Levy Joseph F, Meek Patrick D, Rosenberg Marjorie A
University of Wisconsin-Madison Department of Population Health Sciences, Madison, WI, USA (JFL)
Albany College of Pharmacy and Health Sciences Department of Pharmacy, Research Institute for Health Outcomes, Albany, NY, USA (PDM)
Med Decis Making. 2015 Jul;35(5):622-32. doi: 10.1177/0272989X14563987. Epub 2014 Dec 22.
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.
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.
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).
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.
在美国,超过10%的国家卫生支出用于处方药。在美国经济评估研究中,评估药物成本并不一致,因为决策模型制定者并不清楚药物的真实采购成本。美国目前的做法侧重于确定一个合理的药物成本,并施加一些分布假设来评估不确定性。
我们基于当前的药学实践提出了一套规则,以考虑药品成本的异质性。根据我们的规则得出的产品集及其相关成本形成了一个经验分布,可用于更现实的敏感性分析,并在药物成本参数计算中实现透明度。这些规则指定了一个算法过程,以选择可减轻药丸负担、使用适当包装尺寸并假设可替代产品加权均匀的临床等效药品。三个不同的例子展示了得出的经验分布,并与先前报告的成本估计进行了比较。
这三种药物的经验分布形状差异很大,包括多个众数和不同的变化。先前发表的估计与经验分布的均值不同。已发表的敏感性分析范围未涵盖经验分布的范围。在一个使用赖诺普利的例子中,可替代产品的经验平均成本为444美元(范围 = 23美元至953美元),而先前发表的估计为305美元(范围 = 51美元至523美元)。
我们的规则创建了一种简单且透明的方法来创建药品成本估计并评估其变异性。该方法易于修改,以纳入可替代产品的一个子集或不同的加权。得出的经验分布很容易纳入单向或概率敏感性分析。