Medical societies specializing in cardiovascular diseases recommend personalized risk assessment tools to tailor preventive measures, diagnoses, and treatment to individual patients. The implementation of this recommendation in clinical routine is insufficient in Germany. There is a lack of technical structures to bring together relevant information from different sources on often long-term patient treatments; data storage in electronic health records is insufficiently standardized, with a lack of interfaces and connectivity to enable automated individual risk calculations. There is no standardized infrastructure for reproducible high-resolution biosignal analysis (e.g., from ECGs) as an important, previously untapped resource for individual risk assessments. ACRIBiS is an innovative, groundbreaking concept that combines structured clinical records and biosignal analysis and captures its improved predictive power in reality.
ACRIBiS will a) establish standardized collection of cardiovascular data at all partner sites, with patient treatment fully represented by the ACRIBiS cohort (approx. 4,500 patients) b) improve the infrastructure of the Medical Informatics Initiative (MII) with interoperable biosignal integration c) verify predictive power using clinically relevant risk models based on a federated MII and NUM infrastructure d) improve patients’ risk awareness and involve them in individualized risk identification by providing interactive risk visualization (app) in accordance with the Medical Devices Regulation.
ACRIBiS will thus contribute a fundamental building block for the dynamically learning healthcare system of the future at the system level and pave the way for a demonstrably effective and dynamically adaptive clinical decision support tool at the patient level.
The University Medical Center Schleswig-Holstein, the Institute for Medical Informatics and Statistics, and the Department of Cardiology will participate as implementation partners. This includes the implementation of the core cardiovascular data set to be developed as part of the project, as well as the integration and provision of high-resolution ECG data (long-term ECGs and resting ECGs) from clinical IT systems.
