, Volume 31, Issue 8, pp 635–641 | Cite as

Constructing Indirect Utility Models: Some Observations on the Principles and Practice of Mapping to Obtain Health State Utilities

  • Christopher McCabe
  • Richard Edlin
  • David Meads
  • Chantelle Brown
  • Samer Kharroubi
Leading Article


The construction of mapping models is an increasingly popular mechanism for obtaining health state utility data to inform economic evaluations in health care. There is great variation in the sophistication of the methods utilized but to date very little discussion of the appropriate theoretical framework to guide the design and evaluation of these models. In this paper, we argue that recognizing mapping models as a form of indirect health state valuation allows the use of the framework described by Dolan for the measurement of social preferences over health. Using this framework, we identify substantial concerns with the method for valuing health states that is implicit in indirect utility models (IUMs), the conflation of two sets of respondents’ values in such models, and the lack of a structured and statistically reasonable approach to choosing which states to value and how many observations per state to require in the estimation dataset. We also identify additional statistical challenges associated with clustering and censoring in the datasets for IUMs, additional to those attributable to the descriptive systems, and a potentially significant problem with the systematic understatement of uncertainty in predictions from IUMs. Whilst recognizing that IUMs appear to meet the needs of reimbursement organizations that use quality-adjusted life years in their appraisal processes, we argue that current proposed quality standards are inadequate and that IUMs are neither robust nor appropriate mechanisms for estimating utilities for use in cost-effectiveness analyses.


Resource Allocation Decision Health State Utility Health State Valuation Specific Health State Health State Description 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was funded by the UK Medical Research Council NICE Methods Programme: G0901490 Methods for the Indirect Estimation of Health State Utilities. Christopher McCabe was also funded by the Capital Health Research Chair Endowment at the University of Alberta (Edmonton, AB, Canada). Christopher McCabe is the author of a rarely used direct utility model, the UK HUI2 algorithm, which is freely available for public and private researchers. Richard Edlin, David Meads, Chantelle Browne and Samer Kharroubi have no conflicts of interest that are directly relevant to the content of this article.


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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Christopher McCabe
    • 1
  • Richard Edlin
    • 2
  • David Meads
    • 3
  • Chantelle Brown
    • 4
  • Samer Kharroubi
    • 5
  1. 1.Capital Health Endowed Research Chair, Faculty of Medicine and DentistryUniversity of AlbertaEdmontonCanada
  2. 2.School of Population HealthUniversity of AucklandAucklandNew Zealand
  3. 3.Academic Unit of Health EconomicsUniversity of LeedsLeedsUnited Kingdom
  4. 4.United BioSource CorporationLondonUnited Kingdom
  5. 5.Department of MathematicsUniversity of YorkYorkUnited Kingdom

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