A new European initiative, the European Cardiovascular Health Data and AI Network (CHAIN), has been launched with a budget of €20 million to enhance care for cardiovascular disease, which is the leading cause of death in Europe. The initiative, funded by the EU4Health Programme and coordinated by the European Society of Cardiology (ESC), aims to address the fragmented integration of artificial intelligence (AI) in cardiovascular healthcare. Cardiovascular disease accounts for approximately one in every three deaths in Europe and costs the EU an estimated €282 billion annually.
The CHAIN project brings together a consortium of 53 partners from 20 European countries, including universities, research centers, hospitals, technology companies, national health ministries, and patient organizations. Over the next three years, the project will strive to create a federated ecosystem to safely and effectively integrate AI in cardiovascular care while aligning with the European Health Data Space, which facilitates cross-border health data sharing.
Despite advancements in cardiology, the deployment of AI in routine care has been inconsistent. While numerous AI models have been developed to enhance the early detection of heart disease and improve clinical decision-making, a lack of standardized validation mechanisms has hindered their widespread adoption in hospitals. This often results in reliable tools remaining at the pilot stage, while unverified ones occasionally enter clinical use without proper scrutiny.
CHAIN addresses this challenge through two key components: a federated data infrastructure and a system of validation credentials. The project will enable secure connections among hospitals and health registries across Europe, allowing AI solutions to be tested and validated while keeping sensitive patient data within its original institutions. This approach aligns with the privacy principles of the European Health Data Space, facilitating the evaluation of algorithms across diverse populations and healthcare systems.
Another central feature of CHAIN is the establishment of a European repository of validated AI technologies, each with an ‘AI passport’ documenting its performance, safety, and clinical suitability. This initiative aims to help healthcare officials and practitioners make informed choices about AI tools that can deliver real-world benefits. Professor Folkert Asselbergs of Amsterdam University Medical Centre and CHAIN’s scientific coordinator emphasized the need for healthcare professionals to have a framework that ensures the implementation of trusted innovations.
To validate its framework, CHAIN will roll out six real-world use cases across 13 countries, covering various aspects of cardiovascular care, including risk stratification and disease management. The initiative is designed to highlight disparities in AI tool performance in different healthcare settings, from large hospitals to rural clinics, before widespread implementation.
CHAIN builds upon existing efforts, such as the ESC’s EuroHeart registry network, which aggregates standardized cardiovascular data from multiple countries. It also aims to collaborate with various EU projects, ensuring the efficient use of resources and avoiding redundancy. The project aligns with the EU Safe Hearts Plan, focusing on the innovative integration of AI in cardiovascular healthcare.
As CHAIN launches, it enters a crucial period marked by the European Health Data Space and evolving regulations for medical products, including AI applications. The initiative intends to navigate this regulatory landscape while ensuring that validated AI tools meet clinical safety and efficacy standards. EU Commissioner Olivér Várhelyi remarked on the importance of ensuring that AI works safely for both patients and healthcare professionals, while ESC President Cecilia Linde highlighted the critical need for action in addressing cardiovascular disease.
In the coming years, the CHAIN consortium aims to develop a strategic roadmap for scaling AI adoption in cardiology across Europe, potentially leading to improved patient outcomes and more efficient healthcare systems.
