Nosocomial infections - i.e. infections acquired in a hospital or a care facility - represent a great burden for the patients affected, the health care staff and, due to their financial importance for the health system, also for society as a whole. The prevention of such infections is important for ensuring patient safety, particularly taking into account the increasing number of cases.

The RISK PRINCIPE use case has the following goals:

1. To develop algorithms and tools for risk prediction based on interoperable data from various partners. The focus of this project is on identifying individual, location-related and treatment-related risks of hospital onset bacteremia (HOB)
2. To visualise the results along with the expertise in the field of infectious diseases in an app for surveillance and risk prediction. It will be possible to map individual infection risks stratified according to relevant parameters in order to be able to act and react in a patient-oriented manner.

RISK PRINCIPE relies on the expertise of various disciplines, including medical informatics, infection prevention and visualisation. In addition, knowledge already gained from the two use cases in the field of infectiology (HiGHmed - infection control and SMITH HELP - targeted antibiotic therapy in infectious medicine) is used and further developed.

The overarching goal is to achieve effective and efficient prevention of infections with the help of automated surveillance and data-based risk prediction.