ArticleJAMIA open2023
Transforming Estonian health data to the Observational Medical Outcomes Partnership (OMOP) Common Data Model: lessons learned.
Article in JAMIA open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- DrugUtilisation: An R Package to Support Drug Utilisation Research Using the OMOP Common Data Model.Pharmacoepidemiology and drug safety · 2026Article
- Data Resource Profile: EST-Health-30.International journal of epidemiology · 2026Article
- Extracting and Classifying Drug Discontinuations From Estonian Electronic Health Records: Development and Validation Study.Journal of medical Internet research · 2026Article
- Addressing Data Quality Challenges in Lung Cancer Data Within the Observational Medical Outcomes Partnership Common Data Model: Observational Study.Journal of medical Internet research · 2026Observational
- Data harmonization processes of cancer data into the observational medical outcomes partnership common data model.Scientific reports · 2026Article
- Rethinking Trust in Synthetic Health Data: Lessons From 7 European Research Initiatives.Journal of medical Internet research · 2026Article
- Systematic evaluation of medication adherence determinants across 137 active substances on population-level real-world health data.Communications medicine · 2026Article
- Data Resource Profile: Linking nationwide health and social registries in Estonia (BIG-HEART).International journal of epidemiology · 2026Article
- A Comprehensive Approach to Days' Supply Estimation in a Real-World Prescription Database: Algorithm Development and Validation Study.Online journal of public health informatics · 2026Article
- A multidimensional hierarchical framework for sources of bias in real-world healthcare evidence: a scoping review.Journal of biomedical informatics · 2026Article
- Risks of autoimmune and inflammatory post-acute COVID-19 conditions: a network cohort study in six European countries, the USA and Korea.BMJ public health · 2026Article
- Semiautomatic mapping of a national drug terminology to standardised OMOP drug concepts using publicly available supplementary information.BMC medical research methodology · 2025Article
- Establishing standards: harmonising coding principles for a minimal cancer dataset in the OMOP Common Data Model.ESMO real world data and digital oncology · 2025Article
- The Estonian Biobank's journey from biobanking to personalized medicine.Nature communications · 2025Review
- Conversion of Sensitive Data to the Observational Medical Outcomes Partnership Common Data Model: Protocol for the Development and Use of Carrot.JMIR research protocols · 2025Article
- Article
- Mapping Emergency Medicine Data to the Observational Medical Outcomes Partnership Common Data Model: A Gap Analysis of the American College of Emergency Physicians Clinical Emergency Data Registry.Journal of the American College of Emergency Physicians open · 2025Article
- Kineret: Israel's Largest Hospital Network Transformed into the OMOP common data model for collaborative research.PloS one · 2025Article
- Incidence of post-acute COVID-19 symptoms across healthcare settings in seven countries: an international retrospective cohort study using routinely-collected data.EClinicalMedicine · 2024Article
- Implementation of the Observational Medical Outcomes Partnership Model in Electronic Medical Record Systems: Evaluation Study Using Factor Analysis and Decision-Making Trial and Evaluation Laboratory-Best-Worst Methods.JMIR medical informatics · 2024Article
Corrections and comments
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Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To describe the reusable transformation process of electronic health records (EHR), claims, and prescriptions data into Observational Medical Outcome Partnership (OMOP) Common Data Model (CDM), together with challenges faced and solutions implemented. Materials and Methods: We used Estonian national health databases that store almost all residents' claims, prescriptions, and EHR records. To develop and demonstrate the transformation process of Estonian health data to OMOP CDM, we used a 10% random sample of the Estonian population ( Results: In total, we transformed over 100 million entries to standard concepts using standard OMOP vocabularies with the average mapping rate 95%. For conditions, observations, drugs, and measurements, the mapping rate was over 90%. In most cases, SNOMED Clinical Terms were used as the target vocabulary. Discussion: During the transformation process, we encountered several challenges, which are described in detail with concrete examples and solutions. Conclusion: For a representative 10% random sample, we successfully transferred complete records from 3 national health databases to OMOP CDM and created a reusable transformation process. Our work helps future researchers to transform linked databases into OMOP CDM more efficiently, ultimately leading to better real-world evidence.
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