Health IT Needs Moneyball Technique To Succeed

The healthcare industry needs to "professionalize" its analysis of big data; in other words, create a "moneyball technique," said Andrew Slavitt, group executive VP of Optum, at the eHealth Initiative Annual Conference in Orlando, Fla. As care shifts from traditional outlets to non-traditional settings, such as at-home services, the industry needs a better big data strategy to manage the change.

"…[T]he urgent needs of today are well beyond the four walls of the hospital," Slavitt said, but the industry continues to build IT for the old world of care. This new world, he said, or the "new care," involves a large portion of the population that he called "dual eligible," patients who are eligible for both Medicare and Medicaid. "The average dual eligible consumes $36,000 [of healthcare services] per year," he said. "That's $360 billion [nationwide]."

As health disparities between dual eligibles and the rest of the population grow, Slavitt noted the cost burden is shifting to those taking care of the dual eligibles. Driving down healthcare costs to address this trend is where better healthcare analytics and a moneyball strategy come in.

[ Not everyone is impressed with healthcare's latest trend. Read Big Data Analytics: Where's The ROI> ]

The Michael Lewis book Moneyball laid out how the Oakland Athletics used deep analytics to win two-thirds of its games in 2001. Baseball always had reams of data and statistics, but the A's figured out which data matters most.

"They eliminated noise and clutter from data," Slavitt said. "…They tested baseball in simple terms, and anything that didn't create an 'out' had value. … They built consistent winning teams by selecting players who excelled at the right stats."

Applying the same concept to healthcare, said Slavitt, means focusing on "how do we get value out of data?" Slavitt said a good role model is Tucson Medical Center in Arizona. The small, rural center built an accountable care organization and professionalized how it looked at data. After launching its ACO, the center selected groups of patients and used data analysis to determine where it could drive down costs.

Within a group of 230 patients, Slavitt said the organization invested in ways to create "unique and proactive ways to take care of them," such as increased home visits and primary care visits among other initiatives. As a result, the center saw a decrease of 5% in readmission rates and a 5% increase in market share due to primary care referrals.

"To get IT on top of your CEO's agenda, you need to speak two things: margin and market share," he said. "As soon as IT and data speak that, knowledge and movement is accelerated."

Slavitt closed his keynote by asking if big data is hype, fad or trend. Although most attendees responded with "fad," Slavitt insisted on "hype," and maintained there is potential for big analytics to have a lasting impression in healthcare.

Today, there's a key piece missing from the big data discussion, he said. "Our lack of interoperability and standards hurts patient care and drains usefulness out of data," he said. "We need to do this with a money ball view -- we need to link data. The verdict is big data is hype, until collaboration comes in."

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