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OptumLabs Core (OLC)

What is Optum Labs?

Optum Labs is a collaborative research and innovation center with its core linked data assets in the Optum Labs Data Warehouse (OLDW). University of Maryland Baltimore joined the Optum Labs collaborative as a partner in 2024. The University of Maryland Institute for Health Computing (UM-IHC) leads this important relationship.


Optum Labs Data Warehouse (OLDW) is a comprehensive, nationwide real-world database that contains de-identified, longitudinal health information on enrollees and patients, representing a mixture of ages and geographical regions across the United States. The claims data in OLDW includes medical and pharmacy claims, laboratory results and enrollment records for over 200M commercial and Medicare Advantage enrollees. The electronic health record (EHR)-derived data in OLDW includes a subset of EHR data sourced from different health systems and practices across the United States that has been normalized and standardized into a single database. Additional data linkages may be feasible, as long as there is no risk of data re-identification.

All data are kept in a secure environment and in accordance with the Health Insurance Portability and Accountability Act (HIPAA) regulations; no personally identifiable information is shared.

Why Optum Labs?

In addition to gaining access to one of the largest linked patient databases available in the U.S., researchers are able to leverage a network of world-class thought leaders from across Optum Labs partners. OLDW data has been used for a wide range of impactful research studies.

How to conduct a research project using Optum Labs data?

Services and Costs

All projects are managed by an assigned project coordinator with expertise supporting research activities using OLDW and its linked data assets. Frequently requested services include:

  • Advising on the appropriate data assets to use for a given research question
  • Supporting grant submissions
  • Assisting investigators in obtaining data
  • Operationalizing variable definitions
  • Cleaning and managing the analytic dataset
  • Performing statistical analyses
  • Project management
  • Publication support
  • Providing input on statistical analysis: pharmacoepidemiology, epidemiology, comparative effectiveness and safety, health equity, causal inference, population health, and machine learning/artificial intelligence modeling methods

 

Next Steps

If you are interested in learning more about Optum Labs data or are ready to begin a project please complete the Project Consultation Form on the "Request Services" tab of this site.  Also, please feel free to reach out to  Rozalina G. McCoy, MD MS, or Lisa Pineles, MA to schedule an Optum Labs Introductory Meeting. 

Contacts

Name Role Phone Email Location
Rozalina G. McCoy, MD MS
Associate Professor
 
410 706 6652
 
rozalina.mccoy@som.umaryland.edu
 

 
Lisa Pineles
Project Manager
 
410 706 0063
 
lpineles@som.umaryland.edu