Updated: December 3rd, 2025
Overview
The Yale New Haven Hospital System (YNHHS) utilizes an electronic medical record (EMR) system provided by the Epic Corporation. This system digitizes all patient chart information, including medical history, allergies, current medications, laboratory and radiology results, and visit notes. Patients within the YNHHS network—which includes Greenwich Hospital, Bridgeport Hospital, Yale New Haven Hospital, Northeast Medical Group, and affiliated physicians—will have their EMR records maintained in the YNHHS Epic system 1,2.
YNHHS provides a wide range of medical services, including emergency care, primary care, and over 100 specialties such as oncology, cardiovascular care, and neurology 3. The YNHHS facts and figures section and annual reports indicate that over the past few years, there have been approximately 150 thousand inpatient visits, 3.5 to 4 million outpatient encounters, and 350 thousand emergency department visits annually 2,4,5.
Epic Cosmos combines inpatient and outpatient charts into unified, longitudinal patient records while removing duplicates that may arise from patients receiving care at multiple Cosmos organizations. The data provided to researchers adheres to HIPAA-defined limited data set standards 8. To enhance patient privacy protections, the de-identified dataset suppresses geographic information, consistently shifts patient dates, and conceals source organizations. Detailed information on individual data element transformation processes is available in the Cosmos Data Domain Encyclopedia and the Data Dictionary (also accessible through the Cosmos portal) 9,10.
The Research Informatics Office (RIO), operated by the Yale Biomedical Informatics and Computing (YBIC), hosts open office hours every Thursday for researchers using Epic. Contact Soundari Sureshanand to request the Zoom link 11.
The Joint Data Analytics Team (JDAT) offers customized reporting and data analysis from the Epic data system, specializing in research support. With a team of 60 informaticists and analysts, JDAT works closely with users to understand their data needs and efficiently retrieve information. JDAT supports projects such as cohort population counts, grant application statistics, retrospective reviews, custom data extracts, and report development 12.
Click here for directions on submitting a Helix research data request with JDAT, Yale’s customized data warehouse system. Learn more on the Yale Center for Clinical Investigation’s Epic Electronic Health Record SharePoint page, which is also accessible from their For Researchers & Research Professionals webpage 12–14.
The types of data collected in the EMR are continuously expanding. For example, researchers currently have access to the following data 8:
Patient Information: Limited demographic details such as age, sex, gender identity, race, ethnicity, location, patient status, and family history, social history elements like tobacco and substance use, birth control, social determinants of health, allergy information, and detailed birth history.
Visits and Encounters: Patient encounters and admissions including encounter type, classification, department and provider specialties, and visit reasons, as well as clinical notes from various medical documentation and patient experience data from MyChart usage and patient-reported outcomes.
Medical Data: Diagnoses, clinical and billed procedures, and vital signs such as blood pressure, pulse, temperature, respiratory rate, SpO2 levels, height, weight, BMI, and head circumference.
Lab and Genomics: Lab results such as component-specific results, susceptibility results, and reference ranges, in addition to genomic variant data like allelic state and chromosome details, and biosamples for genomic assays including blood, saliva, and urine samples.
Health Assessments: Information on cancer staging, immunizations, and eye exams, with details on stage group, immunization type, and visual acuity.
Specialty Data: Records data on hospital-acquired infections and various infection types, surgical procedures, transplant data for liver and kidney transplants, and health tracking data from wearable devices.
Research and Analytics: Geographic factors like RUCA and Social Vulnerability Index, risk scores for conditions such as cardiovascular disease and diabetes, and data from research studies detailing study type, enrollment, and partnered research contributions.
Miscellaneous: Encompasses peer group information on various types of hospitals, medication data including prescriptions and patient-reported medications, and additional lab results.
Gaining Access
Do I Qualify?
To get access to YNHHS Epic data, you need 15:
To either work for a Yale University-YNHHS (YU-YNHHS) Covered Entity (e.g., YNHHS or YSM), OR have a sponsor who can request access for you.
Someone with a YNHH account (either your manager or sponsor) to submit the “YNHHS Researcher Basic Access” request.
All YNHH/YSM faculty and licensed providers can submit and sponsor access requests.
Are you affiliated with YNHHS or Yale School of Medicine?
If yes: Your manager can request access for you.
If no: You’ll need to find a sponsor with a YNHH account to request access for you.
To check if your department is a YU-YNHHS Covered Entity, see the “List of Covered Departments” under “Administrative Functions” on the hippa.yale.edu Resource Documents and Guidance page 16.
Qualifying researchers can apply for RBA without needing Institutional Review Board (IRB) approval, granting them access to de-identified, summary count data. If researchers with RBA later obtain IRB approval, they can then request access to individual-level data relevant to their IRB-approved study 17.
Typical Timeline
The approval process is the most significant and variable source of time constraints. The time required for RBA request approvals can vary. Resetting passwords typically takes about 24 hours, while granting Learning Management System (LMS) access after network ID creation usually takes 48 hours. Reviewing and approving Epic UserWeb profiles may take a few days, but this duration can also vary.
Step-by-Step Guide
a: Manager or Sponsor Requests RBA on Your Behalf
Your YU-YNHHS Covered Entity manager or sponsor will complete the YNHHS Researcher Basic Access request on your behalf 15.
b: Complete Account Setup and Enrollment
After the request is approved, access will be provided to the RBA SharePoint site 18. Guides with further detailed steps are referenced in this SharePoint site. For technical support for external or offsite users, contact the YNHH Service Desk at 203-688-HELP (4357) or helpdesk@ynhh.org. It may be necessary to verify identity and account permissions when requested 19.
- Upon approval of the application, a welcome letter from YNHH will be sent containing the YNHH Network ID and a temporary password. Follow the instructions in the letter to reset the password 19.
The YNHH NetID also serves as the Epic username.
Enroll in Duo Multi-Factor Authentication through the Password Self Service Portal. Full details are available in the “YNHH Duo Enrollment” document on the RBA SharePoint 20.
Once these steps are completed, the MyApps Portal will be accessible. This secure platform provides access to Epic and the YNHH Virtual Desktop Infrastructure (VDI). Log in with the YNHH NetID and password to verify credentials. Full details are available in the “Accessing YNHH VDI & Epic (MyApps Portal)” document on the RBA SharePoint 21.
The minimum supported operating systems are Windows 10 and macOS Catalina. An OS upgrade is required if the device does not meet these requirements. An HTML5 web browser (e.g., Microsoft Edge, Google Chrome, Firefox) is also necessary.
This portal provides primary or alternative access to content depending on your role and work location. For guidance, view the “Accessing YNHH VDI & Epic” document on the RBA SharePoint.
- An Epic UserWeb profile needs to be created using the YNHH NetID. Remember that the YNHH NetID also serves as the Epic username 22.
Navigate to Epic UserWeb. If directed to the YNHH log-in portal (sts2.ynhh.org), proceed to the next step. If the Epic UserWeb sign-in page (signin.epic.com) appears, type “Yale New Haven Health System” in the “Find your Organization” search bar and select the appropriate option to continue.
Log into the YNHH portal (sts2.ynhh.org) using the YNHH User ID.
From the Epic UserWeb main page (userweb.epic.com), request an Epic UserWeb profile.
Complete the profile using credentials from the associated Epic organization. For instance, use the “@yale.edu” email for Yale University affiliates.
Follow any setup instructions or verification steps to finalize the account.
c: Training
All Epic users are required to complete the “Epic Research User Curriculum”, available on the YNHH Learning Management System 23,24.
Users of YNHHS Epic data analytic tools, such as SlicerDicer, are expected to be proficient and aware of the tools’ limitations. The following training courses are recommended for researchers intending to use these tools for Epic Reporting tasks:
“Epic Reporting Fundamentals” - available on YNHH Learning Management System (LMS) 18,25
“Epic SlicerDicer Fundamentals” - available on the YNHH LMS 18,25
For those seeking additional resources to learn how to use Epic’s SlicerDicer tool, it is recommended to review the “SlicerDicer” article available in Galaxy or to access one of the weLearning modules created by the Epic community, which can be found here 26,27.
Additional courses offered by JDAT and YNHH are also available for exploration:
SlicerDicer-related courses (“Available SlicerDicer Models”, “SlicerDicer Quick Start Guide”, and “SlicerDicer Quick Epic Demo”) - available on the JDAT Analytics Portal 28
“Epic SlicerDicer E-Learning Course” - available on the YNHH LMS 17,29
For some, a manager or supervisor might assign training modules accessible through the YNHH LMS, the JDAT Analytics Portal, or Epic University. Further information on training expectations can be found in the “DTS Epic Training Course Catalog”. For example, the “Research” section lists mandatory trainings for non-clinical research users. This document is accessible from two locations:
The YNHH LMS: Open the “Epic Course Catalog” embedded document and select the “View our Epic Course Catalog” hyperlink 30.
The YNHH IT SharePoint (itstraining.ynhh.org): Click the blue “Training & Support Material” drop-down menu and select “Epic Training”. The catalog is linked in the right “Quick Links” sidebar 23,31,32.
It may be necessary to review role-based training requirements, which can be found in the “Roles and Course Spreadsheet” that is also accessible from both webpages.
Users who have not accessed YNHHS Epic for a year or longer must complete role-specific training before regaining access 32.
Accessing Requested JDAT Research Data
As mentioned above, JDAT provides customized reporting and data analysis from the Epic data system for research projects. Once the approved request is ready, accessing the data may be necessary from the YNHH OneDrive. This can be done by using the Office 365 application installed on the YNHHS VDI. Full details are available in the “Accessing YNHH OneDrive” document on the RBA SharePoint 33.
Publications Expectations
Epic provides data users with a checklist for preparing data for publications, emphasized in the user agreement, “Cosmos Rules of the Road”. The full instructions and expectations can be found in the Galaxy “Cosmos Publication Checklist” article and the “Cosmos Rules of the Road”, which outlines some of the Data Use Agreement terms 34,35.
When transferring results off the VDI or sharing SlicerDicer graphs, it is imperative to follow Epic’s process to prevent the exportation of line-level data. No counts less than 10 can be individually noted (report as <11).
Review the Centers for Medicare and Medicaid Services (CMS) Cell Size Suppression Policy outlined by the Research Data Assistance Center (ResDAC) for examples of how to appropriately suppress low counts 36.
Researchers are obligated to provide a list of citations for any publications or references to their research conducted using Cosmos. This list must be submitted to the Governing Council on a semi-annual basis 35.
Included Tools and Applications
Researchers seeking access to YNHHS Epic data will need a Researcher Basic Access (RBA) account. Qualifying researchers will receive a YNHH NetID and Duo Access, which provides access to 15:
| Virtual Desktop Infrastructure (VDI) |
Provides remote access to a YNHHS secure device without requiring the YNHHS VPN. Each device is suited with software such as SQL Server Management Studio, R, Stata, SAS, Office365, and Epic, and is where researchers can access Kamino/CHP. This set up can handling small-to-medium sized data, as well as accessing Epic charts, SlicerDicer, and the Computational Health Platform (CHP) 37. |
|
| Epic SlicerDicer |
Access de-identified summary count data representing the entire YNHHS patient dataset for data exploration, analytics, and reporting. While IRB applications are not required for accessing this de-identified data, training is strongly recommended. Refer to the “Step-by-Step Guide” Part C: Training section for more details 12,17. Researchers can also request access to the Epic Cosmos system, which provides de-identified summary count data for all participating Epic systems outside of YNHHS. Learn more on our Epic Cosmos information webpage. |
|
| Computational Health Platform (CHP) |
A secure, compliant, and collaborative high-performance computing cluster specifically designed for clinical data analysis. It is suitable for AI research and development and is well suited for analyzing large volumes of data in various forms (e.g., images, text, structured) 37. This tool requires advanced data science skills with relational databases, Python, and SQL. Additional details can be found here: OMOP Common Data Model 38. |
|
| Microsoft Office 365 |
Access Microsoft applications integrated within the YNHHS organization through the VDI. As noted above, this is how you can retrieve JDAT-requested data 33. |
Valuable Links
YNHH Learning Management System (LMS): Center Point Systems is where you can sign up for YNHH-created in-person or online training courses 30.
MyAPPs: Find the portal to access the VDI through Citrix Workspace. Ensure your YNHH Duo is active for authentication and use your YU/YNHHS VPN if accessing from outside the Yale University or YNHHS network 21.
JDAT RBA SharePoint: Find details about what RBA provides, along with supporting documents such as how-to guides for accessing the VDI, enrolling in Duo, links to training portals, and user guides for researchers 18.
YNHH IT SharePoint: Find IT support materials, guides for navigating the Epic VDI software, notices of upcoming training events and system updates, and training requirements for researchers using Epic data. To access the Epic-specific documentation, click the blue “Training & Support Material” drop-down menu and select “Epic Training” to access the “Epic Training Portal” 23.
JDAT Analytics Portal: Submit a Helix request to have JDAT compile your research data. Additionally, access JDAT-created training for tools like Epic’s SlicerDicer 13.
Epic UserWeb: Find Epic training materials, documentation, community discussions, support resources, updates, customization options, and access to your Epic profile 39.
Epic University: A subdomain of the UserWeb, find training opportunities and access to coursework necessary to obtain certificates, such as the Super User Badge, with courses organized by the Epic team 40. Learn more about advanced training options on our Epic Cosmos information webpage.
Galaxy: A subdomain of the UserWeb, find comprehensive resource that provides documentation, announcements, best practices, and implementation guides related to the Epic dataset 41.
Publications
This section presents a selection of PubMed articles that utilize the dataset and are authored by individuals affiliated with the Yale School of Public Health. These articles are provided to inspire researchers and students to use the data in their own work.
-
Use of Electronic Health Records to Characterize Patients with Uncontrolled Hypertension in Two Large Health System Networks.
Yuan Lu, Ellen C Keeley, Eric Barrette, Rhonda M Cooper-DeHoff, Sanket S Dhruva, Jenny Gaffney, Ginger Gamble, Bonnie Handke, Chenxi Huang, Harlan M Krumholz, Caitrin W McDonough Rowe, Wade Schulz, Kathryn Shaw, Myra Smith, Jennifer Woodard, Patrick Young, Keondae Ervin, Joseph S Ross
medRxiv : the preprint server for health sciences 2023 Jul 28 pii: 2023.07.26.23293225. doi: 10.1101/2023.07.26.23293225
PMID: 37546792 -
A Multicenter Evaluation of the Impact of Therapies on Deep Learning-Based Electrocardiographic Hypertrophic Cardiomyopathy Markers.
Lovedeep S Dhingra, Veer Sangha, Arya Aminorroaya, Robyn Bryde, Andrew Gaballa, Adel H Ali, Nandini Mehra, Harlan M Krumholz, Sounok Sen, Christopher M Kramer, Matthew W Martinez, Milind Y Desai, Evangelos K Oikonomou, Rohan Khera
The American journal of cardiology 2024 Nov 23 doi: 10.1016/j.amjcard.2024.11.028
PMID: 39581517 -
A Multimodal Video-Based AI Biomarker for Aortic Stenosis Development and Progression.
Evangelos K Oikonomou, Gregory Holste, Neal Yuan, Andreas Coppi, Robert L McNamara, Norrisa A Haynes, Amit N Vora, Eric J Velazquez, Fan Li, Venu Menon, Samir R Kapadia, Thomas M Gill, Girish N Nadkarni, Harlan M Krumholz, Zhangyang Wang, David Ouyang, Rohan Khera
JAMA cardiology doi: 10.1001/jamacardio.2024.0595
PMID: 38581644 -
Estimated Effectiveness of Nirsevimab Against Respiratory Syncytial Virus.
Hanmeng Xu, Camila Aparicio, Aanchal Wats, Barbara L Araujo, Virginia E Pitzer, Joshua L Warren, Eugene D Shapiro, Linda M Niccolai, Daniel M Weinberger, Carlos R Oliveira
JAMA network open 2025 Mar 3 doi: 10.1001/jamanetworkopen.2025.0380
PMID: 40063022 -
Use of electronic health records to characterize patients with uncontrolled hypertension in two large health system networks.
Yuan Lu, Ellen C Keeley, Eric Barrette, Rhonda M Cooper-DeHoff, Sanket S Dhruva, Jenny Gaffney, Ginger Gamble, Bonnie Handke, Chenxi Huang, Harlan M Krumholz, Caitrin W McDonough, Wade Schulz, Kathryn Shaw, Myra Smith, Jennifer Woodard, Patrick Young, Keondae Ervin, Joseph S Ross
BMC cardiovascular disorders 2024 Sep 18 doi: 10.1186/s12872-024-04161-x
PMID: 39289597 -
Artificial Intelligence-Enabled Prediction of Heart Failure Risk From Single-Lead Electrocardiograms.
Lovedeep S Dhingra, Arya Aminorroaya, Aline F Pedroso, Akshay Khunte, Veer Sangha, Daniel McIntyre, Clara K Chow, Folkert W Asselbergs, Luisa C C Brant, Sandhi M Barreto, Antonio Luiz P Ribeiro, Harlan M Krumholz, Evangelos K Oikonomou, Rohan Khera
JAMA cardiology doi: 10.1001/jamacardio.2025.0492
PMID: 40238120