Syllabus: OHDSI Train-the-Trainer (Core Sessions and Optional Modules)
This master syllabus outlines the required readings, tools, and assignments for the OHDSI Train-the-Trainer program: a required core (environment setup, then Days 1 to 4), optional sessions on treatment pathways (Day 5) and HADES (Day 6, taught as Part 1 and Part 2), with every session a half day, and optional advanced modules for continued professional development.
The program bridges Epic Clarity experience with OMOP/OHDSI skills through both GUI-based (Atlas, Athena) and SQL-based (Databricks, DBeaver) learning.
A) Session Syllabus (Days 1 to 4 required; Days 5 and 6 optional)
Tip: Chapters refer to the Book of OHDSI.
For broader context on data sources and study design, see the RWD Guide.
| Week / Day | Focus | Primary Readings / Viewings | Tools & Docs | Homework / Follow-up |
|---|---|---|---|---|
| Day 0 – Environment Setup | Verify access and installations | OHDSI.org – Who We Are · OHDSI Forum “Introduce Yourself” | Environment Checklist Template · ATLAS login · SQL client setup (Databricks / DBeaver) | Complete environment checklist · Test CDM connection and ATLAS login |
| Day 1 – OMOP CDM & Athena Vocabulary Exploration | Understand CDM structure and vocabularies | Book of OHDSI Ch. 4 The Common Data Model (§ 4.1 Design Principles · 4.2 Data Model Conventions · 4.3 CDM Standardized Tables); Ch. 5 Standardized Vocabularies (§ 5.1 Why Vocabularies, and Why Standardizing · 5.2 Concepts · 5.3 Relationships · 5.4 Hierarchy) | Athena Browser · Example CDM entity–relationship diagram (ERD) | Identify standard and non-standard concepts in Athena · Document mappings (Maps to, Is a) and the hierarchy shown in concept_ancestor |
| Day 2 – Concept Sets in Atlas & Introduction to Data Quality Concepts (with SQL Validation) | Build concept sets in Atlas and validate them using SQL tools | Book of OHDSI Ch. 15 Data Quality; Ch. 10 § 10.3 Concept Sets; Ch. 5 § 5.2.8 Classification Concepts | Atlas Concept Sets · SQL Clients (Databricks / DBeaver) · OMOP SQL Examples | Export Atlas SQL for concept sets · Run and validate logic in Databricks/DBeaver · Reflect on vocabulary mapping and data quality concepts |
| Day 3 – Cohort Definition & Characterization with ATLAS (SQL Exploration) | Design and characterize cohorts; explore cohort SQL | Book of OHDSI Ch. 10 Defining Cohorts; Ch. 11 Characterization (§ 11.2 and § 11.7) | ATLAS Cohort Editor · Characterization Module · SQL Clients | Export cohort SQL from Atlas · Annotate key joins and logic in SQL client · Compare table usage across OMOP domains |
| Day 4 – Data Extraction & SQL Validation (site specific) | Retrieve OMOP data for analysis and cross-check results | Book of OHDSI Ch. 9 SQL and R | ATLAS SQL export · Databricks / DBeaver · OMOP SQL Examples | Re-run the extraction SQL manually in your SQL client · Validate counts and compare results |
| Day 5 – Treatment Pathway Analysis (Optional) | Sequence treatments and visualize pathways | Book of OHDSI Ch. 11 Characterization (§ 11.3 Treatment Pathways and § 11.9 Cohort Pathways in ATLAS) | ATLAS Cohort Pathways | Generate and interpret pathway plots · Summarize one analytical insight |
| Day 6, Part 1 – HADES: Cohort Diagnostics and Feature Extraction (Optional) | Set up the R environment, run diagnostics on a cohort, build baseline covariates | Book of OHDSI Ch. 8 OHDSI Analytics Tools; Ch. 11 § 11.8 Cohort Characterization in R | HADES R Packages · CohortGenerator · CohortDiagnostics · FeatureExtraction | Run diagnostics on your Day 3 cohort and note what each output shows |
| Day 6, Part 2 – HADES: Patient-Level Prediction (Optional) | State a prediction problem, train a model, read discrimination and calibration | Book of OHDSI Ch. 13 Patient-Level Prediction | PatientLevelPrediction · Colab notebook (synthetic data) | Run the prediction workflow or the notebook and report the AUC and calibration |
B) Optional / Advanced Modules (After the Sessions)
These modules are not part of the session sequence and can be assigned for continued self-study.
| Module # | Topic | Primary Readings | Key Tools / Docs | Optional Context / Use Case |
|---|---|---|---|---|
| 7. Team Building & Project Management | Cross-functional teamwork in OHDSI | Book of OHDSI Ch. 1 (The OHDSI Community) & Ch. 20 (OHDSI Network Research) | GitHub best practices · Agile boards | Managing multi-site collaborations |
| 8. Advanced Topics | ML, NLP, FHIR, unstructured data | Book of OHDSI Ch. 8 (OHDSI Analytics Tools) | NOTE_NLP · FHIR mapping guides | Extending OMOP to AI and interoperability |
| 9. Train-the-Trainer Skills | Adult learning and facilitation | Adult learning primers · Presentation skills | EXCELERATE TtT materials | Designing your own institutional training program |
| 10. Capstone Project | End-to-end practice study | Revisit Ch. 12, 13, 19 | ATLAS export → SQL / R | Present a mini reproducible study |
| 11. Wrap-Up & Next Steps | Sustaining engagement | Book of OHDSI Ch. 1 (The OHDSI Community) & Ch. 2 (Where to Begin) | OHDSI Workgroups Directory | Join or lead community workgroups |
| 12. Refresher (3-Month Post-Course) | Review and updates | Book of OHDSI Ch. 19 (Study Steps) | Latest OHDSI release notes | Continuing learning & updates |
C) Persona-Based Study Paths (Quick Reference)
| Persona | Core Modules | Key Tools | Suggested Extras |
|---|---|---|---|
| Vocabulary / Terminology Experts | Days 1–3 | Athena · Atlas Concept Sets · SQL Clients (Databricks/DBeaver) | White Rabbit / Rabbit-in-a-Hat |
| Statisticians / Data Analysts | Days 3–6 (Days 5 and 6 optional) | ATLAS Cohort Pathways · HADES · SQL review of outputs | RWD Guide (bias/confounding) |
| Data Engineers (SQL-first) | Days 2–4 | Databricks · DBeaver · DatabaseConnector | Build reproducible pipelines in GitHub |
| Clinicians / Analysts | Days 1–3 | Athena · Atlas Cohort Editor | Explore cohort outputs and characterization summaries |
D) Key Supplemental Resources
| Resource | Purpose / Description |
|---|---|
| The ALS Use Case | The running example for every session: motor neuron disease, ALS medications, and the ALSFRS-R, with the concepts and lookup queries. |
| Environment Checklist Template | Validate all required system access before Day 1. |
| OMOP SQL Examples | Common SQL patterns for exploring concepts, ancestors, and cohort logic in Databricks or DBeaver. |
| SQL Validation Mini Lab | Step-by-step guide to export Atlas SQL, run validation queries, and compare outputs. |
| Book of OHDSI | Core text for OMOP CDM and OHDSI methods. |
| RWD Guide | Companion text for understanding bias, confounding, and data quality. |
E) How to Use
- Before class: Read the assigned Book of OHDSI chapters and open the listed tools.
- During class: Use both Atlas/Athena and your SQL client for guided exercises.
- After class: Complete the homework for the session and the optional SQL validation tasks.
- As a trainer: Bookmark these core references and update your repo with local connection instructions.
This syllabus supports the OHDSI Train-the-Trainer program and connects the graphical and SQL-based workflows. Chapter and section numbers were checked against the online Book of OHDSI on 1 October 2026.