Data analytics driving medical breakthroughs

Using big data to save lives

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"Why Watson is such a breakthrough is it understands questions and tries to interpret them," while making hypotheses through its text mining and analytics capabilities, says IDC's Feldman. IBM built Watson to do what it calls "Deep Q/A," she says, with QA standing for question and answering.

"It's a whole new approach or technology that tries to understand what people are looking for," she says. The technology understands how one entity affects another; in health care, for example, the computer can analyze how a drug affects a particular type of person who has a certain type of disease.

This approach is much different from how a search engine works. A search engine attempts to answer a question that has been input using a few keywords, says Kohn. "Then you get sites or pages to look at to see if any are actually relevant to the question you have in mind. That takes a lot of time ... it's an ineffective process at best."

In contrast, Watson understands a question that's been posed in natural language, reads literature and, using a series of massively parallel "probabilistic algorithms" to analyze the information it is given, goes out and brings back prioritized suggestions on whatever the topic, Kohn says.

Answering complex questions

WellPoint, which bills itself as the country's largest health benefits company, recognized that the Watson Deep Q/A initiative could be used to automate utilization management. That's the manual, often complicated and time-consuming insurance-approval process physicians are required to go through before treating patients, says Ashok Chennuru, director of technology.

"We know according to guidelines and policies we have for cancer treatment options that [patients] need certain drugs and procedures" that are given or performed in concert for maximum benefit. However, right now the company doesn't have a streamlined approach for doctors' offices to submit multiple pre-op authorization requests together, says Chennuru. "Sometimes not enough documentation is submitted and we have to go back and forth and it can be frustrating."

The company started using IBM's Content and Predictive Analytics (ICPA) decision support engine last fall to automate the submissions process between the physician and payer, he says. If everything is clearly documented from the doctor's office, it is sent to WellPoint's version of Watson, which determines if the submission meets all criteria and quickly gives a yes or no answer or requests more information, he says.

WellPoint is conducting a pilot in one region on a limited basis to ensure that the tool is working well, Chennuru says. By the end of the year, the company is hoping to deploy it in all 14 states where WellPoint has facilities.

Eventually, once oncology is covered, WellPoint foresees being able to use the tool for other medical issues such as respiratory distress, diabetes and cardiac and kidney diseases. Using Watson, WellPoint says it envisions being able to look at massive amounts of medical literature, population health data and a patient's health record to answer "profoundly complex questions."

The company believes it will eventually be able to develop new applications to allow physicians to load patient medical histories, recent test results, recommended treatment protocols and the latest research findings into Watson. The goal is to be able to discuss the most effective courses of treatment with their patients.

"It's about leveraging the power of the computer rather than oncologists having to keep up with this [new information] they receive on a daily basis,'' says Chennuru.

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