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A linear index for predicting joint health-states utilities from single health-states utilities

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Author Info
Anirban Basu (Department of Medicine, Section of General Internal Medicine, Center for Health and the Social Sciences, University of Chicago, Chicago, IL, USA)
William Dale (Department of Medicine, Section of Geriatrics, University of Chicago, Chicago, IL, USA)
Arthur Elstein (Department of Medical Education, University of Illinois-Chicago, Chicago, IL, USA)
David Meltzer (Department of Medicine, Section of General Internal Medicine, Center for Health and the Social Sciences, University of Chicago, Chicago, IL, USA)
Abstract

Direct elicitation of utilities for joint health (JS) states may pose substantial interview burden, while traditional models to predict these utilities from utilities of component single states (SS) are inconsistent with the data. Using individual-level data on utilities for health states associated with prostate cancer, we report the performance of a new model that encompasses three traditional models - additive, multiplicative, and minimum - previously used for predicting utilities for joint health states. Describing utilities in terms of utility losses l(.) relative to prefect health, our final estimated linear index for predicting joint health-state utilities is El(JS)=0.05+0.72·max l(SS1),l(SS2)+0.33·min l(SS1),l(SS2)−0.18·l(SS1)·l(SS2). Based on out-of-sample predictions, this model produces up to 50% reduction in mean-square error compared with traditional models and consistent prediction across different ranges of joint-state utilities, which the traditional models do not. Parameter estimates of the new model proposed here provide direct evidence on the inconsistencies of the traditional models, are grounded in psychological theory by emphasizing the more severe component of a joint health state, and provide a simple linear index to generate consistent predictions of utilities for joint health states. Further validation of this function for joint health states in other clinical scenarios is warranted. Copyright © 2008 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/hec.1373
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Article provided by John Wiley & Sons, Ltd. in its journal Health Economics.

Volume (Year): 18 (2009)
Issue (Month): 4 ()
Pages: 403-419
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:wly:hlthec:v:18:y:2009:i:4:p:403-419

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/5749

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  1. D. Stratmann-Schoene & T. Kuehn & R. Kreienberg & R. Leidl, 2006. "A preference-based index for the SF-12," Health Economics, John Wiley & Sons, Ltd., vol. 15(6), pages 553-564. [Downloadable!]
  2. Tversky, Amos & Kahneman, Daniel, 1992. " Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
  3. Stevens, Katherine & McCabe, Christopher & Brazier, John & Roberts, Jennifer, 2007. "Multi-attribute utility function or statistical inference models: A comparison of health state valuation models using the HUI2 health state classification system," Journal of Health Economics, Elsevier, vol. 26(5), pages 992-1002, September. [Downloadable!] (restricted)
  4. Brazier, John & Roberts, Jennifer & Deverill, Mark, 2002. "The estimation of a preference-based measure of health from the SF-36," Journal of Health Economics, Elsevier, vol. 21(2), pages 271-292, March. [Downloadable!] (restricted)
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