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Comprehensive decision analytical modelling in economic evaluation: a Bayesian approach

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  • Nicola J. Cooper
  • Alex J. Sutton
  • Keith R. Abrams
  • David Turner
  • Allan Wailoo

Abstract

Decision analytical models are widely used in economic evaluation of health care interventions with the objective of generating valuable information to assist health policy decision‐makers to allocate scarce health care resources efficiently. The whole decision modelling process can be summarised in four stages: (i) a systematic review of the relevant data (including meta‐analyses), (ii) estimation of all inputs into the model (including effectiveness, transition probabilities and costs), (iii) sensitivity analysis for data and model specifications, and (iv) evaluation of the model. The aim of this paper is to demonstrate how the individual components of decision modelling, outlined above, may be addressed simultaneously in one coherent Bayesian model (sometimes known as a comprehensive decision analytical model) and evaluated using Markov Chain Monte Carlo simulation implemented in the specialist software WinBUGS. To illustrate the method described, it is applied to two illustrative examples: (1) The prophylactic use of neurominidase inhibitors for the prevention of influenza. (2) The use of taxanes for the second‐line treatment of advanced breast cancer. The advantages of integrating the four stages outlined into one comprehensive decision analytical model, compared to the conventional ‘two‐stage’ approach, are discussed. Copyright © 2003 John Wiley & Sons, Ltd.

Suggested Citation

  • Nicola J. Cooper & Alex J. Sutton & Keith R. Abrams & David Turner & Allan Wailoo, 2004. "Comprehensive decision analytical modelling in economic evaluation: a Bayesian approach," Health Economics, John Wiley & Sons, Ltd., vol. 13(3), pages 203-226, March.
  • Handle: RePEc:wly:hlthec:v:13:y:2004:i:3:p:203-226
    DOI: 10.1002/hec.804
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    File URL: https://doi.org/10.1002/hec.804
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    References listed on IDEAS

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    1. Claxton, K. & Thompson, K. M., 2001. "A dynamic programming approach to the efficient design of clinical trials," Journal of Health Economics, Elsevier, vol. 20(5), pages 797-822, September.
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    Cited by:

    1. Richard Grieve & John Cairns & Simon G. Thompson, 2010. "Improving costing methods in multicentre economic evaluation: the use of multiple imputation for unit costs," Health Economics, John Wiley & Sons, Ltd., vol. 19(8), pages 939-954, August.
    2. Christopher H. Jackson & Linda D. Sharples & Simon G. Thompson, 2010. "Structural and parameter uncertainty in Bayesian cost‐effectiveness models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(2), pages 233-253, March.
    3. Zoie Shui-Yee Wong & David Goldsman & Kwok-Leung Tsui, 2016. "Economic Evaluation of Individual School Closure Strategies: The Hong Kong 2009 H1N1 Pandemic," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-18, January.
    4. Mark J. Sculpher & Karl Claxton & Mike Drummond & Chris McCabe, 2006. "Whither trial‐based economic evaluation for health care decision making?," Health Economics, John Wiley & Sons, Ltd., vol. 15(7), pages 677-687, July.
    5. Zafar Zafari & Kristian Thorlund & J. FitzGerald & Carlo Marra & Mohsen Sadatsafavi, 2014. "Network vs. Pairwise Meta-Analyses: A Case Study of the Impact of an Evidence-Synthesis Paradigm on Value of Information Outcomes," PharmacoEconomics, Springer, vol. 32(10), pages 995-1004, October.
    6. J. Brown & N. J. Welton & C. Bankhead & S. H. Richards & L. Roberts & C. Tydeman & T. J. Peters, 2006. "A Bayesian approach to analysing the cost‐effectiveness of two primary care interventions aimed at improving attendance for breast screening," Health Economics, John Wiley & Sons, Ltd., vol. 15(5), pages 435-445, May.
    7. Andrew Briggs, 2012. "Statistical Methods for Cost-effectiveness Analysis Alongside Clinical Trials," Chapters, in: Andrew M. Jones (ed.),The Elgar Companion to Health Economics, Second Edition, chapter 50, Edward Elgar Publishing.
    8. 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.
    9. Marta O Soares & L Canto e Castro, 2010. "Simulation or cohort models? Continuous time simulation and discretized Markov models to estimate cost-effectiveness," Working Papers 056cherp, Centre for Health Economics, University of York.
    10. Alexei Botchkarev, 2016. "Essential notion of the health economic evaluation: Definition," Economic Analysis Working Papers (2002-2010). Atlantic Review of Economics (2011-2016), Colexio de Economistas de A Coruña, Spain and Fundación Una Galicia Moderna, vol. 2, pages 1-1, December.

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