Semantic Interoperability at National Scale: The SPHN Federated Clinical Routine Dataset

Semantic Interoperability at National Scale: The SPHN Federated Clinical Routine Dataset | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Semantic Interoperability at National Scale: The SPHN Federated Clinical Routine Dataset Jan Armida, Vasundra Touré, Philip Krauss, Deepak Unni, Harald Witte, and 16 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8250886/v2 This work is licensed under a CC BY 4.0 License Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Abstract Over the past eight years, the Swiss Personalized Health Network (SPHN) has established a national federated framework enabling semantically interoperable health-related data, with a primary focus on hospital clinical routine data. Rather than centralizing patient-level information, hospitals locally perform semantic coding and standardization and store SPHN-compliant data in dedicated triple stores. To promote discoverability, descriptive metadata and summary statistics derived from these local datasets are then centralized in the SPHN Metadata Catalog, which follows the SPHN Metadata Catalog Schema and aligns with European Health Data Space metadata standards. As of 2025, the SPHN Federated Clinical Routine Dataset encompasses information from more than 800,000 patients who provided broad consent, covering the period from 2018 to present. Across the first six participating hospitals, the infrastructure holds over 12.5 billion (10^9) RDF triples mapped to 125 SPHN semantic concepts including demographics, diagnoses, procedures, medications, laboratory results, vital signs, clinical scores, allergies, microbiology, intensive care data, oncology, and biological samples. This federated approach ensures that health data remain FAIR (Findable, Accessible, Interoperable, and Reusable) while safeguarding patient privacy by avoiding centralizing information. In this paper, we present the design, implementation, and scope of the SPHN Federated Clinical Routine Dataset, and its role in supporting data discoverability for research and clinical applications. Federated datasets Metadata Knowledge Graph RDF Terminology Usage Real World Data Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 2 posted You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8250886","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":557339332,"identity":"c23dcc6b-85e1-4bcb-9160-58c0ab7de11f","order_by":0,"name":"Jan Armida","email":"","orcid":"https://orcid.org/0009-0007-4250-3983","institution":"SIB Swiss Institute of Bioinformatics,","correspondingAuthor":false,"prefix":"","firstName":"Jan","middleName":"","lastName":"Armida","suffix":""},{"id":557339333,"identity":"8322cd72-483e-40c7-88eb-0edbe31f9d23","order_by":1,"name":"Vasundra 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