Early benefit assessment of innovative pharmaceuticals according to AMNOG in Germany: empirical analysis of the decision-making process

• Applicants: Professorin Dr. Katharina Blankart; Professor Dr. Tom Stargardt
• Subject Area: Accounting and Finance ; Economic Policy, Applied Economics
• Term: from 2014 to 2017
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 255711605

Across many industrialized countries, decision processes have established that determine reimbursement of new health technologies. By introducing the Act on the Reform of the Market for Medicinal Products (Arzneimittelmarktneuordnungsgesetz, short: AMNOG) in 2010, the regulatory framework for patented pharmaceuticals has changed substantially for Germany. Manufacturers are to submit a dossier to demonstrate additional health benefit of the new pharmaceutical. In turn, a so-called early benefit assessment (EBA) is then conducted by the Institute for Quality and Efficiency in Health Care (IQWiG) before the Federal Joint Committee (G-BA) makes a decision. As coverage decision-making is highly relevant for health policy, sound empirical analysis is necessary to understand the functioning of in order to assess the consequences of AMNOG. Currently, no empirical evidence exists that analyses what influences the appraisal.It is thus the aim of this project to identify factors that determine the degree of the additional benefit (remarkable, considerable, minor, not quantifiable, no evidence of benefit, less benefit than comparator). We also examine factors that explain the effect on the level of rebate granted by the manufacturer in the subsequent price negotiations. Doing so, we differentiate between (a) the quality of evidence presented to demonstrate additional benefit, (b) its presentation, (c) technological characteristics of the appraised pharmaceuticals, (d) process related criteria for decision-making, and (e) the pharmaceutical s budget impact. For this purpose, regression analysis such as binomial and multinomial logistic regression models will be used. In a pilot study that has preceded this project, we already defined the variables to be collected. The pilot study also confirmed the feasibility of the project.The project uses the documentation of the EBAs as data source from the G-BA s website and the Lauer-Taxe database to calculate the rebate granted. To ensure the validity of the data, all variables are to be extracted by two independent reviewers and compared afterwards. The results provide evidence about the roles of the participating institutions (especially G-BA and IQWiG) and, the decision processes.

• DFG Programme: Research Grants