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Confidence Intervals for Cost-Effectiveness Ratios: A Comparison of Four Methods

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  • Daniel Polsky

    (Division of General Internal Medicine and Leonard Davis Institute of Health Economics, University of Pennsylvania, USA)

  • Henry A. Glick

    (Division of General Internal Medicine and Leonard Davis Institute of Health Economics, University of Pennsylvania, USA)

  • Richard Willke

    (Pharmacia and Upjohn, Inc., Kalamazoo, USA)

  • Kevin Schulman

    (Clinical Economics Research Unit, Division of General Internal Medicine, Georgetown University Medical Center, Washington, DC, USA)

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    Abstract

    We evaluated four methods for computing confidence intervals for cost-effectiveness ratios developed from randomized controlled trials: the box method, the Taylor series method, the nonparametric bootstrap method and the Fieller theorem method. We performed a Monte Carlo experiment to compare these methods. We investigated the relative performance of each method and assessed whether or not it was affected by differing distributions of costs (normal and log normal) and effects (10% absolute difference in mortality resulting from mortality rates of 25% versus 15% in the two groups as well as from mortality rates of 55% versus 45%) or by differing levels of correlation between the costs and effects (correlations of −0.50, −0.25, 0.0, 0.25 and 0.50). The principal criterion used to evaluate the performance of the methods was the probability of miscoverage. Symmetrical miscoverage of the intervals was used as a secondary criterion for evaluating the four methods. Overall probabilities of miscoverage for the nonparametric bootstrap method and the Fieller theorem method were more accurate than those for the other the methods. The Taylor series method had confidence intervals that asymmetrically underestimated the upper limit of the interval. Confidence intervals for cost-effectiveness ratios resulting from the nonparametric bootstrap method and the Fieller theorem method were more dependably accurate than those estimated using the Taylor series or box methods. Routine reporting of these intervals will allow individuals using cost-effectiveness ratios to make clinical and policy judgments to better identify when an intervention is a good value for its cost. © 1997 by John Wiley & Sons, Ltd.

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    Bibliographic Info

    Article provided by John Wiley & Sons, Ltd. in its journal Health Economics.

    Volume (Year): 6 (1997)
    Issue (Month): 3 ()
    Pages: 243-252

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    Handle: RePEc:wly:hlthec:v:6:y:1997:i:3:p:243-252

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

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    Cited by:
    1. 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., John Wiley & Sons, Ltd., vol. 11(5), pages 415-430.
    2. Simon Frey & Roland Linder & Georg Juckel & Tom Stargardt, 2014. "Cost-effectiveness of long-acting injectable risperidone versus flupentixol decanoate in the treatment of schizophrenia: a Markov model parameterized using administrative data," The European Journal of Health Economics, Springer, Springer, vol. 15(2), pages 133-142, March.
    3. Simon Eckermann & Andrew R. Willan, 2009. "Globally optimal trial design for local decision making," Health Economics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 18(2), pages 203-216.
    4. J. G. Hirschberg, J. N. Lye & D. J. Slottje, 2008. "Confidence Intervals for Estimates of Elasticities," Department of Economics - Working Papers Series, The University of Melbourne 1053, The University of Melbourne.
    5. Elamin H. Elbasha, 2005. "Risk aversion and uncertainty in cost-effectiveness analysis: the expected-utility, moment-generating function approach," Health Economics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 14(5), pages 457-470.
    6. F. J. Vázquez-Polo & M. A. Negr�n 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., John Wiley & Sons, Ltd., vol. 14(6), pages 545-557.
    7. Murillo Fort, Carles & González López-Valcárcel, Beatriz, 2006. "Potencialidades Y Limitaciones De Las Ligas De Calidad De Los Proveedores Sanitarios/Quality Ranking Of Health Care Providers: Potential And Limitations," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 24, pages 777-788, Diciembre.
    8. P. Sendi & A. Gafni & S. Birch, 2002. "Opportunity costs and uncertainty in the economic evaluation of health care interventions," Health Economics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 11(1), pages 23-31.
    9. David H. Howard & Florence K. Tangka & Laura C. Seeff & Lisa C. Richardson & Donatus U. Ekwueme, 2009. "The impact of detection and treatment on lifetime medical costs for patients with precancerous polyps and colorectal cancer," Health Economics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 18(12), pages 1381-1393.
    10. Daniel F. Heitjan & Huiling Li, 2004. "Bayesian estimation of cost-effectiveness: an importance-sampling approach," Health Economics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 13(2), pages 191-198.
    11. Daniel F. Heitjan, 2000. "Fieller's method and net health benefits," Health Economics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 9(4), pages 327-335.
    12. Tommi Härkänen & Timo Maljanen & Olavi Lindfors & Esa Virtala & Paul Knekt, 2013. "Confounding and missing data in cost-effectiveness analysis: comparing different methods," Health Economics Review, Springer, Springer, vol. 3(1), pages 1-11, December.
    13. Hirschberg, J.G. & Lye, J.N. & Slottje, D.J., 2008. "Inferential methods for elasticity estimates," Journal of Econometrics, Elsevier, Elsevier, vol. 147(2), pages 299-315, December.
    14. 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., John Wiley & Sons, Ltd., vol. 13(5), pages 461-475.
    15. 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., John Wiley & Sons, Ltd., vol. 9(3), pages 227-234.
    16. Martin W. McIntosh & Scott D. Ramsey & Kristin Berry & Nicole Urban, 2001. "Parameter solicitation for planning cost effectiveness studies with dichotomous outcomes," Health Economics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 10(1), pages 53-66.
    17. Andrea Manca & Neil Hawkins & Mark J. Sculpher, 2005. "Estimating mean QALYs in trial-based cost-effectiveness analysis: the importance of controlling for baseline utility," Health Economics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 14(5), pages 487-496.
    18. Emma McIntosh, 2006. "Using Discrete Choice Experiments within a Cost-Benefit Analysis Framework," PharmacoEconomics, Springer, Springer, vol. 24(9), pages 855-868, September.
    19. Andrew R. Willan & Bernie J. O'Brien, 1999. "Sample size and power issues in estimating incremental cost-effectiveness ratios from clinical trials data," Health Economics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 8(3), pages 203-211.
    20. Baral, Ranju & Davis, George C. & Serrano, Elena & McFerren, Mary & You, Wen, 2013. "The Cost Effectiveness of Educating Limited Resource Youths on Food and Nutrition," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C., Agricultural and Applied Economics Association 150221, Agricultural and Applied Economics Association.
    21. Stephen Palmer & Peter Smith, 1999. "Incorporating option values into the economic evaluation of health care technologies," Working Papers, Centre for Health Economics, University of York 166chedp, Centre for Health Economics, University of York.
    22. Daniel F. Heitjan & Alan J. Moskowitz & William Whang, 1999. "Bayesian estimation of cost-effectiveness ratios from clinical trials," Health Economics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 8(3), pages 191-201.
    23. Raymond C. W. Hutubessy & Louis W. Niessen & Rob F. Dijkstra & Ton F. Casparie & Frans F. Rutten, 2005. "Stochastic league tables: an application to diabetes interventions in the Netherlands," Health Economics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 14(5), pages 445-455.

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