Data analytics driving medical breakthroughs

Using big data to save lives

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This test has been running in parallel with current clinical practice so doctors and scientists can compare the two approaches, which they are now in the process of doing. One day's worth of data is copied and sent back to UOIT for the offline analytics component.

The platform, known as Artemis, or "data baby," has been input with a set of clinical rules that serve as a layer of analytics to help it make predictions for the first time, says McGregor, who is also a professor and associate dean at UOIT. Today, medical devices at the bedside give broad information, she explains. Devices provide readings at a very high frequency, but "a human has to be able to analyze" the results, which are "constantly changing," McGregor says.

Final results have not yet been released -- they're expected sometime in late April for peer review and should be public by year-end. But initial results have proven Artemis's "robustness as an approach," McGregor says. The study, of over 400 patients in three sites, has collected "the equivalent of two decades of patient years" worth of data, she explains.

While medical personnel have some traditional indicators for the onset of infection -- such as body temperature -- Artemis will provide "a much richer environment," McGregor says, to analyze a range of different signals for a variety of various conditions that babies can develop.

Premature baby
Toronto's Hospital for Sick Children is testing a data analytics system to more accurately predict which premature babies, like this one, are at highest risk for infection. Photo credit: Carlos Garcia Rawlins / Reuters

"This system was designed to predict the onset of sepsis 24 hours before it became clinically apparent," says IBM's Chief Medical Scientist Marty Kohn. "It is using structured data to look for patterns that allowed [the hospital] to predict the onset of serious disease based on clinical observation. In a case like this, if you can intervene an hour earlier you can often improve outcomes dramatically."

"This has the potential to reduce a baby's average length of stay in the hospital, as well as to save lives," McGregor says.

UOIT and hospital staffers also plan to use the data to do more clinical research "to look beyond what people already know from watching a heart rate for example; what else we can find from looking at physiology," McGregor explains. By running new algorithms, she says Artemis would be able to tell clinical staff with high probability that a baby's behavior change might be correlated to infection.

Dealing with data deluge

The ability to make sense of unstructured information and make predictions about diseases that could develop, thereby enabling physicians to make better decisions about treatment, is the goal of a set of tools from IBM that include its highly publicized Watson technology. Voluminous amounts of information come at doctors all the time, especially with thousands of new articles being published monthly in medical journals. Add to that lab results, health care systems and social networking sites for professionals, and it can become overwhelming pretty quickly.

"As you gain more and more information in the world, it becomes impossible for a person to manage a physical library or have an electronic collection unless you can create very intelligent access to it,'' explains IDC's Feldman. "Language is so rich and so variable that there are too many ways of saying the same idea, so you really need technologies that can understand all the various ways we can understand something."

Tools that structure various sources of information by applying analytics are helping the health care industry -- among others -- gain a whole new level of intelligence, observers say. IDC is projecting the overall big data information technology and services market to grow from $3.2 billion in 2010 to $16.9 billion in 2015.

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