Sessions

It sounds so easy to start working with your healthcare data to support your organization's needs and to deliver digital services to the patients. You see all this excellent digital service from other branches, so why can't we do the same? When working with healthcare data and patients, it is essential to understand the various objectives that present challenges in this process.To promote healthcare data interoperability, Halmstad University, Region Halland, Capio Ramsay Santé, Mölnlycke Healthcare, InterSystems, and Avenga are running a joint research project within the framework of the research profile CAISR Health. We will explore how multidisciplinary knowledge co-creation can drive practical interoperability in data-driven care, using standardized models such as openEHR and OMOP CDM while upholding data reliability, clinical validity, regulatory compliance, and alignment with the European Health Data Space (EHDS).

The work to harmonize FHIR Base profiles of Nordic countries was initiated in Vitalis 2023 (https://invitepeople.com/public/events/edd1776c4a/seminars/ca0805fa9c).Denmark, Finland, Norway, and Sweden have all published national FHIR base profiles through their HL7 affiliates. There is an ongoing initiative to harmonize the base profiles and to create common Nordic FHIR Base profile specification. Given the similarity of the healthcare systems of all the Nordic countries, we can learn from each other in developing and using national FHIR base profiles and reach a higher level of base-profile harmonization between Nordic countries.  Also, due to the EHDS regulation, standardization efforts in Europe are now of central importance and HL7 Europe is a key organization in those efforts. With collaboration and harmonization between Nordic countries we can also in a better way contribute and influence European work, including European HL7 FHIR base profiles.This session will present the current status of this work, including involvement on the European level, and a call for participation for interested parties.

Authors: Tanya McCance, Brendan McCormack

Separate registration needed

Authors: Elin-Sofie Forsgärde, Marco Socci, Gabriele Morettini, Maria Gabriella Melchiorre, Elizabeth Hanson

The EHDS regulation is now in force, with implementation milestones beginning in 2029. But moving from policy to working infrastructure is the real challenge. This session explores what it takes to build sovereign, AI-ready health data platforms for EHDS - from enabling cross-border care continuity and interoperable health records, to powering secure secondary use through trusted research environments and privacy-preserving analytics. With a focus on Nordic readiness and practical implementation pathways, this session is for healthcare leaders, CIOs, data architects, researchers, and solution providers preparing for Europe's health data transformation.Vitalis Key Partner - Amazon Web Services 

How can healthcare systems remain functional during crises, war and disruptions to infrastructure and supply chains without creating one model for ordinary times and another for emergencies? This seminar explores how person-centred care can serve as the foundation for a healthcare system that is resilient by design, with home dialysis as a concrete and compelling example.The seminar brings together perspectives from policy, healthcare, innovation and person-centred care to discuss how home-based care models can support a more resilient healthcare system for both everyday delivery and exceptional circumstances.

Authors: Ruth Smoother, Karen Tuqiri, Lucinda Barlow

Authors: Shinya Mitani, HIrofumi Ogawara, Shoko Miyagawa, Ardith Doorenbos, Hiroki Fukahori

The ASAP Stroke project explores how artificial intelligence (AI) can support early stroke assessment and triage in prehospital settings. The project follows two tracks: traditional AI using structured data such as registry data, vital signs, and clinical observations; and video-based analysis using machine learning (ML) to assess neurological features associated with stroke from patient videos recorded in ambulances. Synthetic video data are used to enable model development while preserving patient privacy, with initial studies demonstrating promising performance in assessing eye movement abnormalities and neglect. By integrating these data sources into an AI-based clinical decision support system (CDSS), ASAP Stroke aims to improve stroke identification, distinguish large vessel occlusions (LVO) and guide optimal care pathways. Overall, ASAP Stroke seeks to strengthen prehospital decision-making, bridge prehospital and in-hospital stroke assessment, reduce time-to-treatment and improve patient outcomes.