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The OHDSI Sweden community is building the OMOP data model
The adoption of the OMOP Common Data Model (Observational Medical Outcomes Partnership), which aims to harmonise health data, is still at an early stage in Sweden, but progress is rapid. This work is being advanced by the newly established OHDSI Sweden community.
The OHDSI Sweden community is led and organised by Dr. Jordan Kane, Project Manager at the research and innovation company Chalmers Industriteknik. The community is open to everyone interested in promoting the responsible adoption of OMOP in Sweden, including clinicians, researchers, data engineers, informaticians, registry experts, authorities, companies, and patient-centred stakeholders. The community aims to engage 50–100 committed members.
OHDSI (Observational Health Data Sciences and Informatics), which develops OMOP, is an international collaborative network whose goal is to unlock the value of health data through large-scale analytics. All solutions are based on open-source software. The coordinating centre is located at Columbia University in New York, United States. OHDSI also has a strong regional and national network across Europe.
In OMOP, Data from Different Healthcare Systems Are Transformed into a Common Format
Within the OMOP Common Data Model, data collected in different countries or regions can be compared, studies can be replicated across datasets, analytical tools and methods can be applied to different data sources without customisation, and data can be analysed in a federated manner without transferring patient-level data between organisations. In practice, data from different hospitals, registries, and healthcare systems are transformed into a standardised structure.
According to Jordan Kane, the goal of OHDSI Sweden is to help Sweden build OMOP as a reusable analytics infrastructure rather than merely a new data standard. This includes shared mappings and terminologies, data quality assurance, and cohort definitions that can be reused across regions, registries, and studies.
“This means supporting local value creation while gradually building coherent national capacity,” Kane explains.
Kane describes Sweden’s health data assets as among the most valuable in the world. However, a key challenge remains that data, expertise, governance, and terminology are fragmented across many organisations and systems.
“This leads to duplicated work, slow study initiation, and limited comparability across regions and registries. OMOP provides a practical way to make analytics more reusable, comparable, and scalable while preserving local data governance. This is particularly important as Europe moves toward more structured cross-border secondary use of health data through the European Health Data Space (EHDS),” Kane notes.
OMOP Creates Value for Healthcare, Research, Industry, and Patients
- Healthcare: OMOP can support improvements in quality of care, care pathway analysis, clinical insights, precision medicine analytics, benchmarking, and the validation of artificial intelligence solutions.
- Research and innovation: OMOP can help launch studies more rapidly and make them easier to replicate and compare across sites and disciplines. In the life sciences and innovation ecosystem, OMOP can support more efficient generation of real-world evidence, feasibility assessments, patient identification, and the evaluation of treatments in healthcare settings.
- Patients: For patients, the long-term value of OMOP lies in enabling existing health data to more effectively support stronger evidence, safer and more precise treatments, and faster learning across the healthcare system.
Nordic Countries Face Similar Challenges, Making OMOP Collaboration Essential
OHDSI Sweden considers Nordic collaboration important because the Nordic countries face similar challenges: strong health data assets, small populations, decentralised governance, long-standing registry traditions, and increasing EU-level requirements for harmonization of health data. Not everything needs to be reinvented at the national level. Examples include terminologies and mappings, federated analytics methods, and training.
“The goal is not to create a single shared Nordic system, but to build practical collaboration and mutual learning so that the Nordic countries can participate more strongly in European and international OMOP-based research and innovation, and promote data-intensive care models such as precision medicine,” Kane explains.
A Phased Roadmap for OMOP Implementation in Sweden
- 2026: Focus on coordination, training, selection of pilots, clarification of legal and administrative issues, terminology planning, and building the OHDSI Sweden community.
- 2027–2028: Focus on more concrete regional- and registry-level implementations that generate reusable national resources.
- From 2029 onwards: Sweden will be better prepared for EHDS-compatible federated analytics and international collaboration.
