Abstract
As healthcare reform evolves and takes shape, comparative effectiveness research (CER) appears to be one of the central topics on the national healthcare agenda. Over the past couple of years, comparative effectiveness has been explicitly incorporated in more than ten bills. For example, the passage of the American Recovery and Reinvestment Act of 2009 authorized $US1.1 billion for CER. Comparative effectiveness, when costs are formally considered, offers the hope of efficient resource allocation within US healthcare markets. However, the future operationalization and implementation of comparative effectiveness is uncertain, and there exist potentially negative, and unintended, consequences under certain scenarios.
One example, and the focus of this article, is pharmaceutical innovation. Incentives for pharmaceutical R&D could be affected if drug development costs increase as a result of firms having to bear, directly or indirectly, the costs of running larger, randomized, head-to-head comparative effectiveness trials. While this may or may not be the case with current and future comparative effectiveness legislation and its subsequent implementation, the potential consequences for pharmaceutical innovation warrant recognition.
This is the purpose of the article. To achieve this goal, we develop several models of clinical trial design, drug development costs and R&D investment. By example, we shed light on the causal links between the models and the ways in which industry R&D investment can be affected.
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Notes
See, for example, the TIME Magazine article on the research by Kingsbury,4] which discusses NICE thresholds of $US50 000 and recent Stanford University researchers’ estimates that the value of a life-year is instead $US129 000.
Other factors are also considered (e.g. the size of the treatment population).
A real options approach to R&D investment decision making could also be modelled; however, the simple NPV approach discussed is sufficient to demonstrate our point.
The subsequent effect on life expectancies could also be approximated using the empirical results from Lichtenberg,[14,15] who estimated the contribution of pharmaceutical R&Dexpenditures to life expectancies. Vernon[16] used this estimate to model, over time, the present value cost of various drug price control regimens in terms of lifeyears and dollars.
The use of a gross profits-to-sales ratio to infer price-cost margins entails some challenges. The interested reader is referred to the article by Fisher.[21]
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No sources of funding were used to conduct this study or prepare this article. The authors have no conflicts of interest that are directly relevant to the content of this article.
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Vernon, J.A., Golec, J.H. & Stevens, J.S. Comparative Effectiveness Regulations and Pharmaceutical Innovation. Pharmacoeconomics 28, 877–887 (2010). https://doi.org/10.2165/11537570-000000000-00000
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DOI: https://doi.org/10.2165/11537570-000000000-00000