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Handbooks in Health Economic Evaluation, volume 2

It is becoming increasingly important to examine the relationship between the outcomes of a clinical trial and the costs of the medical therapy under study. The results of such analysis can affect reimbursement decisions for new medical technologies, for example drugs, devices or diagnostics; aid companies seeking to make claims about the cost-effectiveness of their product; allow early consideration of the economic value of therapies, which may be important to improving initial adoption decisions; or address the requirements of regulatory bodies. Economic evaluation in clinical trials uses a consistent set of data collected within the trial, or by projection from this data, and avoids having to incorporate unrelated (and potentially inconsistent) data from many different sources.

This book provides a practical guide to conducting economic evaluation in ongoing clinical trials. It covers issues and techniques related to the collection of both cost and outcome data, as well as a framework for reporting and interpreting economic reports from clinical trials. This is illustrated by detailed supporting examples and exercises, designed to teach the reader how to apply this model. These exercises are supported with datasets, programmes and solutions made available online.

Supporting Material

This web page and the web address below provide datasets and programs for Stata for Windows (Stata Corporation, College Station, Texas, U.S) as examples of the analysis of cost (and QALYs) discussed in chapter 5, estimation of sampling uncertainty for the comparison of cost and effect, and calculation of sample size and power for cost-effectiveness analysis in clinical trials (both discussed in chapter 9).  We anticipate that the web-based material will be expanded and updated over time.

Alternative web address:


Supported Chapters:

Chapter 5:

Univariate Analysis of Cost

Chapter 9:

Sampling uncertainty:calculation, sample size and power, and decision criteria

Confidence Interval for CER, CI for NMB, and acceptability curves

Sample Size and Power for Cost-Effectiveness Analysis


  • Henry A. Glick Professor of Medicine, Division of General Internal Medicine, Perelman School of Medicine; Professor of Health Care Systems, Wharton School; Senior Fellow, Leonard Davis Institute of Health Economics; Associate Scholar, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, USA; Visiting Professor, Institute of Health and Wellbeing, University of Glasgow, United Kingdom.
  • Jalpa A. Doshi Associate Professor of Medicine, Division of General Internal Medicine, Perelman School of Medicine; Director, Economic Evaluations Unit, Center for Evidence-Based Practice; Director, Value-Based Insurance Design Initiatives; Center for Health Incentives and Behavioural Economics; Senior Fellow, Leonard Davis Institute of Health Economics, University of Pennsylvania, USA.
  • Seema. S. Sonnad Director of Health Services Research, The Value Institute, Christiana Care Health System, USA; Adjunct Associate Professor, Department.
  • Daniel Polsky Robert D. Eilers Professor, Health Care Management, The Wharton School; Professor of Medicine, Division of General Internal Medicine, Perelam School of Medicine; Executive Director, Leonard Davis Institute of Health Economics; University of Pennsylvania, USA.

Ordering this book          

Oxford University Press,
ISBN: 9780199685028

Go to our Handbooks homepage for details on how to order.