Scientific Computing and Data / Mount Sinai Data Warehouse / Training, Tutorials, and Documentation
Understanding Electronic Health Record (EHR) Data
Principal Data Architect Timothy Quinn, PhD, has developed informative presentations on OMOP Vocabulary Tables and Electronic Health Record (EHR) Data in MSDW:
- March 26, 2025 – “Leveraging Electronic Health Records for Data Analysis and Reporting” Presentation Recording
- March 26, 2025 – “Leveraging Electronic Health Records for Data Analysis and Reporting” PowerPoint Slide Deck
- November 29, 2022 – “Terminology Mappings for MSDW OMOP” PowerPoint Slide Deck
- November 2, 2022 – “OMOP Vocabulary Tables Overview” PowerPoint Slide Deck
- June 16, 2022 – “Understanding EHR Data in MSDW” PowerPoint Slide Deck
- June 16, 2022 – “Understanding EHR Data in MSDW” Presentation Recording
Mount Sinai’s Epic electronic health record (EHR) system constitutes the primary data source for the Mount Sinai Data Warehouse. Data are also loaded from other ancillary systems.
AIR•MS Training
Fall 2025 Training Sessions
Session 1: Getting Started with AIR·MS: Health Data Fundamentals
- Tuesday September 30 (10:00 am – 11:00 am) | Hybrid In-Person & Zoom
- RECORDING NOW AVAILABLE – Session 1: Getting Started with AIR·MS: Health Data Fundamentals
- SLIDES NOW AVAILABLE HERE: (PART 1) (PART 2)
- PLEASE NOTE: THE MATERIAL FOR AIR·MS TRAINING SESSION 1 IS HERE.
You will need to have prior access to Minerva and AIR·MS OMOP De-ID dataset to participate in certain areas of this training. If you don’t have yet, you can follow these steps (NB: to access SailPoint you will need to be connected to the Mount Sinai network either by being onsite or by using VPN):
- Check that you have an ISMMS (School Network) Account. If you don’t, you can request it on SailPoint by selecting “School Network Account”
- If you haven’t yet, request a Minerva Account filling out this form. Please note that if you are not a PI, your PI should provide approval via email
- Request access to AIR·MS OMOP De-ID dataset via SailPoint by selecting “AIR.MS Production MSDW OMOP De-ID (MSSM)”. A detailed how to guide can be found here.
More details of how to gain access can be found here: AIR‧MS: Getting Started | Scientific Computing and Data
Session 2: From ChatAI to AIR·MS: Leveraging Large Language Models
- Tuesday October 7 (10:00 am – 11:00 am) | Hybrid In-Person & Zoom
- RECORDING NOW AVAILABLE – Session 2: From ChatAI to AIR·MS: Leveraging Large Language Models
- SLIDES NOW AVAILABLE HERE.
- PLEASE NOTE: THE MATERIAL FOR AIR·MS TRAINING SESSION 2 IS HERE. The direct link to the Jupyter notebook is HERE.
Session 3: Advanced AIR·MS: Multimodal Data
- Tuesday October 21 (10:00 am – 11:00 am) | Hybrid In-Person & Zoom
- RECORDING NOW AVAILABLE – Session 3: Multimodal Data
- SLIDES NOW AVAILABLE HERE.
Spring 2025 Session: slides available here.
Application Training
*Please note: to watch training videos off-campus users must be on VPN.
- De-identified Digital Pathology Training Session
- Epic Research Training
- Leaf/ATLAS Application Training
- March 5, 2025 – PowerPoint Slide Deck
- March 5, 2025 – Video Recording
- October 10, 2024 – PowerPoint Slide Deck
- October 10, 2024 – Video Recording
- January 17, 2024 – PowerPoint Slide Deck
- January 17, 2024 – Video Recording
- October 11, 2023 – PowerPoint Slide Deck
- October 11, 2023 – Video Recording
- February 23, 2023 – PowerPoint Slide Deck
- February 23, 2023 – Video Recording
- October 12, 2022 – PowerPoint Slide Deck
- May 4, 2022 – PowerPoint Slide Deck
- November 3, 2021 – PowerPoint Slide Deck
- November 3, 2021 – Video Recording
Tutorials
Each tool has a specific set of features and functions. Check out these tutorials for our software tools to assist you:
Documentation
Presentations
For MSDW-related presentation recordings and materials, see Presentations.
Reports
For publications, user reports, annual reports, and surveys, see Annual Reports and User Surveys.
Still having trouble? Submit a ticket and we will respond quickly.
We are supported by grant UL1TR004419 from the National Center for Advancing Translational Sciences, National Institutes of Health.
