Mount Sinai Data Warehouse
Partnering with researchers and clinicians to effectively utilize Mount Sinai Health System data for translational and clinical research
Announcements
April, 2024 – Training: Leveraging Epic for Research – Tuesday, May 14, 2024 1 pm – 2 pm
This training will cover: an overview of Epic’s Research Module; Epic Research features and workflows; and upcoming features
Presented by: Joseph Kannry, MD, Lead Technical Informaticist, Professor of Medicine, Professor of Pathology, and Sharon Nirenberg, MD, Lead Physician Informaticist, Scientific Computing and Data, Icahn School of Medicine at Mount Sinai
Click here to register for the Zoom webinar.
March, 2024 – The Spring 2024 Mount Sinai Data Warehouse (MSDW) Town Hall will be held Wednesday, May 1, 3 pm- 4 pm. Click here to register for the Zoom webinar.
OMOP Query Tools
Leaf
A web-based query tool that creates patient cohorts from de-identified data using clinical and demographic criteria. Log in with your Mount Sinai credentials.
ATLAS
A web-based query tool that analyzes data standardized in the OMOP CDM format. Mount Sinai users must have a school account for access.
TriNetX
A web-based query tool that queries de-identified Epic data, including demographics, diagnoses, lab results and more. Request Access.
Data Sets
COVID-19 Data Sets
The de-identified COVID-19 data sets include all patients at a Mount Sinai facility who have been screened for or diagnosed with COVID.
Custom Data Request
The MSDW team will work with you to create a custom de-identified or PHI data set for your research or quality improvement project.
OMOP Data Marts
MSDW supports continually refreshed OMOP-formatted data marts of your research projects’ patient cohorts of interest.
Services
CTSA CD2H
CTSA National Center for Data to Health (CD2H) provides additional resources to the community.
Tools for OMOP
Open source software tools can be used with MSDW’s Observational Medical Outcomes Partnership (OMOP) Common Data Model.
Acknowledge Mount Sinai in Your Work
All publications must include the following language in the acknowledgments section: “This work was supported in part through the Mount Sinai Data Warehouse (MSDW) resources and staff expertise provided by Scientific Computing and Data at the Icahn School of Medicine at Mount Sinai.”
Supported by grant UL1TR004419 from the National Center for Advancing Translational Sciences, National Institutes of Health.