Advancing Cardiovascular Risk Identification with Structured Clinical Documentation and Biosignal Derived Phenotype Synthesis

Medical professional societies recommend personalized risk assessment tools to tailor prevention, diagnosis, and treatment of cardiovascular diseases. However, implementing these recommendations in clinical practice in Germany requires improvement. There is a lack of technical infrastructure to integrate relevant clinical information from various sources, insufficient standardization and structure in electronic health records for data capture, and challenges in data exchange, hindering automated individual risk calculations. Furthermore, there is a need for a standardized infrastructure for high-resolution biosignal analysis (such as from EKGs), an untapped resource for individual risk assessment.

ACRIBiS aims to address these gaps. It combines standardized and structured clinical records with biosignal analysis at 15 partner sites, investigating the improvement achievable in individual risk estimation. ACRIBiS will establish a standardized capture of relevant clinical data, enhance the interoperable biosignal integration in the joint infrastructure of the Medical Informatics Initiative (MII) and the University Medicine Network (NUM), validate the predictive power of risk models based on standardized clinical documentation and biosignals individually and in combination using the ACRIBiS cohort (approximately 4500 patients). Additionally, it will involve patients in personalized risk identification by providing an interactive risk visualization app, contributing to risk awareness development.

ACRIBiS will contribute a fundamental component to the future dynamically learning healthcare system at the system level, paving the way for proven effective and dynamically adaptive clinical decision support at the patient level.