HealthToon: Minimizing manual data management to maximize brain injury research
In April 2015, the Hub kicked off a series of cartoons illustrating issues around healthcare and analytics. Last month, HealthToon: Improving pediatric patient care with analytics focused attention on an effort to maintain high standards of patient care amid—and gain speedy insight from—increasing volumes of data. This month's HealthToon highlights an effort to reduce manual data management and utilize real-time streaming analytics to increase the efficiency of brain injury research.
Researchers at the University of Montana (@umontana), specifically in the office of research and creative scholarship, wanted to identify patients with traumatic brain injury who may also go on to develop epilepsy. Given that statistics show 30–50 percent of these types of patients develop epilepsy and their costs for care can be high, improving research efficiency was critical for the university.
The researchers wanted to utilize electroencephalogram (EEG) video data from animal and human experiments to identify at-risk patients, but manually sifting through 50,000 hours of EEG video data was no easy task. The University of Montana’s research team needed software that would analyze this data in real time. It turned to N-SITE LLC to deploy a solution built on the IBM InfoSphere Streams platform.
Using real-time streaming analytics, the solution facilitates an estimated overall research efficiency improvement of more than 80 percent. The university expects improved outcomes through effective and prompt brain trauma treatment, accelerated experimental research and rapid identification of patients likely to develop post-traumatic epilepsy.
Does your organization need to maximize its analytics? Please share your thoughts in a comment or tweet to #IBMHealthToon, and stay tuned for an upcoming illustration that just may apply to your organization. In addition, learn how healthcare organizations can use analytics to help improve care, reduce costs and make better decisions.