Clinical Data Science

Renown OMOP-CDM 

CDS maintains a de-identified database containing clinical data from Renown Health’s Epic electronic health record, transformed into the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM).

Data requests

Requests for OMOP-CDM data can be submitted through the UNR Med Service Catalog:

Service Catalog - Clinical Informatics

Access restrictions

OMOP-CDM access is limited to UNR Med faculty and students with a valid NetID.

Although the OMOP-CDM is classified by the IRB as Not Human Subjects Research, researchers must still obtain IRB review for any requests involving patient-level data.

A students smiles while working on her laptop with other students nearby

Data tiers

Tier 1
Aggregated data

No IRB approval required; suitable for feasibility or exploratory studies.

Tier 2
Patient line-item data

Requires an IRB request for a Determination of Human Subjects Research. Before submitting your data request:

  1. Complete the OMOP-CDM subproject protocol
  2. Complete the research data use agreement
  3. Upload both documents with your data request application.

Please note: HIPAA and CITI research ethics training must be completed prior to receiving access to tier 2 data.

Tier 3
Patient identifiable data

Not available. The OMOP-CDM contains no personally identifiable information, and CDS does not provide direct access to live Epic data.

Data storage and access

OMOP-CDM data can be securely analyzed through UNR Med’s protected remote desktop environment. This allows researchers to work directly with the data without downloading it to personal computers. Results and outputs from approved analyses are shared with users through a secure UNR Med platform.

Our team

Clinical Data Science
Edwin Ahumada
Edwin Ahumada
Lead, Data Manager
(775) 682-5608
8627
Clinical Data Science
Jonathan Chastain
Jonathan Chastain, D.O.
Assistant Professor, Medicine/Clinical Informaticist, Medicaid Partnership
8627

Future plans

CDS will continue expanding its available datasets and analytical resources to enhance support for student and faculty research using large clinical data repositories.