TREAT-Complete: building a shared digital health platform for the future of patient-centred care

As healthcare systems continue to face the growing burden of chronic diseases and fragmented digital tools, the ITEA project TREAT (Transforming Healthcare Through Semantic Interoperability and Self-Efficacy) is working to bring partners, technologies and data streams together into a more connected patient-centred healthcare ecosystem.

A central focus of the project is the development of the TREAT-Complete platform, which is being designed as an integrated digital health environment where all project partners’ technologies, data sources and services can come together. This platform represents one of the most important expected outputs and achievements of the project, as it will provide a common foundation for connecting wearable devices, remote monitoring tools, electronic health records, patient-generated data, AI components and healthcare applications.

Through semantic interoperability, TREAT-Complete aims to align heterogeneous data streams into a common structure, enabling more consistent data exchange, analysis and integration across healthcare platforms. Artificial intelligence and machine learning components will support personalised recommendations, early detection, clinical decision support and improved patient self-management. In this way, the platform is expected to become a key enabler for transforming fragmented digital health solutions into a more connected, patient-centred ecosystem.

Although TREAT-Complete is still evolving as an integrated platform, several concrete components have already been developed within the TREAT ecosystem. These include interactive diabetes data visualisation dashboards built on TURBOARD, AI-generated clinical insight synthesis, a Turkish conversational healthcare analytics interface, a dynamic persona management system, and the Smart ECG T-Shirt System.

The interactive diabetes dashboards allow healthcare professionals and decision makers to explore clinical indicators such as HbA1c values, complication rates, and treatment adherence at both population and patient levels. Combined with AI-generated explanations and persona-based responses, the TREAT-Complete platform helps translate complex clinical data into more understandable and role-specific insights for physicians, nurses, data professionals, and patients. The Smart ECG T-Shirt System further demonstrates the project’s practical direction by enabling comfortable ECG monitoring during daily activities through a wearable garment, wireless data transmission, and motion-tolerant signal processing.

In parallel, additional project partner-driven solutions have reached comparable levels of maturity and real-world validation. These developments include AI-supported patient interaction tools for daily health reflection and behaviour change, which are being tested through pilot studies and randomised controlled trials and subsequently released as mobile applications and integrated platform components across the Netherlands and Canada. Similarly, clinically deployed remote monitoring environments and operational dashboards are already being used in Belgium, Spain, and Portugal to support patient tracking, risk detection, and care workflows in real healthcare settings. Interoperability between partner systems across countries has also been demonstrated through cross-platform data exchange pipelines, enabling the structured flow of patient-generated data and AI-generated insights across digital health platforms and into clinician-facing environments.

Together, these outputs show that TREAT-Complete is not only a concept under development, but a platform supported by concrete, reusable and interoperable components that have been validated across multiple partner implementations. They provide early tangible results, interact directly with potential users and adopters, support feedback from healthcare and technology stakeholders, and improve readiness for future adoption of the TREAT results in real healthcare environments.

More information:

• Project website: https://treatprojects.com/