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The Real-World Data Workshop

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.

Who Should Apply? What will you learn?

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.

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
Tools Used: ATLAS, OMOP, CDM, standardized vocabularies, CohortDiagnostics, R

Course 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.

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

Enrollment Details

Enrollment

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