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Automated surveillance and risk prediction with the aim of risk-stratified infection control and prevention (RISK PRINCIPE)

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Michael Marschollek, Mike Marquet, Nicolás Reinoso Schiller, Joëlle Naim, Seven Johannes Sam Aghdassi, Michael Behnke, Sandra Ehrenberg, Tatiana von Landesberger, Martin Misailovski, Fabian Prasser and others

Healthcare-associated infections (HCAIs) represent an enormous burden for patients, healthcare workers, relatives and society worldwide, including Germany. The central tasks of infection prevention are recording and evaluating infections with the aim of identifying prevention potential and risk factors, taking appropriate measures and finally evaluating them. From an infection prevention perspective, it would be of great value if (i) the recording of infection cases was automated and (ii) if it were possible to identify particularly vulnerable patients and patient groups in advance, who would benefit from specific and/or additional interventions.

To achieve this risk-adapted, individualized infection prevention, the RISK PRINCIPE research project develops algorithms and computer-based applications based on standardised, large datasets and incorporates expertise in the field of infection prevention.

The project has two objectives: a) to develop and validate a semi-automated surveillance system for hospital-acquired bloodstream infections, prototypically for HCAI, and b) to use comprehensive patient data from different sources to create an individual or group-specific infection risk profile.

RISK PRINCIPE is based on bringing together the expertise of medical informatics and infection medicine with a focus on hygiene and draws on information and experience from two consortia (HiGHmed and SMITH) of the German Medical Informatics Initiative (MII), which have been working on use cases in infection medicine for more than five years.

 

Cite this paper

Marschollek, M., Marquet, M., Reinoso Schiller, N. et al. Automatisierte Surveillance und Risikovorhersage mit dem Ziel einer risikostratifizierten Infektionskontrolle und -prävention (RISK Prediction for Risk-stratified Infection Control and Prevention). Bundesgesundheitsbl (2024). https://doi.org/10.1007/s00103-024-03882-w

BibTeX:

 

@article{marschollek2024automatisierte,
  title={Automatisierte Surveillance und Risikovorhersage mit dem Ziel einer risikostratifizierten Infektionskontrolle und -prävention (RISK Prediction for Risk-stratified Infection Control and Prevention)},
  author={Marschollek, Michael and Marquet, Mike and Reinoso Schiller, Nicolás and Naim, Joëlle and Aghdassi, Seven Johannes Sam and Behnke, Michael and Ehrenberg, Sandra and von Landesberger, Tatiana and Misailovski, Martin and Prasser, Fabian and others},
  journal={Bundesgesundheitsblatt-Gesundheitsforschung-Gesundheitsschutz},
  pages={1--8},
  year={2024},
  publisher={Springer}
}