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Deriving preference-based single indices from non-preference based condition-specific instruments: converting AQLQ into EQ5D indices

Author

Listed:
  • Tsuchiya, A
  • Brazier, J
  • McColl, E
  • Parkin, D

Abstract

Suppose that one has a clinical dataset with only non-preference-based QOL data, and that one nevertheless would like to perform a cost/QALY analysis. This study reports on some efforts to establish a “mapping” relationship between AQLQ (a non-preference-based QOL instrument for asthma) and EQ5D (a preference-based generic instrument). Various methods are described in terms of associated assumptions regarding the measurement properties of the instruments. This is followed by empirical mapping, based on regressing EQ5D on AQLQ. Six main regression models and two supplementary models are identified, and the regressions carried out. Performance of each model is explored in terms of goodness of fit between observed and predicted values, and of robustness of predictions on external data. The results show that it is possible to predict mean EQ5D indices given AQLQ data. The general implications for methods of mapping non-preference-based instruments onto preference-based measures are discussed.

Suggested Citation

  • Tsuchiya, A & Brazier, J & McColl, E & Parkin, D, 2002. "Deriving preference-based single indices from non-preference based condition-specific instruments: converting AQLQ into EQ5D indices," MPRA Paper 29740, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:29740
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    File URL: https://mpra.ub.uni-muenchen.de/29740/1/MPRA_paper_29740.pdf
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    References listed on IDEAS

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    1. McKenzie, Lynda & Cairns, John & Osman, Liesl, 2001. "Symptom-based outcome measures for asthma: the use of discrete choice methods to assess patient preferences," Health Policy, Elsevier, vol. 57(3), pages 193-204, September.
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    1. repec:spr:pharmo:v:1:y:2017:i:4:d:10.1007_s41669-017-0027-2 is not listed on IDEAS
    2. Rowen, D & Brazier, J & Tsuchiya, A & Hernández, M & Ibbotson, R, 2009. "The simultaneous valuation of states from multiple instruments using ranking and VAS data: methods and preliminary results," MPRA Paper 29841, University Library of Munich, Germany.
    3. John Brazier & Yaling Yang & Aki Tsuchiya & Donna Rowen, 2010. "A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 11(2), pages 215-225, April.
    4. repec:spr:patien:v:11:y:2018:i:1:d:10.1007_s40271-017-0259-3 is not listed on IDEAS
    5. Brazier, JE & Yang, Y & Tsuchiya, A, 2008. "A review of studies mapping (or cross walking) from non-preference based measures of health to generic preference-based measures," MPRA Paper 29808, University Library of Munich, Germany.
    6. Kamran Khan & Stavros Petrou & Oliver Rivero-Arias & Stephen Walters & Spencer Boyle, 2014. "Mapping EQ-5D Utility Scores from the PedsQL™ Generic Core Scales," PharmacoEconomics, Springer, vol. 32(7), pages 693-706, July.
    7. Samer A Kharroubi & Richard Edlin & David Meads & Chantelle Browne & Julia Brown & Christopher McCabe, 2013. "Use of Bayesian Markov Chain Monte Carlo Methods to Estimate EQ-5D Utility Scores from Eortic QLQ Data in Myeloma for Use in Cost effectiveness Analysis," Working Papers 1308, Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds.

    More about this item

    Keywords

    EQ5D; AQLQ; mapping;

    JEL classification:

    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • I19 - Health, Education, and Welfare - - Health - - - Other

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