Health economics in drug development: efficient research to inform healthcare funding decisions

Peter Hall, Christopher McCabe, Julia M Brown, David A Cameron

Research output: Contribution to journalArticlepeer-review

Abstract

In order to decide whether a new treatment should be used in patients, a robust estimate of efficacy and toxicity is no longer sufficient. As a result of increasing healthcare costs across the globe healthcare payers and providers now seek estimates of cost-effectiveness as well. Most trials currently being designed still only consider the need for prospective efficacy and toxicity data during the development life-cycle of a new intervention. Hence the cost-effectiveness estimates are inevitably less precise than the clinical data on which they are based. Methods based on decision theory are being developed by health economists that can contribute to the design of clinical trials in such a way that they can more effectively lead to better informed drug funding decisions on the basis of cost-effectiveness in addition to clinical outcomes. There is an opportunity to apply these techniques prospectively in the design of future clinical trials. This article describes the problems encountered by those responsible for drug reimbursement decisions as a consequence of the current drug development pathway. The potential for decision theoretic methods to help overcome these problems is introduced and potential obstacles in implementation are highlighted.
Original languageEnglish
Pages (from-to)2674-80
Number of pages7
JournalEuropean Journal of Cancer
Volume46
Issue number15
DOIs
Publication statusPublished - 2010

Keywords

  • Biomedical Research
  • Clinical Trials as Topic
  • Cost-Benefit Analysis
  • Decision Making
  • Decision Support Techniques
  • Delivery of Health Care
  • Financing, Organized
  • Humans
  • Research Design
  • Technology, Pharmaceutical

Fingerprint

Dive into the research topics of 'Health economics in drug development: efficient research to inform healthcare funding decisions'. Together they form a unique fingerprint.

Cite this