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“Big data” could cut billions in health care spending

NEWS IN BRIEF — Posted April 22, 2013

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Use of so-called big data in health care could lead to an annual savings of up to $450 billion, according to a report by McKinsey & Co., a global management consulting firm. “Big data” refers to large repositories of data from multiple sources that can be used by researchers to make health-related discoveries.

Analyses of large volumes of data gleaned from multiple sources could help researchers identify trends that could improve outcomes and result in savings of $300 billion to $450 billion annually, according to the report, published in April.

The report outlines some examples of big data-driven projects that have proven successful, including one at Kaiser Permanente. Using its electronic health record system, which allows the exchange and collection of data across all Kaiser locations, the health care system identified ways to improve outcomes in cardiovascular disease. The discoveries resulted in fewer lab tests and office visits, saving $1 billion annually (link).

Authors of the report warned that challenges to creating a big data-driven health care system, including the movement away from fee-for-service care and privacy issues, must be addressed before big data’s potential is realized. They said health care can learn a lot by studying how other industries, including retail and banking, have used big data to achieve positive results.

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