IDEAS home Printed from https://ideas.repec.org/a/wly/hlthec/v10y2001i4p303-315.html
   My bibliography  Save this article

A framework for cost‐effectiveness analysis from clinical trial data

Author

Listed:
  • Anthony O'Hagan
  • John W. Stevens

Abstract

We present a general Bayesian framework for cost‐effectiveness analysis (CEA) from clinical trial data. This framework allows for very flexible modelling of both cost and efficacy related trial data. A common CEA technique is established for this wide class of models through linking mean efficacy and mean cost to the parameters of any given model. Examples are given in which efficacy may be measured as a continuous, binary, ordinal or time‐to‐event outcome, and in which costs are modelled as distributed normally, log‐normally, as a mixture or non‐parametrically. A case study is presented, illustrating the methodology and illuminating the role of prior information. Copyright © 2001 John Wiley & Sons, Ltd.

Suggested Citation

  • Anthony O'Hagan & John W. Stevens, 2001. "A framework for cost‐effectiveness analysis from clinical trial data," Health Economics, John Wiley & Sons, Ltd., vol. 10(4), pages 303-315, June.
  • Handle: RePEc:wly:hlthec:v:10:y:2001:i:4:p:303-315
    DOI: 10.1002/hec.617
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/hec.617
    Download Restriction: no

    References listed on IDEAS

    as
    1. Tambour, Magnus & Zethraeus, Niklas & Johannesson, Magnus, 1997. "A Note on Confidence Intervals in Cost-Effectiveness Analysis," SSE/EFI Working Paper Series in Economics and Finance 181, Stockholm School of Economics.
    2. Magnus Tambour & Niklas Zethraeus, 1998. "Bootstrap confidence intervals for cost‐effectiveness ratios: some simulation results," Health Economics, John Wiley & Sons, Ltd., vol. 7(2), pages 143-147, March.
    3. Eugene M. Laska & Morris Meisner & Carole Siegel, 1997. "Statistical Inference for Cost–Effectiveness Ratios," Health Economics, John Wiley & Sons, Ltd., vol. 6(3), pages 229-242, May.
    4. Aaron A. Stinnett & John Mullahy, 1998. "Net Health Benefits: A New Framework for the Analysis of Uncertainty in Cost-Effectiveness Analysis," NBER Technical Working Papers 0227, National Bureau of Economic Research, Inc.
    5. Andrew H. Briggs, 1999. "A Bayesian approach to stochastic cost‐effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 8(3), pages 257-261, May.
    6. Daniel F. Heitjan & Alan J. Moskowitz & William Whang, 1999. "Bayesian estimation of cost‐effectiveness ratios from clinical trials," Health Economics, John Wiley & Sons, Ltd., vol. 8(3), pages 191-201, May.
    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. Gianluca Baio & Laura Magazzini & Claudia Oglialoro & Fabio Pammolli & Massimo Riccaboni, 2005. "Medical Devices: Competitiveness and Impact on Public Health Expenditure," Working Papers CERM 05-2005, Competitività, Regole, Mercati (CERM).
    2. Negri­n, Miguel A. & Vázquez-Polo, Francisco-José, 2008. "Incorporating model uncertainty in cost-effectiveness analysis: A Bayesian model averaging approach," Journal of Health Economics, Elsevier, vol. 27(5), pages 1250-1259, September.
    3. Moreno, Elías & Girón, F.J. & Vázquez-Polo, F.J. & NegrI´n, M.A., 2010. "Optimal healthcare decisions: Comparing medical treatments on a cost-effectiveness basis," European Journal of Operational Research, Elsevier, vol. 204(1), pages 180-187, July.
    4. Miguel A. Negrín & Francisco J. Vázquez‐Polo, 2006. "Bayesian cost‐effectiveness analysis with two measures of effectiveness: the cost‐effectiveness acceptability plane," Health Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 363-372, April.
    5. F. J. Vázquez‐Polo & M. A. Negrín Hernández & B. González López‐Valcárcel, 2005. "Using covariates to reduce uncertainty in the economic evaluation of clinical trial data," Health Economics, John Wiley & Sons, Ltd., vol. 14(6), pages 545-557, June.
    6. Francisco-José Polo & Miguel Negrín & Xavier Badía & Montse Roset, 2005. "Bayesian regression models for cost-effectiveness analysis," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 6(1), pages 45-52, March.
    7. Richard M. Nixon & David Wonderling & Richard D. Grieve, 2010. "Non‐parametric methods for cost‐effectiveness analysis: the central limit theorem and the bootstrap compared," Health Economics, John Wiley & Sons, Ltd., vol. 19(3), pages 316-333, March.
    8. David J. Vanness & W. Ray Kim, 2002. "Bayesian estimation, simulation and uncertainty analysis: the cost‐effectiveness of ganciclovir prophylaxis in liver transplantation," Health Economics, John Wiley & Sons, Ltd., vol. 11(6), pages 551-566, September.
    9. Richard M. Nixon & Simon G. Thompson, 2005. "Methods for incorporating covariate adjustment, subgroup analysis and between‐centre differences into cost‐effectiveness evaluations," Health Economics, John Wiley & Sons, Ltd., vol. 14(12), pages 1217-1229, December.
    10. Caterina Conigliani & Andrea Tancredi, 2009. "A Bayesian model averaging approach for cost‐effectiveness analyses," Health Economics, John Wiley & Sons, Ltd., vol. 18(7), pages 807-821, July.

    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:10:y:2001:i:4:p:303-315. 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: (Wiley Content Delivery). 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 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.

    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.