Lessons Learned From European Health Data Projects With Cancer Use Cases: Implementation of Health Standards and Internet of Things Semantic Interoperability
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| Publicat a: | Journal of Medical Internet Research vol. 27 (2025), p. e66273 |
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| Autor principal: | |
| Altres autors: | , , , , , , , , , , , , , , , , , , |
| Publicat: |
Gunther Eysenbach MD MPH, Associate Professor
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| Matèries: | |
| Accés en línia: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 1438-8871 | ||
| 024 | 7 | |a 10.2196/66273 |2 doi | |
| 035 | |a 3222368428 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a Gyrard, Amelie | |
| 245 | 1 | |a Lessons Learned From European Health Data Projects With Cancer Use Cases: Implementation of Health Standards and Internet of Things Semantic Interoperability | |
| 260 | |b Gunther Eysenbach MD MPH, Associate Professor |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a The adoption of the European Health Data Space (EHDS) regulation has made integrating health data critical for both primary and secondary applications. Primary use cases include patient diagnosis, prognosis, and treatment, while secondary applications support research, innovation, and regulatory decision-making. Additionally, leveraging large datasets improves training quality for artificial intelligence (AI) models, particularly in cancer prevention, prediction, and treatment personalization. The European Union (EU) has recently funded multiple projects under Europe’s Beating Cancer Plan. However, these projects face challenges related to fragmentation and the lack of standardization in metadata, data storage, access, and processing. This paper examines interoperability standards used in six EU-funded cancer-related projects: IDERHA (Integration of Heterogeneous Data and Evidence Towards Regulatory and Health Technology Assessments Acceptance), EUCAIM (European Cancer Imaging Initiative), ASCAPE (Artificial Intelligence Supporting Cancer Patients Across Europe), iHelp, BigPicture, and the HealthData@EU pilot. These initiatives aim to enhance the analysis of heterogeneous health data while aligning with EHDS implementation, specifically for the EHDS for the secondary use of data (EHDS2). Between October 2023 and July 2024, we organized meetings and workshops among these projects to assess how they adopt health standards and apply Internet of Things (IoT) semantic interoperability. The discussions focused on interoperability standards for health data, knowledge graphs, the data quality framework, patient-generated health data, AI reasoning, federated approaches, security, and privacy. Based on our findings, we developed a template for designing the EHDS2 interoperability framework in alignment with the new European Interoperability Framework (EIF) and EHDS governance standards. This template maps EHDS2-recommended standards to the EIF model and principles, linking the proposed EHDS2 data quality framework to relevant International Organization for Standardization (ISO) standards. Using this template, we analyzed and compared how the recommended EHDS2 standards were implemented across the studied projects. During workshops, project teams shared insights on overcoming interoperability challenges and their innovative approaches to bridging gaps in standardization. With support from HSbooster.eu, we facilitated collaboration among these projects to exchange knowledge on standards, legal implementation, project sustainability, and harmonization with EHDS2. The findings from this work, including the created template and lessons learned, will be compiled into an interactive toolkit for the EHDS2 interoperability framework. This toolkit will help existing and future projects align with EHDS2 technical and legal requirements, serving as a foundation for a common EHDS2 interoperability framework. Additionally, standardization efforts include participation in the development of ISO/IEC 21823-3:2021—Semantic Interoperability for IoT Systems. Since no ISO standard currently exists for digital pathology and AI-based image analysis for medical diagnostics, the BigPicture project is contributing to ISO/PWI 24051-2, which focuses on digital pathology and AI-based, whole-slide image analysis. Integrating these efforts with ongoing ISO initiatives can enhance global standardization and facilitate widespread adoption across health care systems. | |
| 610 | 4 | |a International Organization for Standardization European Union | |
| 651 | 4 | |a Europe | |
| 653 | |a Cancer | ||
| 653 | |a Medical prognosis | ||
| 653 | |a Metadata | ||
| 653 | |a Interoperability | ||
| 653 | |a Collaboration | ||
| 653 | |a Ontology | ||
| 653 | |a Communication | ||
| 653 | |a Medical diagnosis | ||
| 653 | |a Workshops | ||
| 653 | |a Graphs | ||
| 653 | |a Initiatives | ||
| 653 | |a Segmentation | ||
| 653 | |a International organizations | ||
| 653 | |a Internet | ||
| 653 | |a Medical imaging | ||
| 653 | |a Medical technology | ||
| 653 | |a Health initiatives | ||
| 653 | |a Internet of Things | ||
| 653 | |a Standardization | ||
| 653 | |a Innovations | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Patients | ||
| 653 | |a Pathology | ||
| 653 | |a Quality standards | ||
| 653 | |a Infrastructure | ||
| 653 | |a Data quality | ||
| 653 | |a Clinical decision making | ||
| 653 | |a Health care | ||
| 653 | |a Medical research | ||
| 653 | |a Implementation | ||
| 653 | |a Frame analysis | ||
| 653 | |a Algorithms | ||
| 653 | |a Harmonization | ||
| 653 | |a Privacy | ||
| 653 | |a Health information | ||
| 653 | |a Governance | ||
| 653 | |a Data exchange | ||
| 653 | |a Health technology assessment | ||
| 653 | |a Semantics | ||
| 653 | |a Health | ||
| 653 | |a Principles | ||
| 653 | |a Adoption of innovations | ||
| 653 | |a Standards | ||
| 653 | |a Data processing | ||
| 653 | |a Health services | ||
| 653 | |a Decision making | ||
| 653 | |a Storage | ||
| 653 | |a Medical decision making | ||
| 653 | |a Regulation | ||
| 653 | |a Medical treatment | ||
| 653 | |a Research applications | ||
| 700 | 1 | |a Abedian, Somayeh | |
| 700 | 1 | |a Gribbon, Philip | |
| 700 | 1 | |a Manias, George | |
| 700 | 1 | |a Rick van Nuland | |
| 700 | 1 | |a Zatloukal, Kurt | |
| 700 | 1 | |a Nicolae, Irina Emilia | |
| 700 | 1 | |a Danciu, Gabriel | |
| 700 | 1 | |a Nechifor, Septimiu | |
| 700 | 1 | |a Marti-Bonmati, Luis | |
| 700 | 1 | |a Mallol, Pedro | |
| 700 | 1 | |a Dalmiani, Stefano | |
| 700 | 1 | |a Autexier, Serge | |
| 700 | 1 | |a Jendrossek, Mario | |
| 700 | 1 | |a Avramidis, Ioannis | |
| 700 | 1 | |a Eva Garcia Alvarez | |
| 700 | 1 | |a Holub, Petr | |
| 700 | 1 | |a Blanquer, Ignacio | |
| 700 | 1 | |a Boden, Anna | |
| 700 | 1 | |a Rada Hussein | |
| 773 | 0 | |t Journal of Medical Internet Research |g vol. 27 (2025), p. e66273 | |
| 786 | 0 | |d ProQuest |t Library Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3222368428/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3222368428/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3222368428/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |