Real-World Data Summer Workshop | OUHSC Office of the Vice President for Research

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From Health Data to Evidence:

A Hands-On Introduction to OMOP, OHDSI, and Real-World Evidence

June 1–5, 2026 | 9:00 AM–5:00 PM Daily | OU Health Campus (Oklahoma City)

About the Course

The OU Real-World Data (RWD) Summer Workshop is an intensive, week-long, project-based training program designed for data scientists and clinicians who want to learn how to use real-world health data (e.g., EHR data) to generate reliable clinical evidence.

Participants will work with the OMOP Common Data Model, explore OHDSI open-science tools, and form multidisciplinary teams to design and execute an end-to-end observational study from formulating a research question to presenting results using state-of-the-art diagnostics and reproducible workflows.

Whether you are new to healthcare data or new to analytics, this course builds the bridge between domains and creates shared expertise across disciplines.

Live Accordion

Who Should Apply?

Data science students or trainees or professionals who want to learn:

How clinical data are generated and structured
How to interpret EHR and claims data
How to use OMOP-standardized vocabularies and OHDSI tools (ATLAS, CohortDiagnostics, R packages)
How to convert clinical questions into analytic designs

Clinicians or health professionals who want to learn:

Foundations of real-world evidence generation
Study design for comparative effectiveness & safety
How to collaborate with data science partners
How to evaluate reliability, bias, and diagnostics in EHR-based studies

No prior experience with RWD or data science required. Clinical or translational research experience preferred.
Teams will intentionally mix complementary expertise.

What Will You Learn?

Across five days of lectures, demonstrations, and hands-on exercises, participants will:

Day 1: Foundations

Introduction to OHDSI & observational network research
Understanding administrative claims & EHR datasets
Mapping a patient journey
OMOP CDM structure & standardized vocabularies
ETL concepts & data quality assessment

Day 2: Study Design

Characterization, cohort design, causal estimation, prediction
OHDSI standard study questions
Building fitness-for-use awareness of data sources

Day 3: Phenotyping

Concept sets, cohort construction, phenotype evaluation
Using CohortDiagnostics, PheValuator, and KEEPER
Team exercise: Build your own cohorts

Day 4: Study Implementation

Constructing study specifications
Using STRATÉGUS and OHDSI R packages
Executing analyses reproducibly

Day 5: Interpretation & Communication

Understanding diagnostics and uncertainty
Reviewing results in R Shiny

Team lightning presentations

Course Format & Schedule

Course Format

Daily schedule: 8:00 AM–5:00 PM (lunch included)
Format: Morning lectures + afternoon hands-on labs

Location

OU Health Campus, Oklahoma City
Exact building/room information will be provided after registration.

Tools and Objectives

Capstone: Teams complete a full RWD observational study
Tools used: ATLAS, OMOP CDM, standardized vocabularies, CohortDiagnostics, R

Enrollment Details

Enrollment

Total capacity: ~20 participants
- 10 clinician-scientists
- 10 data science students
Applications open: Spring 2026
Fees: TBD (scholarships may be available)

Why Attend?

Why Attend?

Learn the internationally adopted OMOP data standard
Gain hands-on experience with OHDSI analytics pipelines
Work in interdisciplinary teams
Build a complete study you can include in your portfolio

Join the global OHDSI open-science community

Contact

This will be updated with a REDCap application link, but for updates or to join the interest list:
📧 bbmc@ou.edu