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Big Data Changes How Diseases are Diagnosed

July 2nd, 2014 by - 2,013 views

It’s no secret that Big Data is in the process of revolutionizing how we view the world or that it has already transformed a number of industries in the past handful of years. One of the most fascinating areas of development is the health sector, which uses the technology to better diagnose and locate potential risks within patients through analyzing their medical history and symptoms to prevent a problem before it manifests itself. According to recent studies, research is now more critical than ever in nailing down a medical complication.

It's a truth of the contemporary health insurance industry that cutting down costs can be just as important as a patient's health - fortunately, big data offers the ability to improve both using analytic research processes.

Cutting costs can be just as important as a patient’s health – luckily, Big Data can potentially improve both using analytic research processes.

Insurers benefit from locating health risks before they occur
A recent piece in Information Week by Alison Diana explained how Big Data research has helped medical professionals identify a very specific condition using past records and symptoms as their guide.

“While organizations have used a lot of Big Data projects to discern trends, a study conducted by Aetna and GNS Healthcare analyzed data from almost 37,000 members of an Aetna employer customer who opted in for screening of metabolic syndrome – which can lead to chronic heart disease, stroke, and diabetes,” Diana expanded. “GNS analyzed information such as medical claims records, demographics, pharmacy claims, lab tests, and biometric screening results from a two-year period.”

Achieving this impressive result required a mass amount of information from cloud computing servers to narrow results down to a specific patient, something that wouldn’t have been possible to do before the emergence of Big Data technology. Because the risk for metabolic syndrome can now be identified far more quickly than in the past, health insurance providers are taking advantage of Big Data to restructure their systems to save money and reduce complications on behalf of their customers. Research indicated that the condition is 90 percent less likely to affect people if patients have secured primary health care providers and attend regular checkups – by extension, it behooves major providers to tailor their services to whichever processes keep expenses low. Diana spoke with Adam Scott, managing director of Aetna Innovation Labs, about how cloud computing will change the way health insurance is dispersed.

“If we can use information that we have on hand to understand more about disease and risk and provide that information to both our membership and those providers that care for those members, we can drive toward better value, delivered toward better outcomes,” Scott said.

Understanding the moves toward Big Data
Like many things in the medical field, it’s often difficult for the lay person to understand exactly why Big Data is going to change the way we live and interact with one another. Ironically, Forbes contributor and Senior Vice President of Information and Analytics at IBM, Bob Picciano, recently wrote that the key to understanding the technology is to use it. He referred to the phenomenon as a type of new natural resource that is ubiquitous, but harnessed effectively by few.

“Because even as information access is becoming commonplace,” Picciano explained, “the ability to analyze data and add expertise to it is turning into a competitive advantage. Like any natural resource, some data can be a commodity.”

Health insurance providers appear to be working toward this level of understanding to identify costly medical threats to their customers before these expenditures become a problem. In this industry, the healthier consumers remain, the larger the “competitive advantage” is for the company funding the care. It’s a truism about the contemporary health insurance industry: cutting down costs can be just as important as a patient’s health – luckily, Big Data can potentially improve both using analytic research processes.

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