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What Can We Expect from Value-Based Funding of Medicines? A Retrospective Study


  • Anthony Harris

    () (Centre for Health Economics)

  • Jing Jing Li

    (Centre for Health Economics)

  • Karen Yong

    (Centre for Health Economics)


Objective Deciding on public funding for pharmaceuticals on the basis of value for money is now widespread. We suggest that evidence-based assessment of value has restricted the availability of medicines in Australia in a way that reflects the relative bargaining power of government and the pharmaceutical industry. We propose a simple informal game-theoretic model of bargaining between the funding agency and industry and test its predictions using a logistic multiple regression model of past funding decisions made by the Pharmaceutical Benefits Advisory Committee in Australia. Method The model estimates the probability of a drug being recommended for subsidy as a function of incremental cost per quality-adjusted life-year (QALY), as well as other drug and market characteristics. Data are major submissions or resubmissions from 1993 to 2009 where there was a claim of superiority and evidence of a difference in quality of life. Independent variables measure the incremental cost per QALY, the cost to the public budget, the strength and quality of the clinical and economic evidence, need as measured by severity of illness and the availability of alternative treatments, whether or not a resubmission, and newspaper reports as a measure of public pressure. We report the odds ratio for each variable and calculate the ratio of the marginal effect of each variable to the marginal effect of the cost per QALY as a measure of the revealed willingness to pay for each of the variables that influence the decision. Results The results are consistent with a bargaining model where a 10,000 Australian dollar ($A) fall in value (increase in cost per QALY) reduces the average probability of public funding from 37 to 33 % (95 % CI 34–32). If the condition is life threatening or the drug has no active comparator, then the odds of a positive recommendation are 3.18 (95 % CI 1.00–10.11) and 2.14 (95 % CI 0.95–4.83) greater, equivalent to a $A33,000 and a $A21,000 increase in value (fall in cost per QALY). If both conditions are met, the odds are increased by 4.41 (95 % CI 1.28–15.24) times, equivalent to an increase in value of $A46,000. Funding is more likely as time elapses and price falls, but we did not find clear evidence that public or corporate pressure influences decisions. Conclusion Evidence from Australia suggests that the determinants of public funding and pricing decisions for medicines reflect the relative bargaining power of government and drug companies. Value for money depends on the quality of evidence, timing, patient need, perceived benefit and opportunity cost; these factors reflect the potential gains from striking a bargain and the risk of loss from not doing so.

Suggested Citation

  • Anthony Harris & Jing Jing Li & Karen Yong, 2016. "What Can We Expect from Value-Based Funding of Medicines? A Retrospective Study," PharmacoEconomics, Springer, vol. 34(4), pages 393-402, April.
  • Handle: RePEc:spr:pharme:v:34:y:2016:i:4:d:10.1007_s40273-015-0354-z
    DOI: 10.1007/s40273-015-0354-z

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    References listed on IDEAS

    1. Drummond, Michael & Jonsson, Bengt & Rutten, Frans, 1997. "The role of economic evaluation in the pricing and reimbursement of medicines," Health Policy, Elsevier, vol. 40(3), pages 199-215, June.
    2. Productivity Commission, 2001. "International pharmaceutical price differences," Others 0107004, University Library of Munich, Germany.
    3. Mikael Svensson & Fredrik Nilsson & Karl Arnberg, 2015. "Reimbursement Decisions for Pharmaceuticals in Sweden: The Impact of Disease Severity and Cost Effectiveness," PharmacoEconomics, Springer, vol. 33(11), pages 1229-1236, November.
    4. 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, May.
    5. Garattini, Livio & Cornago, Dante & De Compadri, Paola, 2007. "Pricing and reimbursement of in-patent drugs in seven European countries: A comparative analysis," Health Policy, Elsevier, vol. 82(3), pages 330-339, August.
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    Cited by:

    1. Peter Ghijben & Yuanyuan Gu & Emily Lancsar & Silva Zavarsek, 2018. "Revealed and Stated Preferences of Decision Makers for Priority Setting in Health Technology Assessment: A Systematic Review," PharmacoEconomics, Springer, vol. 36(3), pages 323-340, March.
    2. Afschin Gandjour, 2016. "Limiting Free Pricing of New Innovative Drugs After Launch: A Necessity for Payers?," Applied Health Economics and Health Policy, Springer, vol. 14(5), pages 507-509, October.

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