41610-5 (ebk.); ISBN 978-1-118-43367-6 (ebk.)1. Health facilities—Business management. 2. Health services administration. I. Brown,

Evelyn C., 1966- II. Title.RA971.3.K767 2013362.1068—dc23

2012033935

Printed in the United States of America

FIRST EDITION

PB Printing 10 9 8 7 6 5 4 3 2 1

CONTENTS

Tables and Figures xiPreface xxiThe Authors xxxi

PART I STRATEGY 1

Chapter 1 Health Care Operations and Supply Chain Strategy 3Health Care Operations and Supply Chain Management 4Purchasing, Logistics, and Vendor-Managed Inventories 7Efficiency, Effectiveness, and Value 8Competitive Dimensions of Health Care 12The Bullwhip Effect in Health Care 14MiniCase: The Bullwhip Effect in Health Care

Organizations 18

Chapter 2 Financial Aspects of Health Care Operationsand Supply Chain Management 21

Health Care Finance and Operations/Supply ChainManagement 22

Income Statement/Operating Statement 24Balance Sheet 27Statement of Cash Flows 32Basic Financial Ratios and Metrics 35Time Value of Money 47Break-Even Analysis 49Crossover Analysis 53

Chapter 3 Managerial Accounting Aspects of HealthCare Operations and Supply Chain Management 61

Managerial Aspects of Health Care Operations andSupply Chain Management 62

Managerial Accounting 62Activity-Based Costing 65Supply Chain Management behind the Scenes:Cost Drivers at Hospitals 69

PART II PROCESS DESIGN AND ANALYSIS OFHEALTH CARE OPERATIONS 75

Chapter 4 Data and Statistical Tools for Health CareOperations Improvement 77

Descriptive Statistics for Describing Data Sets 78Graphical Methods of Data Description 78Numerical Methods of Data Description 81Hypothesis Testing: Analyzing the Differenceof Two Means 101

Pareto Analysis 116Box-and-Whisker Plots 117Tornado Diagrams and Sensitivity Analysis 129

Chapter 5 Problem Solving and Decision-Making Tools inHealth Care Operations 143

Health Care Operations and Supply ChainManagement in Action: How Legal DecisionMakers Use Decision Models 144

Framing the Decision Problem 146Components of a Decision-Making Problem 146Payoff Tables 149Decision-Making Criteria without ProbabilityAssessments 151

Decision-Making Criteria with ProbabilityAssessments 159

Expected Value of Perfect Information 162

vi � CONTENTS

Modeling 177Decision Trees 179

Chapter 6 Simulation 201Introduction 202Process Flows 202Probability Distributions 203Random Number Generation 210Discrete-Event versus Continuous Simulation 211Monte Carlo Simulation 213Agent-Based Simulation 215Simulation in Health Care 215Queuing Analysis 216

Chapter 7 Process Improvement and Patient Flow 229Introduction 230Process Mapping 231Value Stream Mapping 233Use of Maps and Charts in Health Care 240Staffing 242Workload Management 243Productivity and Efficiency Analysis 245Common Health Care Productivity and Efficiency

Measures 248Improving Productivity and Efficiency 249MiniCase: Improving Process Flow to Improve

Service-Level Performance Statistics 253

Chapter 8 Facility Layout 257Introduction 257Layout Considerations 258Types of Layouts 262Muther Diagrams 264Workload Management 266Evaluating Different Types of Layouts 267Basics of Optimization 270Optimization Using Excel Solver 272Optimizing Facility Layout and Design 280

CONTENTS � vii

PART III MANAGING HEALTH CAREOPERATIONS QUALITY 287

Chapter 9 Managing Quality in a Health Care Setting 289What Is Service Quality? 290Quality Planning, Control, and Improvement 291Quality and Financial Performance 292Seven Tools for Quality Control 294Six Sigma Concepts 305Six Sigma and Lean 311MiniCase: Delayed Room Cleaning Dilemma 320

Chapter 10 Quality Control and Improvement 323Design of Quality Control Systems 324Process Quality Control 324Variables Control 327Using Control Charts 331Process Capability 334Total Quality Management and ContinuousImprovement 337

International Organization for StandardizationCertification 338

Malcolm Baldrige Award 340

PART IV PLANNING AND CONTROLLINGHEALTH CARE OPERATIONS 351

Chapter 11 Lean Concepts in Health Care 353Introduction 354What Is Lean? 354Controlling Waste 355Controlling Flow with a Kanban System 357Kaizen Events 359Value Stream Mapping 362Measures and Tools 362Adverse Effects of Becoming Too Lean 364MiniCase: Using Lean Concepts to ImproveInpatient Care 366

viii � CONTENTS

Chapter 12 Forecasting for Health Care Management 369Analyzing Data Using Time Series and

Regression Models 370Linear and Nonlinear Trends 371Seasonality in Data 372Naive Forecasting 376Moving Averages 378Weighted Moving Averages 381Exponential Smoothing 383Autocorrelation 387Regression as a Forecasting Technique 393Multiple Regression Model 402Measuring Accuracy 409Measuring Forecasting Errors 423

Chapter 13 Project Management 431Introduction 432Role of Project Manager 432Objectives and Trade-Offs 433Planning and Control in Projects 435Project Scheduling 437Critical Path Method 440Gantt Charts 448Program Evaluation and Review Technique 451Implementation 453MiniCase: Implementing Electronic Medical Records

at St. Hampton’s Hospital 457

Chapter 14 Aggregate Planning, Scheduling, and CapacityManagement in Health Care 461

Aggregate/Central Planning 462Resource Planning and Control 464Scheduling and Capacity Management 468Workforce Scheduling 468Dispatching Rules 473Job Sequencing 474

CONTENTS � ix

Johnson’s Rule 475Service Facility Location Analysis 486Center of Gravity Method 487

Chapter 15 Inventory Management 501Introduction 502Purpose of Inventories 502Costs of Inventories 504Economic Order Quantity 506Independent versus Dependent Demand 509Periodic Review Systems 510Continuous Review Systems 511ABC Inventory Management 515Inventory Management Technology 519

Index 525

x � CONTENTS

TABLES AND FIGURES

LIST OF TABLES

Table 1.1 Major Causes of the Bullwhip Effect 16Table 2.1 For-Profit andNot-for-Profit Health Care Financial Statements 24Table 2.2 Key Health Care Financial Ratios 35Table 3.1 Six Cost Drivers and Health Care Examples 65Table 3.2 Activities and Cost Drivers for the Nurse’s Station 67Table 3.3 Formulas for the Cost per Unit Driver Calculations 68Table 3.4 Formulas for the Total Cost per Activity Calculations 69Table 3.5 Formulas for the Traditional Method of Indirect Cost

Assignment 69Table 4.1 DRG Category Data 81Table 4.2 Common Measures of Central Tendency in Health Care 83Table 4.3 Emergency Room Waiting Time Information 90Table 4.4 Daily Census for Rehabilitation Center 95Table 4.5 ER Wait Times with Wait Time Distribution 100Table 4.6 ER Wait Times with Expected Wait Time Calculated 101Table 4.7 Descriptive Statistics of Two Populations 103Table 4.8 Novine’s Average Prescription Data 108Table 4.9 Summary Statistics for Novine’s Pharmacy Receipts 109Table 4.10 Excel Formulas for Box Plot 122Table 4.11 Tornado Diagram Data Set 130Table 5.1 Possible Outcomes for Medical Equipment Example 148Table 5.2 Payoff Table for Medical Equipment Example 149Table 5.3 Sarah’s Equipment Payoff Table (Percent Return) 152Table 5.4 Summary of Final Medical Equipment Example Choices 162Table 5.5 Definitions and Quantifications of Risk 166

Table 5.6 Range Calculations for the Medical Equipment Example 175Table 5.7 Minimax Regret Calculations for the Medical Equipment

Example 176Table 5.8 Medical Equipment Decision Tree Expected Values 184Table 6.1 Excel Formulas for Queuing Example 221Table 6.2 Excel Formulas for Summary Statistics 223Table 7.1 Value Stream Mapping Symbols 236Table 7.2 Examples of Health Care Productivity and Efficiency Measures

by Facility Type 250Table 8.1 Types of Facility Layouts 262Table 8.2 Reasons for Closeness Rating 265Table 8.3 Importance of Relationship 265Table 8.4 Design Evaluation Criteria 267Table 8.5 Impact Analysis of Aisle Arrangement 268Table 8.6 Design Alternative Metrics 270Table 8.7 Patient Traffic per Week 282Table 8.8 Patient Movement Costs 283Table 9.1 Control Chart Data Set 303Table 9.2 Factors for Determining Control Limits 303Table 9.3 MiniCase Cleaning Delay Information 321Table 10.1 Areas of Interest and Associated Quality Control Systems 325Table 10.2 Factors or Computing Control Chart Limits (Three Sigma) 328Table 10.3 Formulas for Control Chart Spreadsheet Calculations 329Table 10.4 Control Chart Patterns 333Table 10.5 Formulas for Process Capability Spreadsheet Calculations 336Table 12.1 Example Data Set for Hospital (Beds Demanded) 376Table 12.2 Hospital Charge/Length of Stay Data for Linear Regression

Computation 400Table 12.3 Patient Satisfaction Data for Linear Regression Computation 403Table 12.4 Excel Formulas for Error Calculations 412Table 12.5 Error Measurements for Glucose Example 423Table 13.1 Direct Ranking Method Example 434Table 13.2 Deriving Weights from Importance Ratings 435Table 13.3 Data for Example Project 440Table 13.4 Early Start Schedule 440Table 13.5 Late Start Schedule 442Table 13.6 Slack for Project Activities 442

xii � TABLES AND F IGURES

Table 13.7 Project Crashing Example 444Table 13.8 Health Care Project Example 445Table 14.1 Workforce Scheduling Packages 471Table 14.2 Johnson’s Rule Example 476Table 14.3 Formulas and Brief Explanatory Notes for Figure 14.9 480Table 14.4 Demand Locale Data for Outpatient Clinic 489Table 14.5 Formulas to Accompany Spreadsheet in Figure 14.17 492Table 14.6 Laboratory Jobs Processing Times 494Table 14.7 Billing Inquiry Processing Times 495Table 14.8 Senior/Community Center Location Data 496Table 14.9 Health Care Facility Location Data 497Table 15.1 Differences between Periodic and Continuous Inventory

Systems 512Table 15.2 Inventory Data 516Table 15.3 Percent Total Dollar Volume Data 517

LIST OF FIGURES

Figure P.1 Graph of Projected Health Expenditures xxiiFigure P.2 Health Expenditures as a Percentage of Gross Domestic

Product xxiiFigure 2.1 Operating Statement for a Health Care Organization 25Figure 2.2 Balance Sheet for a Not-for-Profit Health Care Organization 28Figure 2.3 Statement of Cash Flows for a Health Care Organization 33Figure 2.4 Graphical Break-Even Analysis 53Figure 2.5 Crossover Graph 55Figure 3.1 Flowchart/Process Map for the Nurse’s Station Example 68Figure 4.1 Histogram for Daily Recorded DRG Codes 79Figure 4.2 Relative Frequency Diagram 80Figure 4.3 Excel Options Window 92Figure 4.4 Excel Add-Ins Choices within the Options Window 93Figure 4.5 Excel Add-Ins Menu 93Figure 4.6 Data Analysis Window 94Figure 4.7 Excel Spreadsheet to Accompany Histogram Example 97Figure 4.8 Histogram Dialogue Box 98Figure 4.9 Histogram Dialogue Box with Specific Graphing Options

Checked 99

TABLES AND F IGURES � xiii

Figure 4.10 Histogram with Cumulative Percentage Overlay 99Figure 4.11 Reject/Accept Regions for Two-Tailed t-Tests 107Figure 4.12 Pharmacy Data in Excel 112Figure 4.13 Tools Menu and Data Analysis Option in Excel 113Figure 4.14 t-Test: Two-Sample Assuming Equal Variances Option

in Excel 113Figure 4.15 t-Test Dialogue Box in Excel 114Figure 4.16 Data Analysis Output for t-Test 114Figure 4.17 Pareto Diagram in Excel 118Figure 4.18 Pareto Diagram with 80 Percent Mark Displayed 119Figure 4.19 Basic Box Plot 119Figure 4.20 Data for Box Plots 121Figure 4.21 2-D Stacked Column Option 123Figure 4.22 Stacked Column Graph after Column Switch 124Figure 4.23 Error Bar Menus 125Figure 4.24 Input Window for Error Bar Input 126Figure 4.25 Format Error Bars Menu 126Figure 4.26 Special Value Input Menu 127Figure 4.27 Box Plot Graph after Error Bar Formatting 127Figure 4.28 Final Box Plot Graph 128Figure 4.29 Insert Tab and Bar Chart Option Menu 131Figure 4.30 Preliminary Bar Chart for Tornado Diagram 131Figure 4.31 Format Axis Menu x-Axis 132Figure 4.32 Format Data Series Option Screen 133Figure 4.33 Format Axis Menu y-Axis 134Figure 4.34 Tornado Diagram 134Figure 5.1 Decision Tree for Litigation Example 145Figure 5.2 Excel Spreadsheet for Sarah’s Equipment Payoff Table 152Figure 5.3 Excel Spreadsheet for Maximax Decision Criterion 153Figure 5.4 Excel Spreadsheet for Maximin Decision Criterion 154Figure 5.5 Excel Spreadsheet for Minimax Regret Decision Criterion 157Figure 5.6 Excel Spreadsheet for Hurwicz Criterion 160Figure 5.7 Sensitivity Analysis Data Calculations 167Figure 5.8 Final Chart Output in Excel 169Figure 5.9 Scatter Chart Menu in Excel 170Figure 5.10 Insert Chart Menu in Excel 170

xiv � TABLES AND F IGURES

Figure 5.11 Format Axis Option after Right Click in Excel 171Figure 5.12 Format Axis Menu in Excel 171Figure 5.13 Layout Tab for Modifying Graphs in Excel 172Figure 5.14 Move Chart Option for Modifying Graphs in Excel 172Figure 5.15 Move Chart Dialogue Box for Modifying Graphs in Excel 172Figure 5.16 Excel Output for Medical Equipment Sensitivity Analysis 173Figure 5.17 Payoff Table for Sarah’s Medical Equipment Example 180Figure 5.18 Decision Tree for Sarah’s Medical Equipment Example 181Figure 5.19 Decision Tree for Sarah’s Medical Equipment Example

under Equal Likelihood Scenario 183Figure 5.20 Multistage Decision Tree Example 185Figure 5.21 Excel Options Button 186Figure 5.22 Excel Options Window 187Figure 5.23 Excel Add-Ins Menu 188Figure 5.24 TreePlan Option in Add-Ins Tab 188Figure 5.25 Initial TreePlan Menu 188Figure 5.26 Initial Decision Tree 189Figure 5.27 TreePlan Formula Example 189Figure 5.28 TreePlan Add/Change/Modify Dialogue Box 190Figure 5.29 Decision Tree with Event Node Added 191Figure 5.30 TreePlan Menu for Modifying an Existing Node 191Figure 5.31 Example Tree Depicting Data Entry Areas 192Figure 6.1 Process Flow at Low-Acuity Emergency Department 203Figure 6.2 Graph of Multinomial Distribution 206Figure 6.3 Graph of Poisson Distribution (λD 5) 206Figure 6.4 Graph of Exponential Distribution 208Figure 6.5 Graph of Normal Distribution 209Figure 6.6 Discrete Simulation Flow for Process of Figure 6.1 214Figure 6.7 Excel Screen Shot forMilitary Recruit BloodWork Example 221Figure 7.1 Process Map for Room Turnover Process 232Figure 7.2 Current State Map 234Figure 7.3 Future State Map 235Figure 7.4 Staffing Profile 242Figure 7.5 Process Flow at Low-Acuity Emergency Department 254Figure 8.1 Hospital Unit 259Figure 8.2a Centralized Medication Storage 260

TABLES AND F IGURES � xv

Figure 8.2b Decentralized Medication Storage 261Figure 8.3 Muther Diagram for Health Care Example 264Figure 8.4 Alternative Designs for Evaluation 269Figure 8.5 Graphical Solution to Health Care Example 271Figure 8.6 Excel Formulation for Health Care Example 274Figure 8.7 Solver Parameters Dialogue Box 276Figure 8.8 Add Constraint Dialogue Box 276Figure 8.9 Solver Parameters for Health Care Example 277Figure 8.10 How to Set Integer Constraints for Health Care Example 277Figure 8.11 Final Step When Setting Integer Constraints 278Figure 8.12 Final Solver Parameters Dialogue Box for Health Care

Example 278Figure 8.13 Solver Options Dialogue Box 279Figure 8.14 Final Results for Solver for Health Care Example 280Figure 8.15 Possible Department Layout 282Figure 9.1 Check Sheet for Admission Delays 295Figure 9.2 Example Flowchart for Patient Check-In and to Room

Process 296Figure 9.3 Cause-and-Effect or Fishbone Diagram 298Figure 9.4 Histogram for Delay Times 299Figure 9.5 Pareto Diagram for Medical Documentation Errors 300Figure 9.6 ScatterDiagramof Patients perDay versusDay of theWeek 301Figure 9.7 X-Bar Control Chart Example 302Figure 9.8 Control Chart with Control Limits and Zones 304Figure 9.9 DMAIC Process 307Figure 9.10 Six Sigma DMAIC Process Metrics 309Figure 10.1 Spreadsheet for Control Chart Calculations 328Figure 10.2 x-Bar Chart 329Figure 10.3 R Chart 330Figure 10.4 Process Capability Spreadsheet Calculations 336Figure 10.5 House of Quality Example 342Figure 11.1 Sample Kanban 358Figure 11.2 Value StreamMap for Hennepin County Medical Center 367Figure 12.1 Trend Line 371Figure 12.2 Nonlinear Trend Data Pattern Example 372Figure 12.3 Seasonal Data Pattern Example 373Figure 12.4 Combined Trend and Seasonal Data Pattern Example 374

xvi � TABLES AND F IGURES

Figure 12.5 Naive Forecast for Beds Demanded 377Figure 12.6 Data Analysis Dialogue Box 379Figure 12.7 Excel’s Moving Average Dialogue Box 380Figure 12.8 Three- and Five-Year Moving Averages for Bed Demand Time

Series Data 381Figure 12.9 Graph of Baseline, Three-Year, and Five-Year Moving

Averages 382Figure 12.10 Data Analysis Dialogue Box 384Figure 12.11 Excel’s Exponential Smoothing Dialogue Box 385Figure 12.12 Graph of Baseline and Exponentially Smoothed Bed

Demand Data 386Figure 12.13 Lagged Time Series Example and Correlation Estimate 388Figure 12.14a Seasonal Data for Hospital Bed Example 389Figure 12.14b Graph of Seasonal Data for Hospital Bed Example 390Figure 12.15 Seasonally Sorted Demand Data 391Figure 12.16 Combined Graph of Original Time Series and Forecasted

Data 393Figure 12.17 Scatter Plot of a Perfect Positive Linear Relationship 396Figure 12.18 Scatter Plot of a Perfect Negative Linear Relationship 396Figure 12.19 Scatter Plot Depicting a Curvilinear Relationship 397Figure 12.20 Scatter Plot Depicting No Linear Relationship 397Figure 12.21 Simple Linear Representation 399Figure 12.22 Regression Output from Excel for Patient Satisfaction

Example 404Figure 12.23 Excel Output for Residual/Error Calculations 411Figure 12.24 Excel File Tab 413Figure 12.25 Excel Options Add-Ins Menu 413Figure 12.26 Add-Ins Dialogue Box 414Figure 12.27 Glucose Area Data Set 415Figure 12.28 Data Analysis Option in Excel 416Figure 12.29 Data Analysis Options Menu 417Figure 12.30 Data Analysis Regression Menu 417Figure 12.31 Regression Output for Glucose Data Set 418Figure 12.32 Data Analysis Menu Option in Excel Ribbon 421Figure 12.33 Data Analysis Dialogue Box in Excel 422Figure 12.34 Correlation Menu in Excel’s Data Analysis Package 422Figure 12.35 Correlation Matrix for Age and BMI 423

TABLES AND F IGURES � xvii

Figure 13.1 Generic Work Breakdown Structure 438Figure 13.2 Network for Simple Project Example 441Figure 13.3 Network for Health Care Project Example 445Figure 13.4 Gantt Chart for Health Care Project 446Figure 13.5 Resource Leveling—Delaying Activity D 446Figure 13.6 Resource Leveling—Delaying Activity E 447Figure 13.7 Project Data 448Figure 13.8 Project Data Formulas 449Figure 13.9 Intermediate Step—Gantt Chart Creation 449Figure 13.10 Gantt Chart in Excel 450Figure 13.11 Activity-on-Arc Network Diagram 451Figure 13.12 PERT Example in Excel 453Figure 13.13 Network for Electronic Medical Records Implementation 458Figure 14.1 Aggregate Planning Hierarchy in a Health Care

Organization 464Figure 14.2 Scheduling Framework for a Health Care Organization 469Figure 14.3 One-Dimensional Horizontal Matrix with Five

Job/Patient Slots 477Figure 14.4 Johnson’s Rule First Iteration 477Figure 14.5 Johnson’s Rule Second Iteration 477Figure 14.6 Johnson’s Rule Third Iteration 477Figure 14.7 Johnson’s Rule Fourth Iteration 478Figure 14.8 Johnson’s Rule Fifth and Final Iteration 478Figure 14.9 Spreadsheet to Accompany Johnson’s Rule Patient Processing

Problem 479Figure 14.10 Gantt Chart for Patient Scheduling Problem 482Figure 14.11 Stacked Bar Option 483Figure 14.12 Initial Bar Chart for Gantt Chart Creation 484Figure 14.13 Data Option Menu 485Figure 14.14 Preliminary Gantt Chart for First Process Complete

Paperwork 485Figure 14.15 Formatted Gantt Chart 486Figure 14.16 Coordinate Locations for the County Demand Locales 490Figure 14.17 Excel Spreadsheet for Center of Gravity Method 492Figure 15.1 Spreadsheet Model Using Given Value of Q 507Figure 15.2 Cost Formulas for Figure 15.1 508

xviii � TABLES AND F IGURES

Figure 15.3 Spreadsheet Model Using Formula to Calculate EconomicOrder Quantity 508

Figure 15.4 Cycles in a Periodic Review System 511Figure 15.5 Periodic Review Journal Entries for Health Care Corp. 513Figure 15.6 Formulas for Figure 15.5 514Figure 15.7 Continuous Review Journal Entries for Health Care

Corp. 514Figure 15.8 Formulas for Figure 15.7 515Figure 15.9 Inventory Data 517Figure 15.10 Percent Total Dollar Volume Data 518Figure 15.11 Sorted Data 518

TABLES AND F IGURES � xix

PREFACE

The health care field is a complex industry with numerous players, from end-userpatients to insurance companies to large medical facilities. Health care facilitiesmove large numbers of patients through many processes while attempting tomaintain the proper supply of medical products as well as health care expertsto complete the required care. Although generally viewed as a service-basedindustry, the health care field faces some of the most complex operations andsupply chain challenges of any industry.

In today’s world of government spending cuts and health care reform, healthcare facilities must closely monitor their operations and determine ways to improvetheir efficiency in order to survive. Gone are the days of unlimited supplies, carefreespending, and billing Medicare or Medicaid for hospital-acquired conditions.Health care facility managers face two daunting tasks: first, they must change themind-set and culture of the health care workers, including the doctors; second, theymust implement data-driven decision making across all areas of their facilities.

Many of the behaviors and practices that occur in health care facilities are donesimply because “that’s the way it has always been done.” This practice of doingthings one way because it is the only way they have ever been done can be costly.

National health expenditure data obtained from the website of the Center forMedicare and Medicaid Services (CMMS) (www.cmms.gov/home/rsds.asp)indicate that total health expenditures in the United States will exceed $4.6 billionby 2020, with these expenditures accounting for almost 20 percent of the U.S.gross domestic product by that time. Figure P.1 and Figure P.2 were generatedusing CMMS data for 2005 through 2020. Data for the years 2009–2020 areprojections only.

Not only are health expenditures in general on the rise, but supply chaincosts in the health care industry are also taking a toll on health care facilities’

budgets. Research conducted at the University of Arkansas indicates thatrevamping the supply chain in the health care industry can reduce costs signif-icantly (Nachtmann and Pohl 2009). The results of this research indicate that,among those companies completing the research survey, the average health careprovider spends more than $100 million annually on supply chain operations.For most of these organizations, that is about one-third of their annual budgets(Nachtmann and Pohl 2009).

FIGURE P.1 Graph of Projected Health Expenditures

2005$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

$4,000

$4,500

$5,000$

bill

ions

2010 2015 2020

FIGURE P.2 Health Expenditures as a Percentage of Gross Domestic Product

15.0

15.5

16.0

16.5

17.0

17.5

Perc

ent 18.0

18.5

19.0

19.5

20.0

2010 020251025002

xxii � PR E F A C E

Supply chain costs are not the only area impacting health care settings. Manyoperational errors are costing hospitals and patients lots of money each year. Forexample, there are hundreds of cases each year of surgeons mistakenly leaving asponge, tool, or other object inside a patient (known as a retained foreign body).Research indicates this happens in over 12 percent of surgeries (Gamble 2008),and each instance can cost up to $50,000 (Jaspen 2008).

Another costly operational issue is nosocomial infection, better known ashospital-acquired infection. Obviously, people who are ill have reduced resistanceto fungal and bacterial infections, and thus there is a risk that hospital patientswill acquire infections if rooms, equipment, and instruments are not keptclean and sanitary. During the decade of the 1990s, hospital-acquired infectionsincreased the U.S. health care system’s annual cost between $4.5 and $5.7 billioneach year (Graves 2004). During this same time period, the average cost perinfection was almost $14,000, with surviving patients experiencing an averagecost increase of $40,000 (Stone, Larson, and Kawar 2002). More recent costfigures indicate that the annual cost of these infections had grown to exceed$6.5 billion by 2002 (Graves 2004).

Sponges left in patients and hospital-acquired infections are just two exam-ples of operational challenges facing health care facilities, and both are prevent-able. Through the application of systematic, thorough procedures, the occurrenceof these errors can be greatly reduced. Data clearly indicate that the cost of thesemistakes is exorbitant. Health care managers must find a way to focus personnelon making changes that will reduce these errors, thus saving the facility moneyand improving the well-being of its patients.

Experience has shown that with health care operations, removing the barriersthat reinforce the “that’s the way it has always been done” mind-set can offertremendous financial benefit. As an example, consider a small surgery clinicwhere minor surgical procedures are performed. If the clinic manager permitsthe doctors to perform surgery in the surgical room of their choice, then fewerthan 60 surgeries per day can be performed. If the clinic manager schedules eachsurgery in the next available surgical room, assuming all rooms contain the samesurgical equipment, then over 75 surgeries per day can be performed. By notallowing the doctors to pick and choose the rooms in which they operate, a25 percent increase in throughput can be realized (Centeno and Dodd 2011).The assigning of surgical rooms in this logical manner also reduces patient waittime, which should lead to improved patient satisfaction.

PR E F A C E � xxiii

PURPOSE OF THIS BOOK

This book is intended to be a foundational resource for teaching the utilization ofoperations and supply chain management (OSCM) in health care management andadministration. The text should arm health care facility managers and health careoperations analysts with the type of data collection and analysis skills required torealize where and how operational efficiencies can be realized. From understandingsupply chains (Chapter 1) and financial aspects of health care operations (Chapter2), to best practices in scheduling (Chapter 14) and inventory management(Chapter 15), this book takes a comprehensive look at health care operations.

It illustrates concepts and techniques that many health care facilities may haveheard of but may have not yet adopted or have not fully implemented. Theseconcepts and techniques are all in areas that are considered leading edge in theoperations and supply chain management discipline.

The book introduces the operations and supply chain management conceptsin health policy and administration while incorporating the features and func-tions of Microsoft Excel where appropriate. It provides real data and examplesfrom health care settings to assist in the understanding of the main conceptscontained in each chapter.

A strength of this work is that it is organized differently from other textbookswithin this category. One main differentiator is the addition and inclusion ofsupply chain management material to the traditional health care operations topics.Over the past 10 years, the health care industry has driven a trend to modify thetraditional operations curriculum by adding supply chain content and includingtopics such as lean and six sigma. The integration of Excel and spreadsheet modelsthroughout the operations and supply chain material also makes this work unique.The chapters provide material on how to use Excel as a tool within health careoperations and supply chain management.

Real-world case examples within the context of health care administrationhighlight the use of Excel as a valuable decision-making tool for students andhealth care executives. The work provides novel features such as:

� Leading-edge concepts and techniques that many health care facilities mayhave heard of but not yet adopted or not fully implemented (e.g., the pushlately for training in six sigma and lean).

� Real data and examples from health care settings to assist in the under-standing of the main concepts contained in the text.

xxiv � PR E F A C E

� Employing Excel as a powerful analytical tool to assist managers in theinvestigation of their operational setting using data-driven techniques andspeaking to the interpretation/communication of the results.

INTENDED AUDIENCE

Students and practitioners using this book come from a variety of backgroundsand have different levels of understanding of many concepts it covers. For thisreason, we provide details at the introductory level, assuming little or no quan-titative background. Readers who desire more detail on certain topics will find thechapters’ references to be valuable sources of additional information and depth.

The text can be employed in undergraduate health administration programs,nursing programs, business programs with health care certificates or concentra-tions, and maybe even some engineering courses with a bent toward improvinghealth care processes and delivery.

On a graduate level, the text would lend itself to areas such as pharmacyadministration, nursing and nursing administration, health information admin-istration, MBA programs with health care certificates or concentrations, andhealth informatics.

Undergraduate as well as graduate health care administration students willfind the text an excellent educational resource. In addition, practicing healthpolicy and health administration managers can also use the book as a reference forday-to-day problem solving. The text helps these students and practitionersrealize the importance of sound operations and supply chain management.

ORGANIZATION OF THIS BOOK

The book is organized into four major parts: Strategy, Process Design andAnalysis of Health Care Operations, Managing Health Care Operations Quality,and Planning and Controlling Health Care Operations.

Part I begins with an introduction to supply chains and their role in healthcare operations (Chapter 1). This is followed by chapters that detail financial(Chapter 2) and managerial (Chapter 3) aspects of health care operations.

Part II provides examples of the proper use of data and statistical tools foroperations improvement (Chapter 4) and includes numerous tools for problemsolving and decision making (Chapter 5). Oftentimes, operations improvements

PR E F A C E � xxv

require one to be able to pose what-if scenarios and evaluate alternatives.Simulation (Chapter 6) is introduced as a tool for this type of helpful yetinexpensive analysis.

Just as goods must flow efficiently through a production facility, proper patientflow (Chapter 7) can contribute significantly to a health care facility’s efficiency.Additionally, patient flow is affected by facility layout and design (Chapter 8).

Part III is devoted to quality, which has also become imperative for healthcare facilities to survive in today’s competitive market. Managing quality(Chapter 9) and quality control and improvement (Chapter 10) are topics thathealth care operations managers must understand if they are to create andmaintain a reputation for outstanding service at their facility.

Part IV begins with the concepts of a lean enterprise (Chapter 11), which arealso important when it comes to maintaining a competitive edge. Application oflean concepts to a service industry such as health care can have dramatic impactson patient satisfaction and cost of care.

It is not always possible for all types of health care facilities to accuratelyforecast demand for their services; however, a good understanding of basicforecasting concepts and techniques (Chapter 12) can enable facilities to providebetter care by ensuring that appropriate numbers of resources, such as beds andworkers, are available.

Health care managers, like all managers, must be able to apply best practices inproject management (Chapter 13), scheduling (Chapter 14), and inventory man-agement (Chapter 15). These three topics are covered in the book’s final chapters.

USE OF EXCEL IN HEALTH CARE OPERATIONS

Throughout the text, we have included numerous examples of how to utilize MSExcel to solve health care operations problems. It is critical that the reader takeadvantage of the Excel instructions and examples, as most health care settingswill not have or be able to afford specialized software for problem solving andoptimization. Excel is a simple yet powerful tool that is available on most PCsencountered in the workplace. Excel’s ease of use and widespread availability maymake its solutions more acceptable to management. Physicians and other healthcare workers are likely to have used Excel previously, so explaining the derivationof solutions may be simpler in the context of Excel.

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In Chapters 2 and 3, financial analysis is performed using Excel. Examplesinvolving the construction of balance sheets, operating statements, and state-ments of cash flows are illustrated. Calculations of financial ratios within aspreadsheet are also shown. Finally, the format for activity based costing methodsis illustrated using an Excel template.

Chapter 4 includes an example of how Excel can be used to perform requiredstatistical analyses. In addition to presenting the construction of histograms andPareto diagrams using Excel’s Data Analysis add-in package, the Data Analysisadd-in is used to test hypotheses using analysis of variance (ANOVA). Excel isalso used to construct box-and-whiskers plots and tornado diagrams.

In Chapter 5, problem solving and decision making are accomplished usingExcel. The chapter presents construction of payoff tables along with the useof decision criteria via a spreadsheet, and shows expectation calculations usingrelative references within Excel. In addition, the construction of decision trees aswell as sensitivity graphs is presented.

A queuing example in Excel is utilized in Chapter 6. The example walks thestudent through the creation of arrival times and services times based on a givendistribution and the calculation of wait time, system time, and server idle time foreach entity that enters the system. It also explains how to calculate summary statisticssuch as average wait time, average number waiting in line, and server utilization.

Due to the content of Chapters 7, 8, and 9, Excel examples are not employedin those chapters.

Examples of using Excel to aid in quality control are included in Chapter 10.Specifically, the chapter provides Excel templates for the construction of statisticalprocess control charts and the calculation of capability ratios and indices.

Chapter 11 did not lend itself to Excel examples.Forecasting using Excel is demonstrated through examples in Chapter 12.

Excel’s Data Analysis add-in is again employed in calculating moving averages,exponential smoothing models, linear regression (simple and multiple) models,and correlation coefficients. Excel templates are presented for error calculationsrelated to the forecasting models.

In Chapter 13, an Excel example is used to demonstrate resource leveling.Additional Excel examples are included to assist with the development of a criticalpath method (CPM) model and two types of Gantt charts. There is also an Excelexample for the Program Evaluation and Review Technique (PERT).

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Applications of using Excel for scheduling and capacity management aregiven in Chapter 14. Johnson’s rule for sequencing is presented in spreadsheetformat along with the construction of Gantt charts. In addition, an Excel templateis constructed to illustrate the center of gravity facility location technique.

In Chapter 15, inventory analysis is performed using Excel. An exampleinvolving calculation of the economic order quantity (EOQ) is included to dem-onstrate how total annual cost can be reduced if the order quantity is set to the EOQvalue. The chapter also includes an Excel example on ABC inventory management.

OTHER PEDAGOGICAL FEATURES

In addition to the step-by-step discussions of how health care operations pro-blems are solved using Excel, each chapter includes end-of-chapter exercises thataddress the material covered in that section. Most of these exercises include thereplication of examples from that chapter. The purpose is to provide students animmediate reference with which to compare their work and determine whetherthey are able to correctly carry out the procedure involved. Data for all theexercises are included on the web at www.josseybass.com/go/.

A supplemental package available to instructors includes all answers to thesection exercises. In addition, the supplemental package will contain exam ques-tions with answers and selected Excel spreadsheets that can be used for class pre-sentations, along with suggestions for presenting these materials in a classroom.However, the book can be effectively used for teaching without the additionalsupplemental material.

Users who would like to provide feedback, suggestions, corrections, examplesof applications, or whatever else can e-mail John at krosj@ecu.edu. The websitefor additional resources and information is www.josseybass.com/go/krosbrown.

Please feel free to contact John and provide any comments you feel areappropriate.

ACKNOWLEDGMENTS

As always, this effort would not have been possible without the support andguidance of numerous colleagues, friends, family, and all those poor souls whohad to listen to us bounce ideas off of them, or for that matter anyone whojust had to listen to us!

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