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Optimal drug pricing, limited use conditions and stratified net benefits for Markov models of disease progression


  • Gregory S. Zaric

    (Richard Ivey School of Business, University of Western Ontario, London, Canada)


Limited use conditions (LUCs) are a method of directing treatment with new drugs to those populations where they will be most cost effective. In this paper we investigate how a drug manufacturer could determine pricing and LUCs to maximize profits. We assume that the payer makes formulary decisions on the basis of net monetary benefits, that the disease can be modeled using a Markov model of disease progression, and that the drug reduces the probability of progression between states of the Markov model. LUCs are expressed as a range of probabilities of disease progression over which patients would have access to the new drug. We assume that the manufacturer determines the price and LUCs in order to maximize profits. We show that an explicit trade-off exists between the drug's price and the use conditions, that there is an upper bound on the drug price, that the proportion of the population targeted by the LUC does not depend on quality of life or costs in each health state or the payer's willingness to pay, and that high drug prices do not always correspond with high profits. Copyright © 2008 John Wiley & Sons, Ltd.

Suggested Citation

  • Gregory S. Zaric, 2008. "Optimal drug pricing, limited use conditions and stratified net benefits for Markov models of disease progression," Health Economics, John Wiley & Sons, Ltd., vol. 17(11), pages 1277-1294.
  • Handle: RePEc:wly:hlthec:v:17:y:2008:i:11:p:1277-1294
    DOI: 10.1002/hec.1332

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    References listed on IDEAS

    1. Tambour, Magnus & Zethraeus, Niklas & Johannesson, Magnus, 1997. "A Note on Confidence Intervals in Cost-Effectiveness Analysis," SSE/EFI Working Paper Series in Economics and Finance 181, Stockholm School of Economics.
    2. George Laking & Joanne Lord & Alastair Fischer, 2006. "The economics of diagnosis," Health Economics, John Wiley & Sons, Ltd., vol. 15(10), pages 1109-1120.
    3. Mark Sculpher & Amiram Gafni, 2001. "Recognizing diversity in public preferences: The use of preference sub-groups in cost-effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 10(4), pages 317-324.
    4. Douglas Coyle & Martin J. Buxton & Bernie J. O'Brien, 2003. "Stratified cost-effectiveness analysis: a framework for establishing efficient limited use criteria," Health Economics, John Wiley & Sons, Ltd., vol. 12(5), pages 421-427.
    5. Karl Claxton, 2007. "Oft, Vbp: Qed?," Health Economics, John Wiley & Sons, Ltd., vol. 16(6), pages 545-558.
    6. Nancy Devlin & David Parkin, 2004. "Does NICE have a cost-effectiveness threshold and what other factors influence its decisions? A binary choice analysis," Health Economics, John Wiley & Sons, Ltd., vol. 13(5), pages 437-452.
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    Cited by:

    1. Puig-Junoy, Jaume & López-Valcárcel, Beatriz González, 2014. "Launch prices for new pharmaceuticals in the heavily regulated and subsidized Spanish market, 1995–2007," Health Policy, Elsevier, vol. 116(2), pages 170-181.

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