What's your strategy for big data deployment?
Big data optimism is at a fever pitch in the healthcare industry, and with good reason. According to a recent analysis by consulting firm McKinsey & company, use of such tools and processes could help to save U.S. citizens as much as $450 billion in healthcare costs; as in, close to half a trillion dollars.
What's more, some big-name healthcare organizations are buying in. Last month, the University of California Los Angeles and IBM announced a partnership revolving around the use of big data analytics to test the effectiveness of a real time alarm designed to predict brain swelling in trauma cases. A month earlier, Salt Lake City-based Intermountain Healthcare announced plans to collaborate with Deloitte Consulting with an emphasis on making the former's data use experience commercially available to other healthcare organizations. UnitedHealth and Mayo Clinic also unveiled earlier this year a partnership in which the two entities will combine their data for more than 110 million patients to research methods for improving care while lowering costs.
However, not everyone is convinced that big data is a silver bullet for solving the healthcare cost conundrum. Steve Huffman, vice president and CIO at Memorial Health System of South Bend (Ind.), in a post to healthsystemCIO.com this week, said big data is poised to be "the next technology that executives complain about when referring to IT investments."
"Big data should not be the reason you do a project," Huffman said. "It would be like saying 'Laptop' and hoping that someone would fund your next replacement machine. Work within your organization to develop why you might need to invest in big data and what the returns might be."
For example, Huffman said, while population management data can help providers determine which patients are at a higher risk in relation to a specific disease, what really matters is your plan for that data.
"Will the patient still be compliant if they have not been compliant to date?" he asked. "Who is going to call them and what is the payment mechanism going to be when we ask them to show up for preventative care?"
Additionally, Intermountain CIO Marc Probst told me last month at the Healthcare Information and Management Systems Society's annual meeting in New Orleans that he has some doubts, as well.
"I'm skeptical about [big data]," Probst said. "It isn't just about an appliance or an enterprise data warehouse. I'm a little worried that right now, many are just chasing medical" data tools to keep up with what other institutions are doing.
"The real value comes from this really holistic approach to caring for people, using data as evidence," he said.
The concerns of Huffman and Probst should not be taken lightly. Hospital CIOs and others with influence on the healthcare technology front need to make sure that big data doesn't turn out to be a flash in the pan that ultimately winds up in the graveyard of overhyped medical tools.
Big data use could save $450 billion in healthcare costs
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UCLA, IBM team to use big data to prevent brain swelling
Deloitte, Intermountain team up on big data analytics