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Complementing the net benefit approach: A new framework for Bayesian cost-effectiveness analysis

Published online by Cambridge University Press:  22 October 2009

Miguel Angel Negrín Hernández ,
Francisco José Vázquez-Polo ,
Francisco Javier Girón González-Torre  and
Elías Moreno Bas
Miguel Angel Negrín Hernández
Affiliation:
University of Las Palmas de Gran Canaria
Francisco José Vázquez-Polo
Affiliation:
University of Las Palmas de Gran Canaria
Francisco Javier Girón González-Torre
Affiliation:
University of Málaga
Elías Moreno Bas
Affiliation:
University of Granada
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Abstract

Objectives: The aim of cost-effectiveness analysis is to maximize health benefits from a given budget, taking a societal perspective. Consequently, the comparison of alternative treatments or technologies is solely based on their expected effectiveness and cost. However, the expectation, or mean, poses important limitations as it might be a poor summary of the underlying distribution, for instance when the effectiveness is a categorical variable, or when the distributions of either effectiveness or cost present a high degree of asymmetry. Clinical variables often present these characteristics.

Methods: In this study, we present a framework for cost-effectiveness analysis based on the whole posterior distribution of effectiveness and cost.

Results: An application with real data is included to illustrate the analysis. Decision-making measures such as the incremental cost-effectiveness ratio, incremental net-benefit, and cost-effectiveness acceptability curves, can also be defined under the new framework.

Conclusions: This framework overcomes limitations of the mean and offers complementary information for the decision maker.

Keywords

Bayesian analysisCost-effectivenessNet benefitBinary effectivenessPredictive posterior densities
Type
General Essays
Information
International Journal of Technology Assessment in Health Care , Volume 25 , Issue 4 , October 2009 , pp. 537 - 545
Copyright
Copyright © Cambridge University Press 2009

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References

REFERENCES

1. Al, MJ, van Hout, BA. A Bayesian approach to economic analyses of clinical trials: The case of Stenting versus Balloon Angioplasty. Health Econ. 2000;9:599–609.3.0.CO;2-#>CrossRefGoogle ScholarPubMed
2. Briggs, AH. A Bayesian approach to stochastic cost-effectiveness analysis. Health Econ. 1999;8:257–261.3.0.CO;2-E>CrossRefGoogle ScholarPubMed
3. Brock, DW. Ethical issues in the use of cost-effectiveness analysis for the priorization of health resources. In: Khushf, G, ed. Handbook of bioethics: Taking stock of the field from a philosophical perspective. Emeryville, CA: Springer-Verlag Telos; 2004.Google Scholar
4. Carpenter, C, Fischl, M, Hammer, S, et al. Antiretroviral therapy for HIV infection in 1998: Updated recommendations of the International AIDS Society-USA Panel. JAMA. 1998;280:78–86.CrossRefGoogle ScholarPubMed
5. Elbasha, E. Risk aversion and uncertainty in cost-effectiveness analysis: The expected utility, moment-generating function approach. Health Econ. 2005;14:457–470.CrossRefGoogle ScholarPubMed
6. Fenwick, E, Claxton, K, Sculpher, M. Representing uncertainty: The role of cost-effectiveness acceptability curves. Health Econ. 2001;10:779–787.CrossRefGoogle ScholarPubMed
7. Gold, MR, Siegel, JE, Russell, LB, Weinstein, MC. Cost-effectiveness in health and medicine. Oxford: Oxford University Press; 1996.CrossRefGoogle ScholarPubMed
8. Heitjan, DF, Moskowitz, AJ, William, W. Bayesian estimation of cost-effectiveness ratios from clinical trials. Health Econ. 1999;8:191–201.3.0.CO;2-R>CrossRefGoogle ScholarPubMed
9. Hoch, JS, Rockx, MA, Krahn, A. Using the net benefit regression framework to construct cost-effectiveness acceptability curves: An example using data from a trial of external loop recorders versus Holter monitoring for ambulatory monitoring of “community acquired” syncope. BMC Health Serv Res. 2006;6:68.CrossRefGoogle ScholarPubMed
10. Löthgren, M, Zethraeus, N. Definition, interpretation and calculation of cost-effectiveness acceptability curves. Health Econ. 2000;9:623–630.3.0.CO;2-V>CrossRefGoogle ScholarPubMed
11. Michiels, S, Piedbois, P, Burdett, S, et al. Meta-analysis when only the median survival times are known: A comparison with individual patient data results. Int J Technol Assess Health Care. 2005;21:119–125.CrossRefGoogle ScholarPubMed
12. O'Brien, BJ, Sculpher, MJ. Building uncertainty into cost-effectiveness rankings: Portfolio risk-return tradeoffs and implications for decision rules. Med Care. 2001;38:460–468.CrossRefGoogle Scholar
13. O'Hagan, A. Research in elicitation. In: Upadhyay, SK, Singh, U, Dey, DK, eds. Bayesian statistics and its applications. New Delhi: Anamaya; 2006:375–382.Google Scholar
14. O'Hagan, A, Forster, J. Kendall's Advanced theory of statistics. vol. 2B. Bayesian inference. 2nd ed. London: Edward Arnold; 2004.Google Scholar
15. O'Hagan, A, Stevens, JW. Bayesian methods for design and analysis of cost-effectiveness trials in the evaluation of health care technologies. Stat Methods Med Res. 2002;11:469–490.CrossRefGoogle ScholarPubMed
16. O'Hagan, A, Stevens, JW. The probability of cost-effectiveness. BMC Med Res Methodol. 2002;2:5.CrossRefGoogle ScholarPubMed
17. O'Hagan, A, Stevens, JW, Montmartin, J. Bayesian cost-effectiveness analysis from clinical trial data. Stat Med. 2001;20:733–753.CrossRefGoogle ScholarPubMed
18. Pinto, JL, López, C, Badìa, X, Coma, A, et al. Análisis coste-efectividad del tratamiento antirretroviral de gran actividad en pacientes infectados por el VIH asintomáticos. Med Clin. 2000;114:62–67.Google Scholar
19. Polsky, D, Glick, H, Willke, R, Schulman, K. Confidence intervals for cost-effectiveness ratios: A comparison of four methods. Health Econ. 1997;6:243–252.3.0.CO;2-Z>CrossRefGoogle ScholarPubMed
20. Spiegelhalter, DJ, Thomas, A, Best, NG, Lunn, D. Winbugs version 1.4 user manual. T. Rep., MRC Biostatistics Unit, 2002. http://www.mrc-bsu.cam.ac.uk/bugs (accessed September 2, 2009).Google Scholar
21. Stinnett, AA, Mullahy, J. Net health benefits: A new framework for the analysis of uncertainty in cost-effectiveness analysis. Med Decis Making. 1993;18:S68–S80.CrossRefGoogle Scholar
22. Vanness, DJ, Mullahy, J. Perspectives on mean-based evaluation of health care. In: Jones AM, ed. Elgar companion to health economics. Cheltenham: Edward Elgar Publishing; 2006:526–536.Google Scholar
23. Wailoo, A, Roberts, J, Brazier, J, McCabe, C. Efficiency, equity and NICE clinical guidelines. BMJ. 2004;328:536–537.CrossRefGoogle ScholarPubMed
24. Willan, AR. On the probability of cost-effectiveness using data from randomized clinical trials. BMC Med Res Methodol. 2001;1:8.CrossRefGoogle ScholarPubMed
25. Zivin, JG. Cost-effectiveness analysis with risk aversion. Health Econ. 2001;10:499–508.CrossRefGoogle ScholarPubMed
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