Pharmacoepidemiology (PhEpi)
The section Pharmacoepidemiology investigates the utilization as well as the benefits and risks of drugs after market approval in the general population. The main objective is to support decisions in individual patients by using big data, for example to identify risk-modulating factors in medication or to identify patients whose medication can be improved. Statistical methods are used for this purpose, for example predictive modeling including machine learning supported by clinical knowledge. Sources for the evidence obtained in this way are, for example, routine data from statutory health insurance funds or hospital data.
Our Mission
Using state-of-the-art methods that are partly developed in-house, we make an important contribution to identifying underuse, overuse, and misuse of drugs. Based on these results, we derive improvement strategies and develop predictive models for individualized treatment recommendations.
Areas of interest
Apply state-of-the-art methods of causal inference and predictive modeling to make robust inferences ("real-world evidence") and predictions in routine data.