Introducing the course
OHDSI & OMOP CDM is a comprehensive course on the world's largest observational health data analytics ecosystem.
Why OHDSI?
Medical data at each hospital and health system is stored in different formats — making multicenter research nearly impossible. OHDSI (pronounced: "Odyssey") solves this problem by normalizing data into the OMOP Common Data Model and providing a unified set of analytics tools.
What will you learn?
Hệ sinh thái OHDSI
├── Standardized Vocabularies (Athena)
├── ETL Tools
│ ├── WhiteRabbit — Khảo sát dữ liệu nguồn
│ ├── Rabbit-in-a-Hat — Thiết kế ETL mapping
│ └── Usagi — Mapping mã nguồn → Standard Concepts
├── OMOP CDM Database (PostgreSQL)
├── WebAPI — Backend REST API
├── ATLAS — Web-based Analytics Platform
│ ├── Concept Sets & Cohort Definitions
│ ├── Characterization & Incidence Rates
│ ├── Population-Level Estimation
│ └── Patient-Level Prediction
├── Data Quality
│ ├── ACHILLES — Data Profiling
│ └── Data Quality Dashboard — 1,500+ Quality Checks
└── HADES — R Packages cho Observational Research
Prerequisites
- Basic SQL (SELECT, JOIN, GROUP BY)
- Basic understanding of databases (PostgreSQL preferred)
- Docker basics (docker run, docker-compose)
- Basic R (for HADES section) — not required
- Does not require in-depth medical knowledge