The cornerstone of an enterprise data analytics project is laid by senior level management. That was one message Rick Schooler delivered at Health Data Management’s Healthcare Analytics Symposium in Chicago.

Schooler, the vice president and CIO at Orlando Health, said the effort needs the backing and direction of an executive-level governance group to succeed. Otherwise, any effort at data analytics could be continually sidetracked by what he called the “tyranny of the urgent,” or the need to put out fires as they occur.

Schooler’s presentation provided a primer for an enterprise data analytics effort. At the most basic level, the organization first must understand the need for analytics. Schooler said it took him five years to convince the health system of the value of an analytics program, which seeks to digest and analyze performance metrics across care settings. He described the make-up of a core analytics team as comprising staff with expertise in data use, source systems capture, analytics methods, and training. “If you don’t put this expertise in place, what you have will become worse,” he said.

The focus of team should be to establish analytics methods and standards, with a systems inventory as an early chore. The number and type of individual databases storing proprietary departmental data is usually an eye-opener, he said. “It is staggering when you document it. The jaws drop.”

Even after an analytics group with senior backing has been formed, changing the mindset and culture of the organization to believe in “one source of truth” from a common analytics platform, rather than relying on disparate compartmentalized databases, is a major challenge, he said.   Source data validity must be a priority. This is a three- to-five-year gig,” Schooler said. “It does not happen short-term.”

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