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Pricing of pharmaceuticals: Assessing the pricing potential by a pricing matrix model

机译:药品定价:通过定价矩阵模型评估定价潜力

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Pricing and reimbursement of new pharmaceuticals have been based until recently on the traditional clinical trial outcomes (efficacy, safety, and quality parameters) used for registration. Now we can distinguish various additional data requirements which relate to the use of the drug in real daily practice. The most important new data requirements are effectiveness, cost-effectiveness, and budgetary impact. A main question is how much the impact is of the various types of data in the pricing and reimbursement process. The objective of this contribution is to present a method for quantifying this type of uncertainty in order to develop a more solid pricing and reimbursement strategy for a new innovative drug. The concepts are illustrated for a new hypothetical antidepressant drug in The Netherlands. This method is based on the analytic hierarchy process (AHP) concept which measures decision makers preferences for the critical success factors. This study shows that the AHP concept may be applied to the pricing and reimbursement environment. The method may be used to assess the pricing potential of a new drug, considering the various data requirements in the reimbursement process.
机译:直到最近,新药品的定价和报销仍基于用于注册的传统临床试验结果(功效,安全性和质量参数)。现在,我们可以区分与实际日常使用中药物使用相关的各种其他数据要求。最重要的新数据要求是有效性,成本效益和预算影响。一个主要问题是在定价和报销过程中,各种类型的数据的影响是多少。这项贡献的目的是提出一种量化这种不确定性的方法,以便为新的创新药物开发更加可靠的定价和报销策略。在荷兰为一种新的假设性抗抑郁药举例说明了这些概念。此方法基于层次分析法(AHP)的概念,该概念衡量决策者对关键成功因素的偏好。这项研究表明,层次分析法的概念可应用于定价和报销环境。考虑到报销过程中的各种数据要求,该方法可用于评估新药的定价潜力。

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