RISK Prediction for Risk-stratified INfection Control and Infection PrEvention
Contact
Project partners
HiGHmed
- Universitätsmedizin Göttingen
- Robert Koch-Institut, Berlin
- Charité – Universitätsmedizin Berlin
- Universitätsmedizin Ostwestfalen-Lippe
- Universitätsklinikum Heidelberg
- Universität zu Köln
- Universitätsklinikum Münster
- Carl von Ossietzky Universität Oldenburg
- Universitätsklinikum Würzburg
SMITH
- Universitätsklinikum Jena
MIRACUM
- Universitätsklinikum Dresden
- Universitätsklinikum Frankfurt
DIFUTURE
- Technische Universität München
Funding
The RISK PRINCIPE project is funded by the Federal Ministry of Education and Research within the national Medical Informatics Initiative with approx. 8.5 million euros of which approx. 1 million euros have been made available to the MHH (promotional reference: 01ZZ2323C).
Summary
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:
- 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).
- To visualize 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 visualization. In addition, knowledge already gained from the two use cases in the field of infectiology (HiGHmed - Infection Control and SMITH HELP - Guideline-based Use of Antibiotics 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.
Duration
07/2023 - 06/2027