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Mayo's Nilay Shah, PhD: Just Having the Analytics Isn't Enough

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Predictive analytics are powerful, they’re everywhere, and they can be meaningless if not designed with a purpose.

Predictive analytics are powerful, they’re everywhere, and they can be meaningless if not designed with a purpose.

Healthcare Analytics News had the opportunity to visit the Mayo Clinic Kern Center for the Science of Healthcare Delivery. There, Kern Center Deputy Director Nilay Shah, PhD, discussed how analytics can be made more meaningful to clinicians.

“You’ve got this beautiful product, but if it doesn't fit the workflow and doesn't fit the needs…” of the patients and clinicians, Shah said, “then it becomes problematic.”

He noted that despite widely growing interest in predictive analytics, a lack of applicability has muted their overall adoption. Even good, validated risk scores don’t necessarily provide physicians and patients with meaning unless the methods are developed with their input in mind.

“We're taking a sort of learning health system approach…we are now talking to a number of clinicians to say ‘How would you use this information?’ We're talking to patients to say ‘If you had this information, how would it have helped you? Would this have helped you, if so what would you've done?’”

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