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Incorporating model uncertainty in cost-effectiveness analysis: A Bayesian model averaging approach

  • Negri­n, Miguel A.
  • Vázquez-Polo, Francisco-José
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    Recently, several authors have proposed the use of linear regression models in cost-effectiveness analysis. In this paper, by modelling costs and outcomes using patient and Health Centre covariates, we seek to identify the part of the cost or outcome difference that is not attributable to the treatment itself, but to the patients' condition or to characteristics of the Centres. Selection of the covariates to be included as predictors of effectiveness and cost is usually assumed by the researcher. This behaviour ignores the uncertainty associated with model selection and leads to underestimation of the uncertainty about quantities of interest. We propose the use of Bayesian model averaging as a mechanism to account for such uncertainty about the model. Data from a clinical trial are used to analyze the effect of incorporating model uncertainty, by comparing two highly active antiretroviral treatments applied to asymptomatic HIV patients. The joint posterior density of incremental effectiveness and cost and cost-effectiveness acceptability curves are proposed as decision-making measures.

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    Article provided by Elsevier in its journal Journal of Health Economics.

    Volume (Year): 27 (2008)
    Issue (Month): 5 (September)
    Pages: 1250-1259

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    Handle: RePEc:eee:jhecon:v:27:y:2008:i:5:p:1250-1259
    Contact details of provider: Web page: http://www.elsevier.com/locate/inca/505560

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    1. 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., vol. 14(6), pages 545-557.
    2. Christian Kronborg Andersen & Kjeld Andersen & Per Kragh-S�rensen, 2000. "Cost function estimation: the choice of a model to apply to dementia," Health Economics, John Wiley & Sons, Ltd., vol. 9(5), pages 397-409.
    3. Carmen Fernandez & Eduardo Ley & Mark F. J. Steel, 2001. "Model uncertainty in cross-country growth regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(5), pages 563-576.
    4. Carmen Fernández & Eduardo Ley & Mark F. J. Steel, . "Benchmark priors for Bayesian Model averaging," Working Papers 98-06, FEDEA.
    5. Min, Chung-ki & Zellner, Arnold, 1993. "Bayesian and non-Bayesian methods for combining models and forecasts with applications to forecasting international growth rates," Journal of Econometrics, Elsevier, vol. 56(1-2), pages 89-118, March.
    6. Gerald Richardson & Andrea Manca, 2004. "Calculation of quality adjusted life years in the published literature: a review of methodology and transparency," Health Economics, John Wiley & Sons, Ltd., vol. 13(12), pages 1203-1210.
    7. Andrew R. Willan & Bernie J. O'Brien, 2001. "Cost prediction models for the comparison of two groups," Health Economics, John Wiley & Sons, Ltd., vol. 10(4), pages 363-366.
    8. 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.
    9. 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.
    10. 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.
    11. Ciaran O'Neill & Lindsay Groom & Anthony J. Avery & Daphne Boot & Karine Thornhill, 2000. "Age and proximity to death as predictors of GP care costs: results from a study of nursing home patients," Health Economics, John Wiley & Sons, Ltd., vol. 9(8), pages 733-738.
    12. Andrew Healey & Massimo Mirandola & Francesco Amaddeo & Paola Bonizzato & Michele Tansella, 2000. "Using health production functions to evaluate treatment effectiveness: an application to a community mental health service," Health Economics, John Wiley & Sons, Ltd., vol. 9(5), pages 373-383.
    13. Andrew H. Briggs, 1999. "A Bayesian approach to stochastic cost-effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 8(3), pages 257-261.
    14. 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.
    15. E. Kathleen Adams & Vincent P. Miller & Carla Ernst & Brenda K. Nishimura & Cathy Melvin & Robert Merritt, 2002. "Neonatal health care costs related to smoking during pregnancy," Health Economics, John Wiley & Sons, Ltd., vol. 11(3), pages 193-206.
    16. Koop, Gary & Tole, Lise, 2004. "Measuring the health effects of air pollution: to what extent can we really say that people are dying from bad air?," Journal of Environmental Economics and Management, Elsevier, vol. 47(1), pages 30-54, January.
    17. Francisco-José Polo & Miguel Negrín & Xavier Badía & Montse Roset, 2005. "Bayesian regression models for cost-effectiveness analysis," The European Journal of Health Economics, Springer, vol. 6(1), pages 45-52, March.
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