There are ways to do analytics right
April 3, 2014 in Medical Technology
With apologies to Internet meme-makers everywhere, analytics experts have a message for healthcare providers trying to get their heads around business and clinical intelligence: “Big data, you’re doing it wrong.”
So much attention and energy have been put toward “big data” in the last couple of years, for perfectly understandable reasons. For example, health systems collectively have spent billions of dollars installing EHRs in recent years. “They want to get their value,” says Cora Sharma, analytics analyst for Chilmark Research, a Cambridge, Mass.-based health IT research firm.
They certainly see a lot of potential in the data. A March poll from MeriTalk and EMC found that 63 percent of healthcare executives in the federal government believe that big data will improve population health management. Similar numbers show that advanced analytics would “significantly improve patient care” and make it easier to deliver preventive care in the Military Health System and Veterans Health Administration.
[See also: Deloitte taps the Zen of data analytics.]
But so few have proper goals and strategies for their data, according to Graham Hughes, MD, chief medical officer of business analytics firm SAS, based in Cary, N.C.
“They’re looking to accumulate data and how to get data in,” Hughes says. In his opinion, this is a faulty course of action. “It’s not about the data. It’s about how you’re going to manage it.”
The focus, according to Hughes, should be on information management, including data governance, stewardship and quality. “If you are just about grabbing data, you will be on a data grab forever.”
Optum, the IT and analytics division of UnitedHealth Group, published a white paper in February that corroborated this belief, particularly when it comes to clinical analytics.
“It may sound impressive to say that your organization has access to terabytes of patient information, but without robust technology and smart people to manipulate it, that data is simply words and numbers without context,” researchers point out in the white paper.
[See also: Rocky road ahead for BI.]
“Raw data from claims or from an EMR database are not suitable for analysis. Turning raw data into usable information requires preparation, including normalization and validation. Only then can an organization gain trustworthy insights from the information and put it to use in maximizing patient care, reducing risk and strengthening a business’s bottom line,” they add.