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Bayesian approaches to the value of information: implications for the regulation of new pharmaceuticals

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  • Karl Claxton

Abstract

The current regulation of new pharmaceuticals is inefficient because it demands arbitrary amounts of information, the type of information demanded is not relevant to decision‐makers and the same standards of evidence are applied across different technologies. Bayesian decision theory and an analysis of the value of both perfect and sample information is used to consider the efficient regulation of new pharmaceuticals. This type of analysis can be used to decide whether the evidence in an economic study provides ‘sufficient substantiation’ for an economic claim, and assesses whether evidence can be regarded as ‘competent and reliable’. Copyright © 1999 John Wiley & Sons, Ltd.

Suggested Citation

  • Karl Claxton, 1999. "Bayesian approaches to the value of information: implications for the regulation of new pharmaceuticals," Health Economics, John Wiley & Sons, Ltd., vol. 8(3), pages 269-274, May.
  • Handle: RePEc:wly:hlthec:v:8:y:1999:i:3:p:269-274
    DOI: 10.1002/(SICI)1099-1050(199905)8:3<269::AID-HEC425>3.0.CO;2-D
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    File URL: https://doi.org/10.1002/(SICI)1099-1050(199905)8:33.0.CO;2-D
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    References listed on IDEAS

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    1. Claxton, Karl, 1999. "The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologies," Journal of Health Economics, Elsevier, vol. 18(3), pages 341-364, June.
    2. Karl Claxton & John Posnett, "undated". "An Economic Approach to Clinical Trial Design and Research Priority Setting," Discussion Papers 96/19, Department of Economics, University of York.
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    Cited by:

    1. Bognar, Katalin & Romley, John A. & Bae, Jay P. & Murray, James & Chou, Jacquelyn W. & Lakdawalla, Darius N., 2017. "The role of imperfect surrogate endpoint information in drug approval and reimbursement decisions," Journal of Health Economics, Elsevier, vol. 51(C), pages 1-12.
    2. C Simone Sutherland & Joshua Yukich & Ron Goeree & Fabrizio Tediosi, 2015. "A Literature Review of Economic Evaluations for a Neglected Tropical Disease: Human African Trypanosomiasis (“Sleeping Sickness”)," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 9(2), pages 1-22, February.
    3. Haitham Tuffaha & Shelley Roberts & Wendy Chaboyer & Louisa Gordon & Paul Scuffham, 2015. "Cost-Effectiveness and Value of Information Analysis of Nutritional Support for Preventing Pressure Ulcers in High-risk Patients: Implement Now, Research Later," Applied Health Economics and Health Policy, Springer, vol. 13(2), pages 167-179, April.
    4. 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., vol. 11(1), pages 23-31, January.
    5. Alan Brennan & Samer A. Kharroubi, 2007. "Expected value of sample information for Weibull survival data," Health Economics, John Wiley & Sons, Ltd., vol. 16(11), pages 1205-1225, November.
    6. Joyce Craig & Louise Carr & John Hutton & Julie Glanville & Cynthia Iglesias & Andrew Sims, 2015. "A Review of the Economic Tools for Assessing New Medical Devices," Applied Health Economics and Health Policy, Springer, vol. 13(1), pages 15-27, February.
    7. Heikkinen, T. & Pietola, K., 2009. "Investment and the dynamic cost of income uncertainty: The case of diminishing expectations in agriculture," European Journal of Operational Research, Elsevier, vol. 192(2), pages 634-646, January.
    8. F. J. Vázquez‐Polo & M. A. Negrín 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, June.
    9. Ilias Goranitis & Pelham Barton & Lee J Middleton & Jonathan J Deeks & Jane P Daniels & Pallavi Latthe & Arri Coomarasamy & Suneetha Rachaneni & Shanteela McCooty & Tina S Verghese & Tracy E Roberts, 2016. "Testing and Treating Women after Unsuccessful Conservative Treatments for Overactive Bladder or Mixed Urinary Incontinence: A Model-Based Economic Evaluation Based on the BUS Study," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-18, August.
    10. Alan Brennan & Samer A. Kharroubi, 2007. "Expected value of sample information for Weibull survival data," Health Economics, John Wiley & Sons, Ltd., vol. 16(11), pages 1205-1225.
    11. Sander Greenland, 2005. "Multiple‐bias modelling for analysis of observational data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(2), pages 267-306, March.
    12. Scott B. Cantor, 2004. "Clinical Applications in the Decision Analysis Literature," Decision Analysis, INFORMS, vol. 1(1), pages 23-25, March.
    13. Álvaro Hidalgo-Vega & Juan Ramos-Goñi & Renata Villoro, 2014. "Cost-utility of ranolazine for the symptomatic treatment of patients with chronic angina pectoris in Spain," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(9), pages 917-925, December.
    14. Joshua Graff Zivin, 2001. "Cost‐effectiveness analysis with risk aversion," Health Economics, John Wiley & Sons, Ltd., vol. 10(6), pages 499-508, September.
    15. 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.
    16. Francisco-José Polo & Miguel Negrín & Xavier Badía & Montse Roset, 2005. "Bayesian regression models for cost-effectiveness analysis," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 6(1), pages 45-52, March.
    17. Björn Stollenwerk & Stefan K. Lhachimi & Andrew Briggs & Elisabeth Fenwick & Jaime J. Caro & Uwe Siebert & Marion Danner & Andreas Gerber‐Grote, 2015. "Communicating the Parameter Uncertainty in the IQWiG Efficiency Frontier to Decision‐Makers," Health Economics, John Wiley & Sons, Ltd., vol. 24(4), pages 481-490, April.
    18. K. Claxton & P. J. Neumannn & S. S. Araki & M. C. Weinstein, "undated". "Bayesian Value-of-Information Analysis: An Application to a Policy Model of Alzheimer's Disease," Discussion Papers 00/39, Department of Economics, University of York.
    19. Castillo-Riquelme, Marianela & Chalabi, Zaid & Lord, Joanne & Guhl, Felipe & Campbell-Lendrum, Diarmid & Davies, Clive & Fox-Rushby, Julia, 2008. "Modelling geographic variation in the cost-effectiveness of control policies for infectious vector diseases: The example of Chagas disease," Journal of Health Economics, Elsevier, vol. 27(2), pages 405-426, March.

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