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Measuring Delay Discounting in Humans Using an Adjusting Amount Task
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Converting condition-specific measures into preference-based outcomes for use in economic evaluation.

Jennifer Petrillo1, John Cairns

  • 1London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT, UK; United BioSource Corporation, 20 Bloomsbury Square, London WC1A 2NS, UK. jennifer.petrillo@lshtm.ac.uk.

Expert Review of Pharmacoeconomics & Outcomes Research
|June 10, 2010
PubMed
Summary
This summary is machine-generated.

Quality-adjusted life-years (QALYs) are crucial for cost-effectiveness in healthcare. This review explores using condition-specific data to generate QALYs, enhancing health technology assessments.

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Area of Science:

  • Health Economics
  • Outcomes Research

Background:

  • Quality-adjusted life-years (QALYs) are vital for healthcare reimbursement decisions.
  • Generic QALY measures (e.g., EQ-5D) are widely used but may not capture all relevant health aspects.
  • There is growing interest in utilizing condition-specific data for QALY generation.

Purpose of the Study:

  • To review recent research on using condition-specific data for QALYs.
  • To explore methods for integrating condition-specific data into cost-effectiveness analyses.
  • To inform assessments of health technologies.

Main Methods:

  • Review of recent research activities.
  • Analysis of two primary methods for condition-specific QALY generation: mapping and direct valuation.
  • Discussion of the utility of condition-specific data alongside or in absence of generic measures.

Main Results:

  • Two main approaches exist: mapping to generic measures and direct valuation of specific health states.
  • Condition-specific data can enhance the precision of QALY estimates.
  • The review highlights increased research activity in this area.

Conclusions:

  • Condition-specific data offer valuable insights for QALY assessments.
  • These methods can improve the accuracy of cost-effectiveness evaluations.
  • Further research is timely to maximize the use of condition-specific data in health technology assessments.