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Green HERON Introduction

As part of the KUMC CTSA Informatics Core, we aim to streamline research processes by providing clinical data analysis environments and to engage investigators in the use of informatics tools for collaboration across the entire spectrum of translational research.  KUMC has established an integrated clinical data repository, HERON, with approximately 2 million patient electronic medical records (EMR) as well as research participant registry, socioeconomic data, and death data, which is a valuable resource for clinical and translational research.  To engage the broader scientific community and catalyze research collaboration, we are expanding the current HERON's capability by creating an open and protected clinical data analytic environment called Green HERON.

Green HERON is a highly protected health data analytic space where approved users can work with de-identified and identified health information.  Green HERON simplifies the effort of obtaining EMR data from KUMC HERON, while supporting collaborators from around the world with approved NetIDs.  The analytics space offers a rich set of tools, services, and resources required by research.  Within the protected environment, Green HERON users are provided the ability to select analytic tools such as R, SAS, and Python.

Requirement for access:

  • Secure KUMC network (either on campus or via VPN)
  • KUMC Faculty member or sponsored by a faculty member
  • Up-to-date Human Subjects Training
  • Signed system access agreement

*KUMC affiliated accounts can be created upon request and approval

Software tools available:

  • SQL Developer
  • R and RStudio
  • Python
  • SAS

*Additional software can be installed upon request and approval.

Discussion forum:

Past Events

  • 1st Frontiers Informatics Meetup (May 23, 2019)
  • 2nd Frontiers Informatics Meetup (September 26, 2019)
  • 3rd Fronteirs Informatics Meetup (December 12, 2019)

Upcoming Events

  • 4th Frontiers Informatics Meetup - Healthcare Data Sharing and Privacy (March 5, 2019 4-6pm)

Tentative Topics:

    • Electronic Medical Record Data De-identification By Dr. Noor Abu-el-rub (University of Kansas Medical Center)
    • Security and Privacy Preserving Learning By Dr. Fengjun Li (University of Kansas)
    • Impact of Data Anonymization on Prediction by Dr. Xing Song (University of Kansas Medical Center)

Event Registration

Event Parking: Free parking will be available in the P4 Bluff Garage starting at 3pm.  The garage can be seen here on the campus map.

Last modified: Dec 30, 2019