How to prove the ‘added value’ when the concerned innovation is beneficial without producing ‘health’ in a direct way?
A model contains a large amount of inputs and every single input will be surrounded with uncertainty and the end result will be a translation of the composite effect of all inputs and their potential variance.
Do you understand the potential impact of using 2 independent datasets? In this blog, we provide you a taste of some basic insights.
To estimate a launch date, some questions will pop-up. Based on the answers, (in combination with a strong strategy) a realistic estimate of the procedural time will become valid.
All market access colleagues involved in the preparation of economic files will be confronted with the aspect of inflation. There are 2 viewpoints versus ‘today’.
We all know that the pathway between the ‘eureka’ moment and the implementation is long. If needed the regulatory bodies can decide to initiate a ‘fast track procedure’.
After years of building expertise with Managed entry agreements, several challenges arose. In this blog we give you our opinion.
Each health economic analysis starts with clinical data. But if your sample does not provide mature data, how can you use this data as reliably as possible?
To what level is it relevant to include costs in the analysis? For quite a few parameters, it is clear that they can have a decisive influence on your analysis, however, sometimes the effort you have to put into looking up data is not reflected in a meaningful impact on the results.
Before you introduce an innovation, you will collect data on a relatively limited scale, after which you will compare this to a similar dataset. But how can you make a good comparison and which information can you take into account?
