A Federated FHIR-Based Interoperability Framework for Multi-Site Heart Failure Monitoring: The RETENTION Project

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Authors: Nikolaos Vasileiou, Olympia Giannakopoulou, Ourania Manta, Konstantinos Bromis, Theodoros Panagiotis Vagenas, Ioannis Kouris, Maria Roumpi, Lefteris Koumakis, Yorgos Goletsis, Maria Haritou, George K. Matsopoulos, D.I. Fotiadis
+1 more Dimitris Koutsouris
Cited by: 1
References: 47

Abstract

Heart failure management increasingly relies on heterogeneous clinical and real-world data generated through remote monitoring technologies. However, transforming these multimodal data streams into actionable insights requires robust interoperability infrastructures. This study presents the RETENTION interoperability framework, a federated HL7 Fast Healthcare Interoperability Resources (FHIR)-based architecture designed to support multi-site heart failure monitoring across five independent clinical environments. A semantic reference model comprising 444 clinical and contextual variables was developed and aligned with FHIR R4 resources and internationally recognised terminology systems. The platform adopts a selective profiling strategy, extending only the Patient resource while standardising the remaining variables through example-driven Implementation Guide documentation. Identifiable data are retained locally within Clinical Site Backends, whereas anonymised datasets are periodically aggregated into a Global Insights Cloud to enable centralised analytics and controlled third-party interactions. The framework was deployed across six hospitals (with two Spanish hospitals sharing the same deployment), supporting 390 patients and over 130,000 patient-days of monitoring, with more than 3.6 million remote device data points harmonised without schema conflicts. The results demonstrate that large-scale semantic harmonisation and privacy-preserving aggregation can be achieved using a lightweight profiling approach, providing a scalable and reproducible interoperability model for multi-centre digital health research infrastructures.

Fields of Study & Subjects

Electronic Health Records Systems Healthcare Technology and Patient Monitoring Machine Learning in Healthcare

Publication details

Journal / source
Computers
Publisher
MDPI AG
Volume
15
Issue
4
Pages
212–212
Publication date
31 March 2026
Language
EN