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A Note on Confidence Intervals in Cost-Effectiveness Analysis

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Author Info

  • Tambour, Magnus

    ()
    (Dept. of Economics, Stockholm School of Economics)

  • Zethraeus, Niklas

    ()
    (Dept. of Economics, Stockholm School of Economics)

  • Johannesson, Magnus

    ()
    (Dept. of Economics, Stockholm School of Economics)

Abstract

How to obtain confidence intervals for cost-effectiveness ratios is complicated by the statistical problems to obtain a confidence interval for a ratio of random variables. Different approaches have been suggested in the literature, but no consensus has been reached. In this note we propose an alternative simple solution to this problem. By multiplying the effectiveness units by the price per effectiveness unit, both costs and benefits can be expressed in monetary terms and standard statistical techniques can be used to estimate a confidence interval for net benefits. This avoids the ratio estimation problem and explicitly recognizes that the price per effectiveness unit has to be known to provide cost-effectibeness analysis with a useful decision rule.

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Bibliographic Info

Paper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 181.

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Length: 8 pages
Date of creation: 13 Aug 1997
Date of revision:
Publication status: Published in International Journal of Technology Assessment in Health Care, 1998, pages 467-471.
Handle: RePEc:hhs:hastef:0181

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Postal: The Economic Research Institute, Stockholm School of Economics, P.O. Box 6501, 113 83 Stockholm, Sweden
Phone: +46-(0)8-736 90 00
Fax: +46-(0)8-31 01 57
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Web page: http://www.hhs.se/
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Related research

Keywords: Confidence intervals; Cost-effectiveness ratios; Cost-effectiveness analysis; Economic evaluation;

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Citations

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Cited by:
  1. 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.
  2. Gregory S. Zaric, 2008. "Optimal drug pricing, limited use conditions and stratified net benefits for Markov models of disease progression," Health Economics, John Wiley & Sons, Ltd., vol. 17(11), pages 1277-1294.
  3. Jeffrey S. Hoch & Andrew H. Briggs & Andrew R. Willan, 2002. "Something old, something new, something borrowed, something blue: a framework for the marriage of health econometrics and cost-effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 11(5), pages 415-430.
  4. Joshua Graff Zivin, 2001. "Cost-effectiveness analysis with risk aversion," Health Economics, John Wiley & Sons, Ltd., vol. 10(6), pages 499-508.
  5. Eugene M. Laska & Morris Meisner & Carole Siegel & Joseph Wanderling, 2002. "Statistical determination of cost-effectiveness frontier based on net health benefits," Health Economics, John Wiley & Sons, Ltd., vol. 11(3), pages 249-264.
  6. Joanne Lord & Maxwell A. Asante, 1999. "Estimating uncertainty ranges for costs by the bootstrap procedure combined with probabilistic sensitivity analysis," Health Economics, John Wiley & Sons, Ltd., vol. 8(4), pages 323-333.
  7. Joseph C. Gardiner & Marianne Huebner & James Jetton & Cathy J. Bradley, 2000. "Power and sample assessments for tests of hypotheses on cost-effectiveness ratios," Health Economics, John Wiley & Sons, Ltd., vol. 9(3), pages 227-234.
  8. 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.
  9. Pedram Sendi, 2008. "Bridging the gap between health and non-health investments: moving from cost-effectiveness analysis to a return on investment approach across sectors of economy," International Journal of Health Care Finance and Economics, Springer, vol. 8(2), pages 113-121, June.
  10. Simon Eckermann & Andrew R. Willan, 2009. "Globally optimal trial design for local decision making," Health Economics, John Wiley & Sons, Ltd., vol. 18(2), pages 203-216.
  11. Eugene M. Laska & Morris Meisner & Carole Siegel & Aaron A. Stinnett, 1999. "Ratio-based and net benefit-based approaches to health care resource allocation: proofs of optimality and equivalence," Health Economics, John Wiley & Sons, Ltd., vol. 8(2), pages 171-174.
  12. Andrew R. Willan & Andrew H. Briggs & Jeffrey S. Hoch, 2004. "Regression methods for covariate adjustment and subgroup analysis for non-censored cost-effectiveness data," Health Economics, John Wiley & Sons, Ltd., vol. 13(5), pages 461-475.
  13. Mickael Löthgren & Niklas Zethraeus, 2000. "Definition, interpretation and calculation of cost-effectiveness acceptability curves," Health Economics, John Wiley & Sons, Ltd., vol. 9(7), pages 623-630.
  14. 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.
  15. Martin Henriksson & Fredrik Lundgren & Per Carlsson, 2006. "Informing the efficient use of health care and health care research resources - the case of screening for abdominal aortic aneurysm in Sweden," Health Economics, John Wiley & Sons, Ltd., vol. 15(12), pages 1311-1322.
  16. Andrew H. Briggs, 1999. "A Bayesian approach to stochastic cost-effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 8(3), pages 257-261.
  17. Manca, A & Austin, P. C, 2008. "Using propensity score methods to analyse individual patient-level cost-effectiveness data from observational studies," Health, Econometrics and Data Group (HEDG) Working Papers 08/20, HEDG, c/o Department of Economics, University of York.

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