How to Save a Life: Big Data and Little Babies

ibm data baby

I wish I spent the entire workday focused on how technology can help those who need it the most. We have endless opportunity to change the world, if only we could magically create the right collaborative relationships. Bringing together different communities, with varied experiences, often allows us to solve the most challenging issues.

Just a few years, that happened. We established a unique three-way relationship between The Hospital for Sick Children in Toronto (SickKids), The University of Ontario’s Institute of Technology (UOIT) and IBM. The goal was to provide better care for newborn infants in the neo-natal intensive care unit. Could big data assist in detecting the subtle warning signs of sepsis, a life-threatening infection?

CNBC recently documented part of this story in their “Rise of the Machines” show. (

The challenge? Dr. Andrew James, from SickKids, explained: “About 20 percent of low-birth-weight babies develop an infection, and of those babies about 18 percent actually pass away. So it’s very serious—and very common.” The physicians theorized that by detecting signals indicating the onset of sepsis, they could intervene earlier to address the life-threatening situation.

The solution? Although sensors routinely monitor medical readings, staff only captures this data at specific time intervals. What if you could track and store readings every second over an extended period and see minuscule changes? Using stream computing technology provided by IBM, the team developed an infrastructure allowing them to collect and store up to 1,000 unique physiological readings every second for each baby. Over time, UOIT and SickKids aggregated data sets for infants developing sepsis. They analyzed these data points in order to provide a real-time view of changes across all affected babies by looking for unique common trends.

The result? Researchers found that heart rate changes, among other changes in the vitals, were a clear sign of infection. “With inflammatory response, there are chemical signals to the brain that affect heart rate,” Dr. James explained. “And—when there’s an infection, heart rate variability decreases.” This assisted physicians in identifying the onset of the illness up to 18 hours earlier.

Combining human knowledge with device-generated data produced potentially life saving results.

I have had the privilege of working with IBM researchers from this project and commercializing the technology across other medical conditions. The lesson for me is quite clear: By identifying a key challenge, bringing together disparate groups, leveraging their combined experiences and collaborating to produce an innovative solution, you can produce profound results.

Help us find other ways to leverage technology to help those who need it the most. Please share your ideas below or contact me directly.

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Categories: analytics, big data, Business, CIO, technology, Uncategorized

About the Author,

Steve Harvey is the Worldwide Leader for Technology and Analytics across IBM's Business Process Outsourcing unit.


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