Designing and Conducting Cost-Effectiveness Analyses in Medicine and Health Care
Buy Rights Online Buy Rights

Rights Contact Login For More Details

More About This Title Designing and Conducting Cost-Effectiveness Analyses in Medicine and Health Care

English

Peter Muennig is the director of program in cost-effectiveness and outcomes at the Robert J. Milano Graduate School of Management and Urban Policy at New School University, where he teaches courses in cost-effectiveness, decision analysis, and epidemiology.

English

Acknowledgments.

List of Tables, Figures, and Exhibits.

Tables.

Figures.

Exhibits.

Preface.

How to Use this Book.

A Note on Methods.

1 Introduction to Cost-Effectiveness.

What Is Cost-Effectiveness Analysis?

Elements of Cost-Effectiveness Analysis ? Why Conduct Cost-Effectiveness Analysis? ? Scope and Aims of Cost-Effectiveness Analysis.

Cost-Effectiveness Analysis and Policy.

Making Comparisons Across Diseases ? Do Cost-Effectiveness Analyses Lead to Policy Changes?

Principles of Cost-Effectiveness Analysis.

The Perspective of a Cost-Effectiveness Analysis ? The Cost-Effectiveness Ratio ? The Numerator of the Cost-Effectiveness Ratio ? The Denominator of the Cost-Effectiveness Equation ? Allocating Costs in the Cost-Effectiveness Ratio ? Interpreting the Cost-Effectiveness Ratio ? Comparing Interventions ? Defining the Comparator ? Interpreting Incremental Changes in Cost and Effectiveness.

Other Types of Analyses.

Cost-Effectiveness Versus Cost-Utility Analysis ? Cost-Benefit Analysis ? Cost-Minimization Analysis ? Burden of Disease Analysis.

2 Developing a Research Project.

The Ten Steps to a Perfect Research Project.

Developing a Research Question.

Designing Your Analysis.

Step 1: Learn About the Disease ? Step 2: Chart Out the Course of the Disease ? Step 3: List the Data Elements That You Will Need.

3 Working with Data.

Overview.

Review of Rates.

Prevalence Versus Incidence ? The Relationship Between Risks and Rates ? Risk over a Long Period of Time.

Understanding Error.

Common Types of Error ? Managing Error in Cost-Effectiveness Analysis ? Frequency Distributions and Random Error.

Calculating Weighted Means.

Evaluating Study Limitations.

Review of Medical Study Designs ? Evaluating the Medical Literature.

4 Finding the Data You Need.

Overview.

Finding Information in the Medical Literature.

Using Electronic Datasets.

Finding the Electronic Data That You Need ? Which Dataset Should You Use? ? Using Data Extraction Tools ? Using Printed Tabulations of Electronic Data ? Understanding Error in Electronic Data.

Using Data from Unpublished Research Projects.

Using Data from Piggybacked Studies.

Using Expert Opinion.

Organizing Your Data.

Summarizing Journal Articles ? Summarizing Data.

5 Working with Probabilities.

Overview.

Incidence and Prevalence.

Incidence Rate of Influenza-Like Illness.

Secondary Transmission of Infectious Disease.

Secondary Transmission of Influenza.

Duration of Illness.

Duration of Influenza-Like Illness.

Efficacy and Measures of Risk.

Bias in Screening Interventions ? Efficacy of Strategies to Prevent Influenza-Like Illness.

Laboratory Test Data.

Laboratory Testing for Influenza.

Distribution of Disease.

Distribution by Age ? Distribution by Stage ? Distribution by Gender, Race, and Socioeconomic Status ? Other Considerations Regarding the Distribution of Diseases ? Distribution of Influenza-Like Illness.

Secondary Complications of Illness.

Secondary Complications of Influenza-Like Illness.

Medical Care Utilization.

Rates Obtained from Electronic Data. ? Hospitalization Data for Influenza-Like Illness ? Ambulatory Care Data for Influenza-Like Illness.

Side Effects.

Side Effects Due to Vaccination or Treatment.

Health-Related Quality of Life Scores.

Obtaining Scores from Published Lists ? Generating HRQL Scores Using Instruments.

Mortality Data.

Mortality Among Persons with Influenza-Associated Conditions.

6 Working with Costs.

Overview.

Opportunity Costs ? Three Steps to Estimating Costs ? Micro-Costing and Gross-Costing.

Measuring Changes in Costs.

Fixed Costs and Variable Costs ? Friction Costs and Transfer Payments.

Using Diagnosis Codes.

Future Medical Costs.

Adjusting Costs.

Adjusting for Inflation ? Calculating Cost-to-Charge Ratios ? Estimating the Cost of Ambulatory and Laboratory Services ? Discounting Future Costs.

Assessing the ?Relevancy? of Cost Data.

Determining Which Costs to Include.

Hospital and Ambulatory Costs ? Time Costs ? Transportation Costs ? Side Effects ? Medication Costs ? Caregiver Costs.

7 Constructing a Model.

Introduction to Decision Analysis.

Types of Decision Analysis Models ? Constructing Simple Decision Analysis Models.

Building the Influenza Model.

Defining the Initial Branches ? Defining Variables in the Decision Analysis Model ? Entering Formulas Into the Decision Analysis Model ? Defining Terminal Nodes ? Defining Ambulatory Care Needs ? Secondary Complications ? Defining Antibiotic Use and Side Effects ? Defining Hospitalization Costs ? Patient Compliance ? Final Costs.

8 Working with Quality of Life Measures.

Overview.

Framework.

Who Should Valuate HRQL?

Deriving HRQL Scores.

Using Preference-Weighted Generic Instruments ? HRQL Scores Generated from Large Health Surveys ? Using Disability-Adjusted Life Years.

Things to Consider Regarding HRQL Scores.

The Effect of Age on HRQL ? The Effect of Disease Stage on HRQL ? The Effect of an Intervention on HRQL ? Use of HRQL Scores in Diverse Populations ? Direct Versus Indirect HRQL Scores.

9 Calculating Quality-Adjusted Life Years.

Overview.

Using the Life Table Method ? Charting the Lifetime Health Path of Your Cohort ? Using the Summation Method ? Using the DALY Method.

Calculating QALYs in the Sample Analysis.

Calculating HRQL Scores for Influenza-Like Illness ? Calculating Years of Life Lost ? Calculating QALYs in the Vaccination Arm ? Calculating QALYs in the Treatment Arm ? Incremental Cost-Effectiveness of Each Intervention ? Using QALYs in Decision Analysis Models.

10 Conducting a Sensitivity Analysis.

Overview.

One-Way Sensitivity Analysis.

Using One-Way Sensitivity Analyses to Validate a Model ? Answering Secondary Questions Using One-Way Sensitivity Analyses ? Determining ?Plausible? High and Low Values.

Two-Way Sensitivity Analysis.

Analysis of Influence.

Determining the Plausible Range of Each Variable ? Generating an Influence Diagram.

Monte Carlo Simulation.

How Monte Carlo Simulations Work ? Defining Distributions ? Conducting a Monte Carlo Simulation.

11 Preparing Your Study for Publication.

Overview.

Content and Structure of Cost-Effectiveness Articles.

Introduction ? Methods ? Results ? Discussion ? The Technical Appendix.

Publishing Your Research.

What Editors Want ? Choosing the Appropriate Journal.

12 Advanced Concepts.

Overview.

Working with Measures of Risk.

Bayes? Theorem.

Generating Life Tables.

Calculating QALE Using Published Data ? Generating QALE Using Electronic Data.

Using Markov Models.

Markov States ? How Markov Models Work ? Benefits of Markov Modeling.

Appendix One: Solutions to Exercises.

Chapter One ? Chapter Three ? Chapter Four ? Chapter Five ? Chapter Six ? Chapter Nine ? Chapter Ten.

Appendix Two: Journal Summaries.

Appendix Three: Census Tables.

Appendix Four: HRQL Scores Derived from the Years of Healthy Life Measure.

Appendix Five: Life Tables and Quality-Adjusted Life Tables.

Appendix Six: The EuroQol Instrument.

References.

The Author.

Index.

English

"?strongly recommended for those individuals interested in a basic presentation of applied cost-effectiveness analysis and cost-utility analysis in health technology assessment?"(Journal of Drug Assessment, No.5, 2002)"Dr. Muennig has written a highly accessible guide to cost-effectiveness analysis that bridges the latest theoretical developments with pragmatic instruction, informative examples, and even tips for online data sources. Students and professionals alike will benefit from the step-by-step clarity with which Dr. Muennig presents and dissects the complex methods that underlie this increasingly important tool for rational decision making in medicine and health policy."
--Marianne C. Fahs, associate professor and director, Health Policy Research Center, Milano Graduate School of Management and Urban Policy, New School University, New York
loading