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INFORMATION FOR

OMOP Common Data Model

Using YU-YNHHS HPC environment and OMOP Limited Dataset for Research

Yale New Haven Health System (YNHHS), in collaboration with investigators from Yale School of Medicine, have deployed a High-Performance Computing Cluster and data science workbench. This Computational Health Platform (CHP) includes a data repository and secure computational environment with the YNHHS electronic health records, other phenotypic data, and genotypic data. Data from clinical images can also be merged when approved.

To use CHP effectively, your team will require someone with advanced data science skills, including proficiency using relational databases, python, and SQL. CHP includes a YNHHS instance of the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). The OMOP CDM is a standardized set of tables (e.g., encounters, patients, providers, diagnoses, drugs, measurements and procedures), and is an internationally adopted standard.

Instructions

YNHHHS OMOP is available for self-service, and additional data can be merged with your OMOP data set upon IRB approval, including MRNs, images, and text data from notes and reports. To use OMOP data for a research project, you must have a program ready to extract your analysis data set.

The following options are available:

  1. Submit an existing data preparation program: Prepare or reuse existing* OMOP-based queries to define the cohort and data set as part of your normal Helix Request using test environments. SparkSQL will be most efficient.
  2. Create a new data preparation program in CHP. For this option, you must Submit a Preparatory to Research Request and access the complete OMOP Limited Data Set for 90 days to develop your data preparation program.
  3. Work with a JDAT analyst to develop your data set on a fee-for-service basis to prepare a data set.

When you are ready to start your research project, submit an IRB application that describes the analysis data set you have prepared. If you need protected health information outside of OMOP for your project, including MRNs, images, or notes, include this in your list of data elements.

Once the IRB is approved, submit your data request and attach the data extraction program.

*Observational Health Data Sciences and Informatics (OHDSI) collaborative has adopted OMOP CDM and maintains an open-source library of analytical tools for research and performance measurement using the OMOP CDM. Standardized structured query language (SQL) queries are shared in a common open-source repository, and detailed data documentation is freely available online.