Open Access

Dominik Felbel, Merten Prüser, Constanze Schmidt, Björn Schreiweis, Nicolai Spicher, Wolfgang Rottbauer, Julian Varghese, Andreas Zietzer, Stefan Störk, Christoph Dieterich, Dagmar Krefting, Eimo Martens, Martin Sedlmayr, Dario Bongiovanni, Christoph B. Olivier, Hendrik Lapp, Hannes H. J. G. Schmidt, Julius L. Katzmann, Felix Nensa, Norbert Frey, Gudrun S. Ulrich-Merzenich, Carina A. Peter, Peter Heuschmann, Udo Bavendiek, Sven Zenker, Ludwig Hinske, Iñaki Soto Rey, Natalia Ortmann, Roland Eils, Lucie Kretzler, Dirk Meyer zum Büschenfelde, Felix Erdfelder, Steffen Ortmann, Dirk Große Meininghaus, Robert Freund, Axel Linke, Stephan Haußig, Miriam Goldammer, Amir Abbas Mahabadi, Obioma Pelka, Christian Haverkamp, Adrian Heidenreich, Christian Becker, Welf Geller, Kim Werle, Angela Merzweiler, Evgeny Lyan, Benjamin Kinast, Thomas Wendt, Christoph Sedlaczek, Sabine Bothe, Markus Vosseler, Daniel Schmitz, Marie Arens, Martin Boeker, Antonius Büscher, Tobias Brix, Hans Kestler, Maximilian Ertl, Kathrin Ungethüm, Kai Günther, Viktoria Rücker

• Aims Personalized risk assessment tools (PRTs) are recommended by cardiovascular guidelines to tailor prevention, diagnosis, and treatment. However, PRT implementation in clinical routine is poor. ACRIBiS (Advancing Cardiovascular Risk Identification with Structured Clinical Documentation and Biosignal Derived Phenotypes Synthesis) aims to establish interoperable infrastructures for standardized documentation of routine data and integration of high-resolution biosignals (HRBs) enabling data-based risk assessment. Methods and results Established cardiovascular risk scores were selected by their predictive performance and served as basis for building a core cardiovascular dataset with risk-relevant clinical routine information. Data items not yet represented in the Medical Informatics Inititative (MII) Core Dataset (CDS) FHIR profiles will be added to an extension module ‘Cardiology’ allowing for maximum interoperability. HRB integration will be implemented at each site through aAims Personalized risk assessment tools (PRTs) are recommended by cardiovascular guidelines to tailor prevention, diagnosis, and treatment. However, PRT implementation in clinical routine is poor. ACRIBiS (Advancing Cardiovascular Risk Identification with Structured Clinical Documentation and Biosignal Derived Phenotypes Synthesis) aims to establish interoperable infrastructures for standardized documentation of routine data and integration of high-resolution biosignals (HRBs) enabling data-based risk assessment. Methods and results Established cardiovascular risk scores were selected by their predictive performance and served as basis for building a core cardiovascular dataset with risk-relevant clinical routine information. Data items not yet represented in the Medical Informatics Inititative (MII) Core Dataset (CDS) FHIR profiles will be added to an extension module ‘Cardiology’ allowing for maximum interoperability. HRB integration will be implemented at each site through a modular infrastructure for electrocardiography (ECG) processing. Predictive performance of PRTs and their dynamic recalibration through HRB integration will be evaluated within the ACRIBiS cohort consisting of 5250 prospectively recruited patients at 15 German academic cardiology departments with 12-month follow-up. The potential of visualising these risks to improve patient education will also be assessed and supported by the development of a self-assessment app. Discussion The ACRIBiS project presents an innovative concept to harmonize clinical data documentation and integrate ECG data, ultimately facilitating personalized risk assessment to improve patient empowerment and prognosis. Importantly, the consensus-based documentation and interoperability specifications developed will support the standardisation of routine patient data collection at the national and international levels, while the ACRIBiS cohort dataset will be available for broad secondary use.…