Aim
A recent UCSF study found that there were 187 audible alarms per bed per day in the ICU, with a false-positive rate of over 88 percent for arrhythmia alarms. Put that in the context of all the other noise in a busy ICU and you begin to understand the concept of alarm fatigue. It’s no surprise that in many settings, clinicians ignore alarms, turn them down or turn them off, leading to a nationwide epidemic that goes beyond the ICU to other hospital units.
SOM Tech worked with UCSF clinicians and researchers to develop Super Alarm, a device that aggregates disparate data, captures trending patterns and filters out false alarms, so clinicians are only alerted when there is a situation that truly demands clinical attention.
The team has already shown they can achieve 90 percent sensitivity in predicting ICU cases where a patient is in need of resuscitation – known in hospitals as code blue – and is on track to complete a prospective National Institutes of Health (NIH)-funded clinical study by the end of 2017.
It is, in a sense, what nurses do in the ICU – they’re watching things all the time, recognizing trends – but with all the data we have these days, including from EHRs [electronic health records], we don’t always have the human bandwidth to filter, synthesize and recognize when the pattern indicates real clinical urgency,” says researcher Michele Pelter. “So engineers grab these data points, and we ground them in who cares and what matters.
Approach
As advisors to the Clinical and Translational Science Institute (CTSI) Digital Health program, SOM Tech worked with biomedical engineer Xiao Hu and his team to create an identity and pitch that helped their ideas get off the drawing board and into the ICU. The team helped shape their story, create the Super Alarm patient website, and establish an identity.
Solutions
First, data had to be integrated into the Super Alarm database as fast as possible, while anticipating potential complications due to impedance mismatch. SOM Tech 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. Drawing on our extensive experience with real-time integrations, we decided to use a JMS queue to hold data from Cloverleaf. The result was a robust integration between Cloverleaf and the Super Alarm database that handles variance in network speeds and can also handle Cloverleaf loads of up to 15 HL7 messages per second.
Partner
The SuperAlarm team, including Xiao Hu, PhD and Richard Fidler, RN, PhD, CRNA
More Information
SOM Tech helped the Super Alarm team crystalize their value propositions and their final Catalyst pitch, which contributed to the team’s successful Catalyst Award win. SOM Tech 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. Today, SOM Tech is partnering with the Smart Alarm team to help refine the user experience.
