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

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Abstract

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.

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Acknowledgments

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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Authors and Affiliations

  1. Capital Health Endowed Research Chair, Faculty of Medicine and Dentistry, University of Alberta, Suite 736 University Terrace, 8303 112 Street, Edmonton, AB, T6G 2T4, Canada

    Christopher McCabe

  2. School of Population Health, University of Auckland, Auckland, New Zealand

    Richard Edlin

  3. Academic Unit of Health Economics, University of Leeds, Leeds, United Kingdom

    David Meads

  4. United BioSource Corporation, London, United Kingdom

    Chantelle Brown

  5. Department of Mathematics, University of York, York, United Kingdom

    Samer Kharroubi

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  1. Christopher McCabe
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  2. Richard Edlin
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  3. David Meads
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  4. Chantelle Brown
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  5. Samer Kharroubi
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Corresponding author

Correspondence to Christopher McCabe.

Appendix 1: Recommendations for Construction and Use of IUMs

Appendix 1: Recommendations for Construction and Use of IUMs

  1. 1.

    IUM estimates between non–preference-based HRQL instruments and preference-based HRQL values should be driven by theoretically plausible relationships.

  2. 2.

    Relationships between non–preference-based HRQL instruments and preference-based HRQL values should be specified prior to empirical analysis.

  3. 3.

    Cost-effectiveness analysis that use IUM utility estimates should not be considered ‘reference case’ analyses.

  4. 4.

    Sensitivity analyses should be used to test for the influence of the following factors on the estimated relationships:

    1. (a)

      The choice of health states used to inform the estimated relationship.

    2. (b)

      The choice of observations used in the estimation sample.

    3. (c)

      The choice of IUM.

  5. 5.

    When the estimated relationships are not sensitive to these factors, the utility estimates should be used to estimate the value of information associated with delaying reimbursement and collecting ‘reference case’ compliant utility data.

  6. 6.

    Should the estimated relationships be found to be sensitive to these factors, the IUM utilities should not be used.

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McCabe, C., Edlin, R., Meads, D. et al. Constructing Indirect Utility Models: Some Observations on the Principles and Practice of Mapping to Obtain Health State Utilities. PharmacoEconomics 31, 635–641 (2013). https://doi.org/10.1007/s40273-013-0071-4

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