Medication safety is a prerequisite for high quality care. Tools and methods to reliably and fastly improve medication safety are limited.
In this project we will develop an automated method based on machine learning to detect Adverse Drug Events based on routinely collected data. Prognostic and causal algorithms as well as free text mining well be developed for detecting ADEs. The first focus is on intensive care patients as they are subject to a high risk of ADEs but successful results will be transferred to other patient categories.