The ‘Advancing Cardiovascular Risk Identification with Structured Clinical Documentation and Biosignal Derived Phenotypes Synthesis’ project: conceptual design, project planning, and first implementation experiences
European Heart Journal - Digital Health

Abstract
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.
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.
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.
The study is registered at the German study registry (DRKS): #DRKS00034792.
Contributors

Merten Prüser
Author

Constanze Schmidt
Author

Björn Schreiweis
Author

Nicolai Spicher
Author

Wolfgang Rottbauer
Author

Julian Varghese
Author

Andreas Zietzer
Author

Christoph Dieterich
Author

Dagmar Krefting
Author

Eimo Martens
Author

Martin Sedlmayr
Author

Dario Bongiovanni
Author

Christoph B Olivier
Author

Hendrik Lapp
Author

Hannes H J G Schmidt
Author

Julius L Katzmann
Author

Felix Nensa
Author

Norbert Frey
Author

Gudrun S Ulrich-Merzenich
Author

Carina A Peter
Author

Peter Heuschmann
Author

Udo Bavendiek
Author

Sven Zenker
Author

Ludwig Hinske
Author

Iñaki Soto Rey
Author

Natalia Ortmann
Author

Roland Eils
Author

Lucie Kretzler
Author

Dirk Meyer zum Büschenfelde
Author

Felix Erdfelder
Author

Steffen Ortmann
Author

Dirk Große Meininghaus
Author

Robert Freund
Author

Axel Linke
Author

Stephan Haußig
Author

Miriam Goldammer
Author

Amir Abbas Mahabadi
Author

Obioma Pelka
Author

Christian Haverkamp
Author

Adrian Heidenreich
Author

Christian Becker
Author

Welf Geller
Author

Kim Werle
Author

Angela Merzweiler
Author

Evgeny Lyan
Author

Benjamin Kinast
Author

Thomas Wendt
Author

Christoph Sedlaczek
Author

Sabine Bothe
Author

Markus Vosseler
Author

Daniel Schmitz
Author

Marie Arens
Author

Martin Boeker
Author

Antonius Büscher
Author

Tobias Brix
Author

Hans Kestler
Author

Maximilian Ertl
Author

Kathrin Ungethüm
Author

Kai Günther
Author

Viktoria Rücker
Author
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