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US-Based Drug Cost Parameter Estimation for Economic Evaluations

Author

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  • Joseph F. Levy
  • Patrick D. Meek
  • Marjorie A. Rosenberg

Abstract

Introduction. In the United States, more than 10% of national health expenditures are for prescription drugs. Assessing drug costs in US economic evaluation studies is not consistent, as the true acquisition cost of a drug is not known by decision modelers. Current US practice focuses on identifying one reasonable drug cost and imposing some distributional assumption to assess uncertainty. Methods. We propose a set of Rules based on current pharmacy practice that account for the heterogeneity of drug product costs. The set of products derived from our Rules, and their associated costs, form an empirical distribution that can be used for more realistic sensitivity analyses and create transparency in drug cost parameter computation. The Rules specify an algorithmic process to select clinically equivalent drug products that reduce pill burden, use an appropriate package size, and assume uniform weighting of substitutable products. Three diverse examples show derived empirical distributions and are compared with previously reported cost estimates. Results. The shapes of the empirical distributions among the 3 drugs differ dramatically, including multiple modes and different variation. Previously published estimates differed from the means of the empirical distributions. Published ranges for sensitivity analyses did not cover the ranges of the empirical distributions. In one example using lisinopril, the empirical mean cost of substitutable products was $444 (range = $23–$953) as compared with a published estimate of $305 (range = $51–$523). Conclusions. Our Rules create a simple and transparent approach to creating cost estimates of drug products and assessing their variability. The approach is easily modified to include a subset of, or different weighting for, substitutable products. The derived empirical distribution is easily incorporated into 1-way or probabilistic sensitivity analyses.

Suggested Citation

  • Joseph F. Levy & Patrick D. Meek & Marjorie A. Rosenberg, 2015. "US-Based Drug Cost Parameter Estimation for Economic Evaluations," Medical Decision Making, , vol. 35(5), pages 622-632, July.
  • Handle: RePEc:sae:medema:v:35:y:2015:i:5:p:622-632
    DOI: 10.1177/0272989X14563987
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    References listed on IDEAS

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    1. Ronald Wielage & Megha Bansal & J. Andrews & Robert Klein & Michael Happich, 2013. "Cost-Utility Analysis of Duloxetine in Osteoarthritis: A US Private Payer Perspective," Applied Health Economics and Health Policy, Springer, vol. 11(3), pages 219-236, June.
    2. Briggs, Andrew & Sculpher, Mark & Claxton, Karl, 2006. "Decision Modelling for Health Economic Evaluation," OUP Catalogue, Oxford University Press, number 9780198526629.
    3. Andrew H. Briggs & Milton C. Weinstein & Elisabeth A. L. Fenwick & Jonathan Karnon & Mark J. Sculpher & A. David Paltiel, 2012. "Model Parameter Estimation and Uncertainty Analysis," Medical Decision Making, , vol. 32(5), pages 722-732, September.
    4. Karl Claxton & Mark Sculpher & Chris McCabe & Andrew Briggs & Ron Akehurst & Martin Buxton & John Brazier & Tony O'Hagan, 2005. "Probabilistic sensitivity analysis for NICE technology assessment: not an optional extra," Health Economics, John Wiley & Sons, Ltd., vol. 14(4), pages 339-347, April.
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