Feb 9, 2023 | Uncategorized
An MSDW (Mount Sinai Data Warehouse) Town Hall will be hosted on Tuesday, May 2, at 11:00 am.
The Town Hall will focus on:
- Recent accomplishments and future vision
- 2022 MSDW usage
- 2022 Leaf and ATLAS usage
- 2022 MSDW user survey results
- 2023 MSDW roadmap
In Person: Icahn School of Medicine building (1425 Madison Ave) Goldwurm Auditorium
Remote: Webinar via Zoom. Register here: https://mssm.zoom.us/webinar/register/WN_JAhrWmAqTjSBbol5sRn0FA
The Mount Sinai Data Warehouse (MSDW) collects clinical and operational data for use in clinical and translational research, as well as quality and improvement initiatives. The MSDW provides researchers access to data on patients in the Mount Sinai Health System:
- Over 11 million patient records
- Over 87 million patient encounters
The majority of the data collected by the MSDW comes from the Epic Clarity and Caboodle databases, as Epic is the primary electronic health record (EHR) across the Mount Sinai Health System (MSHS).
About MSDW
MSDW Data
Submit an MSDW Ticket
Jul 27, 2022 | Uncategorized
There will be scheduled maintenance to the Mount Sinai Data Warehouse (MSDW) PROD server on Wednesday, August 10, from 5:00 to 7:00 PM. This maintenance will include a reboot to install security patches and quality updates for the server.
This server reboot will result in downtime that will impact data availability for the Leaf and ATLAS query tools. Please plan your work ahead of time and log out of the application during maintenance.
For more information on Leaf or ATLAS, click here. You may contact us with questions by submitting a ticket. Thank you.
May 13, 2022 | Uncategorized
Scientific Computing and Data is hosting an MSDW Town Hall on Friday, May 27, from 12:00-12:30 pm.
The Town Hall will focus on:
- 2021 MSDW usage
- 2021 MSDW user survey results
- Recent accomplishments and future vision
The MSDW Town Hall will be hosted in Zoom. Remote Zoom link is provided following registration.
Click here to register for the MSDW Town Hall.
Apr 5, 2022 | Uncategorized
How to Utilize Real-World Data to Support Your Research and Clinical Trials
You are invited to attend five upcoming training webinars to learn how to utilize the TriNetX platform to conduct research and support clinical trials utilizing real-world data. These sessions include:
- TriNetX 401 – Part 1: Advanced Analytics – Analyze Outcomes, Compare Outcomes, and Compare Cohorts
- TriNetX 401 – Part 2: Advanced Analytics – Treatment Pathways and Incidence and Prevalence
- TriNetX 201: Best Practices in Querying Oncology
- TriNetX 101: Network(s) Overview, Query Building and Patient Counts
- TriNetX 102: Basic Analytics for Clinical Trial Optimization Insights
See below for descriptions of each session and links to register. You can also watch on-demand training in the TriNetX Platform Help Center.
TriNetX 401 – Part 1
Advanced Analytics – Analyze Outcomes, Compare Outcomes, and Compare Cohorts.
Learn how to generate real-world evidence using Analyze Outcomes, Compare Outcomes, and Compare Cohorts.
Date: Thursday, April 14, 2022
Time: 8:00 AM ET
Duration: 45 Minutes
Register Now
TriNetX 401 – Part 2
Advanced Analytics – Treatment Pathways and Incidence and Prevalence.
Learn how to generate real-world evidence using Treatment Pathways and Incidence and Prevalence.
Date: Thursday, April 14, 2022
Time: 10:00 AM ET
Duration: 45 Minutes
Register Now
TriNetX 201
Best Practices in Querying Oncology
Learn query design strategies that can improve your ability to effectively query oncology data for research and more.
Date: Thursday, April 21, 2022
Time: 12:00 PM ET
Duration: 45 Minutes
Register Now
TriNetX 101
Network(s) Overview, Query Building and Patient Counts
Learn about the basic functionality of the TriNetX platform as well as how to build and run a query for a clinical study.
Date: Thursday, April 21, 2022
Time: 2:00 PM ET
Duration: 45 Minutes
Register Now
TriNetX 102
Basic Analytics for Clinical Trial Optimization Insights
Learn how to gain valuable insights through results generated using analytic features: Analyze Criteria, Explore Cohort, Healthcare Organizations (HCOs), Rate of Arrival, and Summary Statistics.
Date: Thursday, April 21, 2022
Time: 4:00 PM ET
Duration: 45 Minutes
Register Now
Use Cases:
The TriNetX platform helps investigators at healthcare organizations and life sciences companies with:
Protocol Design and Feasibility
- Determine if a sufficient population matches a protocol
- Investigate attributes and comorbidities of a cohort
- Analyze inclusion/exclusion criteria and the impact of changes
Site Selection for Patient Recruitment
- Locate study sites based upon the availability of eligible patients matching a protocol
- Predict the arrival rate of newly eligible patients
- Engage the right contact within the clinical trials office at study sites
Generation of Real-World Evidence
- Explore and compare cohorts
- Compare outcomes of interest
- Characterize drug efficacy and burden of illness
Collaboration with Peers
- Participate in multi-site research across organizations
- Pursue grant-based research funding
- Strengthen relationships between healthcare organizations and sponsors
ABOUT TRINETX
TriNetX is a global network of healthcare organizations and life sciences companies driving real-world research to accelerate the development of new therapies. Through its self-service, HIPAA, GDPR, and LGPD-compliant platform of federated EHR, datasets, and consulting partnerships, TriNetX puts the power of real-world data into the hands of its worldwide community to improve protocol design, streamline trial operations, and enrich real-world evidence generation. For more information, visit TriNetX at www.trinetx.com or follow @TriNetX on Twitter.
QUESTIONS OR COMMENTS?
Contact collaboration@trinetx.com
Dec 13, 2021 | Uncategorized
To provide the Mount Sinai Community with the very best data and resources to query the data, the Scientific Computing and Data team has been implementing improved infrastructure in the Mount Sinai Data Warehouse. In 2021, we debuted “MSDW2,” based on the OMOP Common Data Model, containing Epic data from throughout the Mount Sinai Health System, and unveiled two self-service query tools for defining and generating patient cohorts: Leaf and ATLAS.
Changes for Cohort Query Tool
While CQT has served our research community, CQT relies on infrastructure that is no longer updated with refreshed data. Researchers deserve access to updated, organized data, which is now available in MSDW2 through Leaf and ATLAS. This is why, effective December 20, 2021, the Cohort Query Tool will be decommissioned from use and will no longer be accessible.
What about my CQT work?
We understand that you may have saved cohorts or patient lists in CQT. With changes to the database and the query tools, there is no direct, easy way to transfer user data into a new tool application. We recommend the following options:
- Data Archive: Between now and December 20, run cohorts as patient lists. Once a patient list is generated, save the patient list as a local file to your computer. To continue using these patients in data queries, submit a custom data request through MSDW and work with one of our MSDW data analysts to continue your research. Click here to see more about MSDW custom queries.
- Leaf & ATLAS: Consider utilizing these query tools to generate cohorts or patient lists. A video training on how to use these tools has been recorded and added to the MSDW website. Click here for the recorded training, and click here for PowerPoint slides.
Final Notes
Monday, December 20, 2021 will be the final day Cohort Query Tool will be available. We ask that you save or transfer any work still in CQT before that date. Once CQT is decommissioned, saved cohorts will be deleted. We encourage all users to explore the new tools Leaf and ATLAS to query refreshed Epic patient data and, as always, to please submit a ticket with any questions or difficulties.
