Computerworld - A hospital is usually a pretty busy place, but the neonatal intensive care unit at Toronto's Hospital for Sick Children has been buzzing with even more activity than is customary. Thanks to a new technology partnership, the hospital is working to use analytics to predict more accurately than ever before which premature babies are at most risk for disease and infection.
The hospital is in a study to monitor temperature, heart rate, blood saturation and blood pressure levels on preemies, collecting streaming data from electronic devices that monitor the premature babies.
Sick Kids, as the hospital is known, is in good company. Healthcare providers -- from insurance firms to hospitals to service suppliers -- are lining up to adopt advanced technologies to help them take better care of their patients, in many cases becoming more proactive and more personalized than ever before, with the hopes of saving money, too.
Susan Feldman, vice president at research firm IDC, says technology is enabling a process "that will change our lives. One of the things going on in healthcare is understanding we need more of our decisions based on evidence so we can more appropriately process and identify information, and bring it to decision-makers in an actionable way."
It's not just healthcare that is on the verge of benefiting from predictive analytics. Other industries that struggle with vast amounts of ongoing data where this type of technology makes sense include finance, emergency response, entertainment and the legal field, to name a few. (See sidebar.)
Society is "on the cusp of being able to do more than ever before, and support decision-making in ways that have not been possible before," says Dr. Harlan Krumholz, professor of medicine at Yale University and a physician who is also involved in big-data research projects with large hospital consortia.
That said, however, specific results will be up to watchful physicians to ensure, he warns. "Those claims about being able to improve medicine ... have to be looked at carefully. The question is: What do people do with the information [from these systems]?"
"If wrong decisions are made based on [incorrect] assumptions about information, they won't obviously provide any value and could [instead] be harmful," Krumholz says.
Back in Toronto, the hospital is processing its data in real time using IBM's InfoSphere Streams, software that can correlate and analyze thousands of real-time data sources. The University of Ontario Institute of Technology (UOIT) is using the software to collect streaming data from electronic devices that monitor the premature babies.
The technology is giving UOIT the ability to make sense of the data and analyze it in ways that include, they hope, discovering the onset of sepsis and various other conditions before these problems occur, says Dr. Carolyn McGregor, the Canada Research Chair in Health Informatics at UOIT.
With the promise of big data (solving the unsolvable problems, informing better decision making, creating new products and services, discovering patterns and acting on them, etc.) on the horizon, what has really changed? Does this mean that everything we know and do with not-so-big data should be tossed?
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