Work package 5 – Management and analysis of health-related data for identification of risk groups and individualized antibiotic therapy.
Purpose: To create a national platform for health analytics that enables data-driven precision health in order to identify risk patients and adapt standard procedures in healthcare to individual patients.
Methods previously developed to identify healthcare-related infections and complications during the VINNOVA-project, VRI-proactive, are refined in this work package to identify patients exposed to increased risk for serious infections, development of resistant infections, and complications/death. AI-based prediction algorithms and machine learning based on a large amount of health data are developed to enable individualize antibiotic therapy and identify patients with a risk to receive ineffective antibiotic treatment. These algorithms are integrated with digital tools which can be further integrated inside healthcare IT-systems. This can make rational antibiotic treatment more effective, by identifying patient groups exposed to increased risk of serious infections and risk of worse medical outcomes (e.g., sepsis). A well-working system like this can also be used as a resource for research with randomized clinical trials in the future.
Work package leader:
Position: Senior infectious diseases physician, Associate Professor
Affiliation: Karolinska Institute