The University Research Informatics Data Environment, also known as URIDE, is a web-based platform that aggregates and visualizes de-identified data from multiple clinical systems UHealth UChart data and Health Choice Network data.
With URIDE, clinical research investigators and their teams can easily explore demographics, diagnoses, procedures, vitals, medications, labs, notes, allergies, comorbidities, locations, physicians, and much more.
Why Use URIDE?
UM investigators conducting scientific research may want to explore de-identified patient data for:
- study design
- feasibility analysis
- grant submission
- or other applications in which population assessments need to be conducted
If you are UM faculty with a valid Cane ID, you already have access to URIDE. Go to https://uride.idsc.miami.edu/home/.
NON FACULTY USERS
If you are NOT UM faculty (e.g., student, resident, staff, etc.), you may obtain access to URIDE with authorization from a sponsoring Principal Investigator (PI) or Faculty using the URIDE Access Request Form.
- You (= the Requestor) must complete the URIDE Access Request Form. You will need a valid Cane ID, and the name and email of your sponsoring PI/Faculty.
- Next, the request will be directly forwarded to the PI/ Faculty Sponsor listed on your questionnaire. You must make sure the PI is aware of your request. Several reminders will be sent.
- After we receive the PI authorization and the vetting process is completed, you will be granted access to URIDE.
For any additional information or questions, please contact us at email@example.com
- Log in with your Cane ID and Password
- Make sure to use a browser other than IE
- Make sure you are using a computer that is logged in to the UM network either through a direct connection, SecureCanes Wi-Fi network or VPN (preferred if working remotely.) More information about the University’s VPN can be found here.
Use Case Guides
Questions or Consultations
Email the CTSI Biomedical Informatics team at CTSIservices@med.miami.edu
URIDE was designed and developed by the Software Engineering team at the University of Miami Institute for Data Science and Computing under the Informatics Program of the Miami Miami Clinical and Translational Science Institute and supported by Grant Award Number UL1TR002736