Programpunkter

This panel discussion explores how a Nordic federated network can unlock the full potential of Nordic health data and strengthen Real-World Evidence (RWE) generation.Professor Kimmo Porkka from Helsinki University Hospital and founder of FinOMOP will introduce the session with a presentation on FinOMOP—a nationwide, population-based harmonized health data infrastructure in Finland, aiming for full coverage by 2026. Through collaboration with all five Finnish university hospitals and national registries, a large share of patient data (70%) is already mapped to OMOP CDM.Following his introduction, the panel will discuss how Sweden and other Nordic countries can build on FinOMOP’s success to leverage its high-quality health data and create a Nordic-wide federated research network. The discussion will explore lessons learned from existing federated networks, the steps Sweden should take to harmonize health data for secondary use, and which data sources should be prioritized for maximum impact. Can the Nordics be a global hub for pharmaceutical companies, biotech firms, AI-driven healthcare innovators, and clinical trial sponsors seeking access to high-quality, real-time real-world data.This session concludes the four-part OMOP introduction at Vitalis, providing a forum for next steps, collaboration opportunities, and practical insights on Nordic OMOP adoption.

This presentation provides a practical overview of implementing the OMOP CDM in a collaborative, pan-European oncology research setting and learnings from a specific study. Professor Åslaug Helland will present a case study from the DigiONE pilot project, where harmonized oncology data was used to evaluate overall survival (OS) in metastatic non-small cell lung cancer (mNSCLC) patients based on metastasis location. The study leveraged federated analysis across multiple European cancer centers, including Oslo University Hospital, to generate real-world evidence while preserving patient privacy. 
This presentation is the third in a series of presentations given as an introduction to OMOP at Vitalis.

This session builds on the previous OMOP 101 session. IT will provide a more practical perspective for organizations looking to adopt the OMOP Common Data Model (CDM) and join the OHDSI community to get started with federated analytics. The presentation will draw from the OMOP experience from Helsinki University Hospital (HUS) and outline key steps, required competencies, and infrastructure needed for implementation, as well as information on how to join and leverage the international OHDSI network in the process.The presentation will show how HUS has successfully navigated the process from data sources, through ETL (Extract, Transform, Load) to OMOP data, quality control, to the first federated real-world study, and further into swarm-learning for predictive modelling.This presentation is the second in a series of presentations given as an introduction to OMOP at Vitalis.

In the rapidly evolving landscape of healthcare data analytics, the OMOP Common Data Model (CDM) has emerged as a game-changer, revolutionizing the way real-world evidence (RWE) is generated and utilized. This presentation gives an introduction to the OMOP Common Data model and its open community. It highlights OMOP's role in enhancing data interoperability, facilitating multi-country observational studies, and its synergy with other standards. This presentation is the first in a series of presentations given as an introduction to OMOP at Vitalis.