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Updated: May 26, 2026

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

Mapping for economic evaluation.

Ling-Hsiang Chuang1, Sarah J Whitehead

  • 1Department of Health Sciences, University of York, Heslington, York, UK. ling-hsiang.chuang@york.ac.uk

British Medical Bulletin
|January 3, 2012
PubMed
Summary
This summary is machine-generated.

Mapping is a statistical method to estimate health utilities and quality-adjusted life years (QALYs) when direct measures are unavailable. Further research is needed to address prediction uncertainties for severe health states.

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Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
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Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
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Area of Science:

  • Health economics
  • Statistical modeling
  • Clinical research

Background:

  • Mapping offers a statistical algorithm for estimating health utilities and quality-adjusted life years (QALYs).
  • It is particularly useful in clinical studies lacking direct preference-based measures.

Purpose of the Study:

  • To review the existing literature on health state mapping.
  • To identify areas of agreement and controversy in mapping methodologies.
  • To highlight future research directions for improving mapping accuracy and reliability.

Main Methods:

  • Systematic reviews of the mapping literature were conducted.
  • Analysis focused on methodologies, data requirements, and areas of debate.

Main Results:

  • Mapping necessitates similar populations and high overlap between base and target measures.
  • The National Institute for Health and Clinical Excellence acknowledges mapping for utility data.
  • Controversies include measure descriptiveness, econometric methods, and model specification.

Conclusions:

  • Further research is required to address over-prediction in severe health states.
  • Uncertainty surrounding estimated utility scores needs investigation.
  • Validation of mapping functions remains a critical area for economic evaluation research.