How well does OMOP CDM fit Vietnam? This article analyzes the policy context (Decision 3516/QĐ-BYT, Personal Data Protection Law 2025, Medical Examination and Treatment Law 15/2023, electronic health records on VNeID), Ministry of Health catalog mapping, custom vocabularies, and a roadmap for a national research data lake.
By 2026, mature organizations run both FHIR (operational) and OMOP (analytics). This article walks through resource ↔ table mapping, the FHIR-OMOP-on-FHIR working group, Pathling, the Bulk Data Export pipeline, and deployment patterns for Vietnam.
A 100M-event CDM in production behaves nothing like the Eunomia sample. This article covers schema design, indexing, partitioning by person_id, vacuum, backup, security under Vietnam's Personal Data Protection Law 2025 (effective Jan 1, 2026), audit logging, and vocabulary upgrades.
HADES (Health Analytics Data-to-Evidence Suite) is the OHDSI bundle of R packages for Patient-Level Estimation, Patient-Level Prediction, Characterization, and Self-Controlled Case Series. This article walks from install to publishing a network study.
ATLAS is the official OHDSI cohort builder; Data Quality Dashboard runs more than 3,000 quality checks; ACHILLES profiles each CDM. This article walks through installing Broadsea, defining cohorts, reading DQD, and acting on results.
ETL from a HIS/EHR/claims source to OMOP CDM takes 3-6 months from scratch. This article walks through the OHDSI standard pipeline: WhiteRabbit profiling, RabbitInAHat design, USAGI mapping, implementation with SQL/Perseus/dbt, and validation with DQD.
A deep dive into the seven most important tables in OMOP CDM 5.4 — schema, foreign keys, ETL conventions, common pitfalls (Measurement vs. Observation, Drug_Exposure vs. Drug_Era), and 10 popular RWE SQL patterns.
Vocabulary is the hardest but most important part of OMOP. This article explains Concepts, Standard vs. Source, Domain, Vocabulary, ConceptRelationship, and ConceptAncestor — plus the Athena download/lookup workflow for Vietnamese projects.
Which Common Data Model fits your organization? This article compares OMOP, FHIR, i2b2, PCORnet, and Sentinel across schema, vocabulary, governance, tooling, and use cases — and provides a decision tree to help you pick.
Real-World Evidence (RWE) is changing how the FDA, EMA, and other regulators make decisions. OMOP CDM is the data standard that lets you run a single study across hundreds of organizations at once. This article introduces OHDSI, CDM 5.4, and the Vietnam context.