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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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    1. 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.
    2. Peter Bayer & Joel S. Brown & Johan Dubbeldam & Mark Broom, 2022. "A Markovian decision model of adaptive cancer treatment and quality of life," Post-Print hal-03767027, HAL.
    3. Christopher H. Jackson & Mark Jit & Linda D. Sharples & Daniela De Angelis, 2015. "Calibration of Complex Models through Bayesian Evidence Synthesis," Medical Decision Making, , vol. 35(2), pages 148-161, February.
    4. Elisabeth Fenwick & Andrew Briggs, 2007. "Cost-Effectiveness Acceptability Curves in the Dock," Medical Decision Making, , vol. 27(2), pages 93-95, March.
    5. Anna Heath & Ioanna Manolopoulou & Gianluca Baio, 2017. "A Review of Methods for Analysis of the Expected Value of Information," Medical Decision Making, , vol. 37(7), pages 747-758, October.
    6. 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.
    7. Marta O. Soares & Luísa Canto e Castro, 2012. "Continuous Time Simulation and Discretized Models for Cost-Effectiveness Analysis," PharmacoEconomics, Springer, vol. 30(12), pages 1101-1117, December.
    8. 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.
    9. 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.
    10. 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.
    11. Marta Soares & Luísa Canto e Castro, 2012. "Continuous Time Simulation and Discretized Models for Cost-Effectiveness Analysis," PharmacoEconomics, Springer, vol. 30(12), pages 1101-1117, December.
    12. 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.
    13. 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.
    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, March.
    15. Alexander J. Sutton & Nicola J. Cooper & Steve Goodacre & Matthew Stevenson, 2008. "Integration of Meta-analysis and Economic Decision Modeling for Evaluating Diagnostic Tests," Medical Decision Making, , vol. 28(5), pages 650-667, September.
    16. 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.
    17. Thomas A. Trikalinos & Uwe Siebert & Joseph Lau, 2009. "Decision-Analytic Modeling to Evaluate Benefits and Harms of Medical Tests: Uses and Limitations," Medical Decision Making, , vol. 29(5), pages 22-29, September.
    18. 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.
    19. Yasuhiro Hagiwara & Takeru Shiroiwa, 2022. "Estimating Value-Based Price and Quantifying Uncertainty around It in Health Technology Assessment: Frequentist and Bayesian Approaches," Medical Decision Making, , vol. 42(5), pages 672-683, July.

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