Data Integration for Predictive Algorithms

ISU created an ESB integration that transforms data from the HL7 feed, containing ADT and lab results data from Epic and SunQuest, to the Super Alarm data model. 

Problem: The challenge was to get the data into the Super Alarm database as fast as possible, while anticipating potential complications due to impedance mismatch. 

Solution: Drawing on our extensive experience with real-time integrations, we decided to use a JMS queue to hold data from Cloverleaf.

Outcome: A robust integration between Cloverleaf and the Super Alarm database that handles variance in network speeds and can also handle the peak load coming from Cloverleaf (15 HL7 messages/second). 


Catalyst Grant Support

As advisors to the Clinical and Translational Science Institute (CTSI) Digital Health program, ISU worked with Xiao and his team to create an identity and pitch that framed his ideas. 

The team helped shape their story, create the Super Alarm patient website, and establish an identity. Through helping shape their identity, ISU helped them crystalize their value propositions and their final Catalyst pitch, which contributed to them winning the Catalyst Award. 

ISU helped Xiao's team articulate their work through providing User Experience insights and perspective. Workshops and other collaborative design processes, facilitated PIs translating the description of their highly technical solution into something more human sounding and human centered. Currently, ISU is partnering with the team to help define the user experience.