Big data in healthcare: What’s holding everyone back

Granite Healthcare Network in Concord, N.H., found what appeared to be an obvious variant in claims data. However, that variation turned out to be false, said Bob Kay, director of population health at Granite Healthcare Network.

What solved the puzzle and brought the truth to light was clinical big data, Kay said. “The context of those claims is very important.”

When it comes to data analytics and big data in healthcare, many organizations struggle to understand the data, never mind analyzing it and reaping the benefits.

In Granite Healthcare’s case, this false variation was due to differences in how claims are paid and how hospitals process claims. Kay explained that a health system charged for a service under an incorrect category which “artificially drove up the rate and the expense for that service category.”

Ultimately, Kay said Granite Healthcare figured out that this was indeed a false variation after having their health systems provide their clinical data as well as explain their billing practice so that the pieces could be put together.

“It’s probably a universal issue with claims data because claims data is really just used to pay bills, and sometimes what you see in claims data is the artifact of how those bills get paid rather than true variation,” Kay said.

Unfortunately, Granite Healthcare doesn’t have claims data merged with clinical data yet — and they are not alone in this big data and data analytics predicament.

Joel Vengco, vice president and CIO at Baystate Health based in Springfield, Mass., said during a panel at the recent Health IT Summit in Cambridge, Mass. that his organization ran into a problem similar to Granite Healthcare’s with its diabetes population. By analyzing only claims data, analysts missed about 35% of people in the health system’s overall population who should have been in the diabetes programs. Vengco said analysts discovered this disparity after they had integrated clinical data in with their claims data.

Many healthcare professionals acknowledge the importance of data analytics and big data in healthcare, but due to lack of interoperability and the healthcare community not yet grasping how to derive value from big data, many are unable to take full advantage of the benefits, like precision medicine, population health management and value-based care.

“The ship has left the dock. We’re all going to have to make this journey,” said Deane Morrison, RPh, CIO at Capital Region Healthcare and Concord (N.H.) Hospital, during the panel.

Before a hospital jumps up and implements analytics, Vengco urged the audience to remember that the data itself is key. “You’ve really got to work on the data and make sure that you’ve transformed it, you’ve localized it, you’ve standardized it, you understand what the knowledge management and the master data management components are for that data so you can evolve it over time,” he said. “The analytics piece will come. But if you don’t have the right data you’re never going to have the right analytics.”

Morrison also advised that “when you [go] through and you look at all the inferences you … really have to challenge yourself [and] say, ‘Can I really draw this conclusion from the data or is the data misleading me?’ And that’s our challenge.”

Granite Healthcare’s solution to the problem of disjointed claims and clinical data was to get help piecing the two sets together  from athenahealth Inc. in Watertown, Mass., a cloud-based electronic health records company that also sells medical billing services.