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Review
. 2025 Aug 4;27(8):euaf149.
doi: 10.1093/europace/euaf149.

EHRA perspective on the digital data revolution in arrhythmia management: insights from the association's annual summit

Vassil Traykov  1 , Helmut Puererfellner  2 , Haran Burri  3 , Csaba Laszlo Foldesi  4 , Daniel Scherr  5 , David Duncker  6 , Elena Arbelo  7   8   9   10 , Giovanni Luca Botto  11 , Giuseppe Boriani  12 , Hein Heidbuchel  13   14 , Katarzyna Malaczynska-Rajpold  15   16 , Michal M Farkowski  17   18 , Nikolaos Dagres  19 , Piotr Szymanski  20 , Radu Huculeci  21 , Ruben Casado-Arroyo  22 , Serge Boveda  23   24 , José L Merino  25
Affiliations
Review

EHRA perspective on the digital data revolution in arrhythmia management: insights from the association's annual summit

Vassil Traykov et al. Europace. .

Abstract

The 2024 European Heart Rhythm Association (EHRA) Summit in Warsaw focused on the digital transformation of arrhythmia management, convening over 130 stakeholders from academia, industry, and policy. This review summarises the current state (in 2025) and future directions of digital health in arrhythmia care, including remote monitoring (RM) of cardiac implantable electronic devices (CIEDs), mobile health (mHealth), artificial intelligence (AI), and integration into the European Health Data Space (EHDS). RM has become central to CIED follow-up, improving outcomes and reducing healthcare use. However, challenges in reimbursement, workforce adaptation, and data interoperability persist. The absence of standardised data exchange between device vendors and healthcare systems has led to initiatives like the World Forum on CIED follow-up to develop interoperability standards. mHealth tools, including apps and wearable devices, offer accurate arrhythmia detection but face regulatory, digital literacy, and privacy barriers. The EHDS aims to enable cross-border data sharing for personalised care and real-world research, though implementation must address ethical, legal, and infrastructural issues. AI shows promise in prediction, monitoring, and data integration, but lacks standardised, transparent validation. The ESC-EHRA Atlas in Heart Rhythm Disorders supports structured data collection to harmonize and benchmark care across Europe. Overall, digital innovations, if coupled with regulatory alignment, interoperability standards, and equitable access, have the potential to shift arrhythmia management toward a more predictive, personalized, and efficient model of care.

Keywords: Arrhythmia; Artificial intelligence; CIEDs; Digital health; EHRA; European Health Data Space; Health data integration; Interoperability; Remote monitoring; mHealth.

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Conflict of interest statement

Conflict of interest: C.L.F. reports receiving compensation for teaching and proctoring from Medtronic and Biotronik SE & Co. D.D. received modest lecture honoraria, travel grants and/or a fellowship grant from Abbott, Astra Zeneca, Biotronik, Boehringer Ingelheim, Boston Scientific, Bristol Myers Squibb, CVRx, Daiichi Sankyo, Medtronic, Microport, Pfizer, Sanofi, ZOLL. E.A. reports speaker fees for Medtronic, Biosense Webster and Bristol-Myers-Squibb; Consulting for Boston Scientific. G.B. reports speaker's fees of small amount from Bayer, Boston, BMS, Daiichi-Sankyo, Janssen, Sanofi. G.L.B. reports speaker's fees (small amount) from Abbott, Boston Scientific, Biotronik, Medtronic, MIcroport, Bayer Heathcare, Daiichi Sankyo; Pfizer. H.H. received personal lecture and consultancy fees from, Biotronik, Daiichi-Sankyo, Downtown Europe, IZIDOK, European Society of Cardiology, and Viatris Pharmaceuticals Inc. He received unconditional research grants through the University of Antwerp and/or the University of Hasselt from Abbott, Bayer, Boehringer-Ingelheim, Biosense-Webster, Boston-Scientific, Daicchi-Sankyo, Viatris Pharmaceuticals Inc, Novo Nordisk, Novartis, and Pfizer-BMS, all outside the scope of this work. H.B. has received institutional research and fellowship support, speaker fees, travel grants, and/or advisory boards from Abbott, Biotronik, Boston Scientific, Medtronic Microport. H.P. received speaker´s honoraria and consultancy fees from Abbott, Boston Scientific, Biotronik, Medtronic, Johnson and Johnson Medtech. J.LM. has received fees and honoraria for lectures, education and scientific advice from Abbott, Biotronik, Daiichi-Sankyo, Everpace, Johnson&Johnson, Zio & Zoll. M.M.F. received consultancy/speaker fees from Abbott, Biosense-Webster, Medtronic, Pfizer. P.S. reports receiving speakers’ honoraria from Boehringer Ingelheim, Novartis, AstraZeneca, Samsung Medison, GE Ultrasound. R.C.-A. reports receiving speaker’s honoraria of small amount from Abbott and Boston Scientific. V.T. reports receiving speakers’ honoraria or travel grants from: Boehringer Ingelheim, Novartis, Pfizer, Servier, J&J, Astra Zeneca, Medtronic. Proctorship fees: Abbott, Biotronik. S.B. is a consultant for Medtronic, Boston Scientific, Microport, and Zoll. D.S., K.M.-R., N.D. and R.H. do not report any disclosures.

Figures

Graphical Abstract
Graphical Abstract
Figure 1
Figure 1
Current status of reimbursement for remote monitoring of ICD/CRT-D (A) and other CIEDs (panel B) in the European countries. Category definitions: YES: Fully reimbursed by mandatory or voluntary, public or private, insurance, or reimbursement level decided on a case-by-case basis or at the region level. NO: Technology is fully covered with patients’ private expenditure (out-of-pocket) or other sources, or there is no agreed reimbursement scheme. Technology not available in the country: the technology is not available in the country. No data: no information is available. Source: The 2025 ESC-EHRA Atlas on Heart Rhythm Disorders (ref.).
Figure 2
Figure 2
Interoperable data flow framework for patients with CIED remote monitoring. This diagram illustrates the integration of remote monitoring data from diverse CIED manufacturers through their respective web platforms. Using the FHIR (Fast Healthcare Interoperability Resources) standard, data are standardised and shared with electronic health records (EHRs), third-party platforms, and clinicians. The model ensures a unified, interoperable system for clinical decision-making and enables both remote and in-office interrogations. It highlights the importance of standardised data exchange for effective multi-vendor device monitoring and patient management. CIED, cardiac implantable electronic device; EHR, electronic health record; FHIR, Fast Healthcare Interoperability Resource.
Figure 3
Figure 3
Key recommendations for standardization of mHealth solutions. EHR, electronic health record; FHIR, Fast Healthcare Interoperability Resource; GDPR, General Data Protection Regulation.
Figure 4
Figure 4
The main pillars of the European health data space concept (https://digital-strategy.ec.Europa.eu/en/news/transformation-health-and-care-digital-single-market-gaining-more-support). The figure illustrates three core components: (i) Access and exchange of health data—enabling individuals and healthcare providers to securely share medical records across borders; (ii) Patient-centred healthcare by digital data—promoting integrated care through digital tools such as electronic health records, wearables, and cloud-based platforms; and (iii) Pooling of health data—facilitating secondary use of anonymised health data for research, innovation, policy-making, and public health, while ensuring privacy and security.
Figure 5
Figure 5
Key challenges in implementing artificial intelligence (AI) in healthcare. The figure summarizes critical barriers to the adoption of AI-based models in clinical practice. These include technical challenges, such as the need for extensive training and large annotated datasets; regulatory and validation requirements, especially due to the adaptive nature of AI; data security, requiring strict compliance with privacy laws; the potential for algorithmic bias, which may impact clinical fairness; and finally, clinical integration, which is often hindered by limited training and user scepticism. Addressing these factors is essential for safe, effective, and equitable deployment of AI in medicine.
Figure 6
Figure 6
The ESC atlas of cardiology four-step data framework.
See this image and copyright information in PMC

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