IDEAS home Printed from https://ideas.repec.org/a/wly/hlthec/v18y2009i4p403-419.html
   My bibliography  Save this article

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

Author

Listed:
  • Anirban Basu
  • William Dale
  • Arthur Elstein
  • David Meltzer

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.

Suggested Citation

  • Anirban Basu & William Dale & Arthur Elstein & David Meltzer, 2009. "A linear index for predicting joint health‐states utilities from single health‐states utilities," Health Economics, John Wiley & Sons, Ltd., vol. 18(4), pages 403-419, April.
  • Handle: RePEc:wly:hlthec:v:18:y:2009:i:4:p:403-419
    DOI: 10.1002/hec.1373
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/hec.1373
    Download Restriction: no

    File URL: https://libkey.io/10.1002/hec.1373?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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, June.
    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. 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.
    4. 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.
    5. G Torrance & Y Zhang & D Feeny & W Furlong & R Barr, 1992. "Multi-attribute Utility Functions for a Comprehensive Health Status Classification System: Health Utilities Index Mark 2," Centre for Health Economics and Policy Analysis Working Paper Series 1992-18, Centre for Health Economics and Policy Analysis (CHEPA), McMaster University, Hamilton, Canada.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Roberta Ara & Allan J. Wailoo, 2013. "Estimating Health State Utility Values for Joint Health Conditions," Medical Decision Making, , vol. 33(2), pages 139-153, February.
    2. SeungJin Bae & Eun Bae & Sang Lim, 2014. "Sourcing Quality-of-Life Weights Obtained from Previous Studies: Theory and Reality in Korea," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 7(2), pages 141-150, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. John Brazier & Jennifer Roberts & Donna Rowen, 2012. "Methods for Developing Preference-based Measures of Health," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 37, Edward Elgar Publishing.
    2. McCabe, Christopher & Brazier, John & Gilks, Peter & Tsuchiya, Aki & Roberts, Jennifer & O'Hagan, Anthony & Stevens, Katherine, 2006. "Using rank data to estimate health state utility models," Journal of Health Economics, Elsevier, vol. 25(3), pages 418-431, May.
    3. Stevens, K, 2010. "Valuation of the Child Health Utility Index 9D (CHU9D)," MPRA Paper 29938, University Library of Munich, Germany.
    4. Christopher McCabe & Katherine Stevens & Jennifer Roberts & John Brazier, 2005. "Health state values for the HUI 2 descriptive system: results from a UK survey," Health Economics, John Wiley & Sons, Ltd., vol. 14(3), pages 231-244, March.
    5. Feng Xie & A. Pickard & Paul Krabbe & Dennis Revicki & Rosalie Viney & Nancy Devlin & David Feeny, 2015. "A Checklist for Reporting Valuation Studies of Multi-Attribute Utility-Based Instruments (CREATE)," PharmacoEconomics, Springer, vol. 33(8), pages 867-877, August.
    6. Kevin Haninger & James K. Hammitt, 2011. "Diminishing Willingness to Pay per Quality‐Adjusted Life Year: Valuing Acute Foodborne Illness," Risk Analysis, John Wiley & Sons, vol. 31(9), pages 1363-1380, September.
    7. Gustav Kjellsson & Dennis Petrie & Tom (T.G.M.) van Ourti, 2018. "Measuring income-related inequalities in risky health prospects," Tinbergen Institute Discussion Papers 18-007/V, Tinbergen Institute.
    8. 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.
    9. Lisa R. Ulrich & Juliana J. Petersen & Karola Mergenthal & Andrea Berghold & Gudrun Pregartner & Rolf Holle & Andrea Siebenhofer, 2019. "Cost-effectiveness analysis of case management for optimized antithrombotic treatment in German general practices compared to usual care – results from the PICANT trial," Health Economics Review, Springer, vol. 9(1), pages 1-10, December.
    10. Peasgood, T & Ward, S & Brazier, J, 2010. "A review and meta-analysis of health state utility values in breast cancer," MPRA Paper 29950, University Library of Munich, Germany.
    11. Katherine Stevens, 2012. "Valuation of the Child Health Utility 9D Index," PharmacoEconomics, Springer, vol. 30(8), pages 729-747, August.
    12. Musal, R. Muzaffer & Soyer, Refik & McCabe, Christopher & Kharroubi, Samer A., 2012. "Estimating the population utility function: A parametric Bayesian approach," European Journal of Operational Research, Elsevier, vol. 218(2), pages 538-547.
    13. Lipman, Stefan A. & Brouwer, Werner B.F. & Attema, Arthur E., 2020. "Living up to expectations: Experimental tests of subjective life expectancy as reference point in time trade-off and standard gamble," Journal of Health Economics, Elsevier, vol. 71(C).
    14. Jose-Luis Pinto-Prades & Jose-Maria Abellan-Perpiñan, 2012. "When normative and descriptive diverge: how to bridge the difference," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 38(4), pages 569-584, April.
    15. O'Hagan, A & Brazier, JE & Kharroubi, SA, 2007. "A comparison of United States and United Kingdom EQ-5D health states valuations using a nonparametric Bayesian method," MPRA Paper 29806, University Library of Munich, Germany.
    16. Cathleen Johnson & Aurélien Baillon & Han Bleichrodt & Zhihua Li & Dennie Dolder & Peter P. Wakker, 2021. "Prince: An improved method for measuring incentivized preferences," Journal of Risk and Uncertainty, Springer, vol. 62(1), pages 1-28, February.
    17. Lisa Prosser & James Hammitt & Ron Keren, 2007. "Measuring Health Preferences for Use in Cost-Utility and Cost-Benefit Analyses of Interventions in Children," PharmacoEconomics, Springer, vol. 25(9), pages 713-726, September.
    18. Samer Kharroubi, 2015. "A Comparison of Japan and UK SF-6D Health-State Valuations Using a Non-Parametric Bayesian Method," Applied Health Economics and Health Policy, Springer, vol. 13(4), pages 409-420, August.
    19. Gang Chen & Julie Ratcliffe, 2015. "A Review of the Development and Application of Generic Multi-Attribute Utility Instruments for Paediatric Populations," PharmacoEconomics, Springer, vol. 33(10), pages 1013-1028, October.
    20. George Tomlinson & Karen E. Bremner & Paul Ritvo & Gary Naglie & Murray D. Krahn, 2012. "Development and Validation of a Utility Weighting Function for the Patient-Oriented Prostate Utility Scale (PORPUS)," Medical Decision Making, , vol. 32(1), pages 11-30, January.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:hlthec:v:18:y:2009:i:4:p:403-419. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://www3.interscience.wiley.com/cgi-bin/jhome/5749 .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www3.interscience.wiley.com/cgi-bin/jhome/5749 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.