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What Determines the Shape of an EQ-5D Index Distribution?

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  • Parkin, D.
  • Devlin, N.
  • Feng, Y.

Abstract

The EQ-5D is one of the most used health-related quality of life instruments worldwide. Understanding the characteristics of its underlying data is essential. In this paper, OHE's Nancy Devlin and Yan Feng join David Parkin from King's College London in analyzing characteristics of the EQ-5D indexing process that may obscure useful, and important, information about health states. Distributions of EQ-5D index values in patient and general populations typically divide into two distinct groups, the authors note. This might reflect the actual distribution of ill health, but it also might be an artefact of how the EQ-5D index is constructed. This paper examines the determinants of the shape of EQ-5D distributions, particularly the origins of the 'two groups' distribution. The authors compare distributions of EQ-5D index values with distributions based on data that have not been weighted and with condition-specific indexes for the same patients. They find that concentrating on the EQ-5D index may obscure useful information about health states and possibly produce misleading information. They emphasise the importance of exploratory analysis of EQ-5D data - both to improve analyses of EQ-5D data for comparison and inference purposes, and to help develop more accurate mapping across different health measures. For an overview of OHE's extensive activities in patient-reported outcomes measures, please [click here]( https://www.ohe.org/news-categories/eq-5d-and-proms).

Suggested Citation

  • Parkin, D. & Devlin, N. & Feng, Y., 2014. "What Determines the Shape of an EQ-5D Index Distribution?," Research Papers 000530, Office of Health Economics.
  • Handle: RePEc:ohe:respap:000530
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    References listed on IDEAS

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    1. Rowen, D & Brazier, J & Roberts, J, 2008. "Mapping SF-36 onto the EQ-5D index: how reliable is the relationship?," MPRA Paper 29831, University Library of Munich, Germany.
    2. Shaheen, Rubina & Lindholm, Lars, 2006. "Quality of life among pregnant women with chronic energy deficiency in rural Bangladesh," Health Policy, Elsevier, vol. 78(2-3), pages 128-134, October.
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    7. Juan Manuel Ramos-Goni & Oliver Rivero-Arias, 2011. "eq5d: A command to calculate index values for the EQ-5D quality-of-life instrument," Stata Journal, StataCorp LP, vol. 11(1), pages 120-125, March.
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    Cited by:

    1. Brendan Mulhern & Yan Feng & Koonal Shah & Mathieu F. Janssen & Michael Herdman & Ben Hout & Nancy Devlin, 2018. "Comparing the UK EQ-5D-3L and English EQ-5D-5L Value Sets," PharmacoEconomics, Springer, vol. 36(6), pages 699-713, June.
    2. Nancy Devlin & John Brazier & A. Simon Pickard & Elly Stolk, 2018. "3L, 5L, What the L? A NICE Conundrum," PharmacoEconomics, Springer, vol. 36(6), pages 637-640, June.
    3. Cubi-Molla, P. & De Vries, J. & Devlin, N., 2013. "A Study of the Relationship Between Health and Subjective Well-being in Parkinson’s Disease Patients," Working Papers 13/12, Department of Economics, City University London.
    4. Nancy J. Devlin & Koonal K. Shah & Yan Feng & Brendan Mulhern & Ben van Hout, 2018. "Valuing health‐related quality of life: An EQ‐5D‐5L value set for England," Health Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 7-22, January.
    5. Mathieu F. Janssen & Gouke J. Bonsel & Nan Luo, 2018. "Is EQ-5D-5L Better Than EQ-5D-3L? A Head-to-Head Comparison of Descriptive Systems and Value Sets from Seven Countries," PharmacoEconomics, Springer, vol. 36(6), pages 675-697, June.

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    More about this item

    Keywords

    Measuring and valuing outcomes;

    JEL classification:

    • I1 - Health, Education, and Welfare - - Health

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