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Mapping SF-36 onto the EQ-5D index: how reliable is the relationship?

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  • Rowen, D
  • Brazier, J
  • Roberts, J

Abstract

Mapping from health status measures onto generic preference-based measures is becoming a common solution when health state utility values are not directly available for economic evaluation. However the accuracy and reliability of the models employed is largely untested, and there is little evidence of their suitability in patient datasets. This paper examines whether mapping approaches are reliable and accurate in terms of their predictions for a large and varied UK patient dataset. SF-36 dimension scores are mapped onto the EQ-5D index using a number of different model specifications. The predicted EQ-5D scores for subsets of the sample are compared across inpatient and outpatient settings and medical conditions. This paper compares the results to those obtained from existing mapping functions. Our results suggest that models mapping the SF-36 onto the EQ-5D have similar predictions across inpatient and outpatient setting and medical conditions. However, the models overpredict for more severe EQ-5D states; this problem is also present in the existing mapping functions.

Suggested Citation

  • 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.
  • Handle: RePEc:pra:mprapa:29831
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    References listed on IDEAS

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    Cited by:

    1. Tracey A. Young & Clara Mukuria & Donna Rowen & John E. Brazier & Louise Longworth, 2015. "Mapping Functions in Health-Related Quality of Life," Medical Decision Making, , vol. 35(7), pages 912-926, October.
    2. Jeff Round & Annie Hawton, 2017. "Statistical Alchemy: Conceptual Validity and Mapping to Generate Health State Utility Values," PharmacoEconomics - Open, Springer, vol. 1(4), pages 233-239, December.
    3. Oliver Rivero-Arias & Melissa Ouellet & Alastair Gray & Jane Wolstenholme & Peter M. Rothwell & Ramon Luengo-Fernandez, 2010. "Mapping the Modified Rankin Scale (mRS) Measurement into the Generic EuroQol (EQ-5D) Health Outcome," Medical Decision Making, , vol. 30(3), pages 341-354, May.
    4. 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.
    5. David Parkin & Nancy Devlin & Yan Feng, 2016. "What Determines the Shape of an EQ-5D Index Distribution?," Medical Decision Making, , vol. 36(8), pages 941-951, November.
    6. Yeon Wook Kim & Chang-Hoon Lee & Young Sik Park & Yu-Il Kim & Chul Min Ahn & Ju-Ock Kim & Joo Hun Park & Sang Haak Lee & Jae Yeol Kim & Eun Mi Chun & Tae Hoon Jung & Kwang Ha Yoo, 2015. "Effect of Exposure to Second-Hand Smoke on the Quality of Life: A Nationwide Population-Based Study from South Korea," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-10, September.
    7. Matthew Franklin & Katherine Payne & Rachel A. Elliott, 2018. "Quantifying the Relationship between Capability and Health in Older People: Can’t Map, Won’t Map," Medical Decision Making, , vol. 38(1), pages 79-94, January.
    8. Nick Kontodimopoulos & Panagiotis Bozios & John Yfantopoulos & Dimitris Niakas, 2013. "Longitudinal predictive ability of mapping models: examining post-intervention EQ-5D utilities derived from baseline MHAQ data in rheumatoid arthritis patients," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(2), pages 307-314, April.
    9. Beth Woods & Andrea Manca & Helen Weatherly & Pedro Saramago & Eleftherios Sideris & Christina Giannopoulou & Stephen Rice & Mark Corbett & Andrew Vickers & Matthew Bowes & Hugh MacPherson & Mark Scul, 2017. "Cost-effectiveness of adjunct non-pharmacological interventions for osteoarthritis of the knee," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-18, March.
    10. Marisa Santos & Monica A. C. T. Cintra & Andrea L. Monteiro & Braulio Santos & Fernando Gusmão-filho & Mônica Viegas Andrade & Kenya Noronha & Luciane N. Cruz & Suzi Camey & Bernardo Tura & Paul Kin, 2016. "Brazilian Valuation of EQ-5D-3L Health States," Medical Decision Making, , vol. 36(2), pages 253-263, February.
    11. Ning Gu & Chris Bell & Marc Botteman & Xiang Ji & John Carter & Ben Hout, 2012. "Estimating Preference-Based EQ-5D Health State Utilities or Item Responses from Neuropathic Pain Scores," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 5(3), pages 185-197, September.
    12. Roberta Ara & Donna Rowen & Clara Mukuria, 2017. "The Use of Mapping to Estimate Health State Utility Values," PharmacoEconomics, Springer, vol. 35(1), pages 57-66, December.
    13. Michela Meregaglia & Amanda Whittal & Elena Nicod & Michael Drummond, 2020. "‘Mapping’ Health State Utility Values from Non-preference-Based Measures: A Systematic Literature Review in Rare Diseases," PharmacoEconomics, Springer, vol. 38(6), pages 557-574, June.
    14. Clara Mukuria & Donna Rowen & Sue Harnan & Andrew Rawdin & Ruth Wong & Roberta Ara & John Brazier, 2019. "An Updated Systematic Review of Studies Mapping (or Cross-Walking) Measures of Health-Related Quality of Life to Generic Preference-Based Measures to Generate Utility Values," Applied Health Economics and Health Policy, Springer, vol. 17(3), pages 295-313, June.

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    More about this item

    Keywords

    health status; SF-36; SF-12; EQ-5D; utility; mapping;
    All these keywords.

    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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