Looking back to before data was big

'Ten years ago, you were lucky if you could even find data that you could use.'
By Mike Miliard
10:55 AM

It's hard to go too long these days without hearing someone hype the benefits of big data. It's to the point where the term is all but a cliché. Hard to believe that's it's still a fairly recent coinage.

"Maybe three years ago?" says Cynthia Burghard research director for accountable care IT strategies at IDC Health Insights, when asked when she first heard the now-ubiquitous term. "It's still relatively new, across all industries. Some industries have used pieces of the big data and analytics technology stack, but not in its entirety."

So much has changed in the past few years when it comes to data and analytics in healthcare – never mind the quantum leap from where we were a decade ago.

"We've come a long way," she says. "We now have technology that can do high-performance computing, that can bring data in from multiple sources – both structured and unstructured. Ten years ago, you were lucky if you could even find data that you could use.

"I worked at a health plan and I wanted to run a very simple report that told me the number of hospital days per thousand members. And it took three weeks for that program to actually run. And then you had to add this, subtract this, divide by three, and then hope for the best. Very crude data. Very cumbersome access. You always had to go through IT to get your data."

Predictive analytics is another big buzzword nowadays, but not too long ago, "it was about reporting facts – and mostly retrospectively." At a payer, it wasn't uncommon to be scrutinizing data that was three to six months old, she says. "It was very hard to make any kind of use for decision-making. By the time you actually got the data, the horse was out of the barn, so to speak."

Two things have driven the belated – and arguably still inadequate – move toward analytic intelligence in healthcare, of course. The technology has advanced, and payment reform has forced the issue.

"We really only started automating healthcare maybe 20 or 25 years ago," says Burghard. 
"Before that it was manual charts, handwritten claims. Even in the late '80s we had rooms full of claims. Stacked to the ceiling!"

And "it wasn't really until the late 80s, early 90s when the first cost really jumped up and people said, 'Oh, we can't sustain 12 and 15 percent premium increases every year.' The industry realized it had to do something about managing cost and quality that the industry turned its attention to analytics. It hadn't really be necessary because there wasn't really any cost pressure."

Still, it's really only been in the past half-decade or so, since HITECH, the Affordable Care Act and assorted other payment reform initiatives, that use of analytics has started to gain steam.

"The new reimbursement models, the only way they're going to be successful is if they have good data: what their health conditions are, what their family situation is, and then a whole range of information about the delivery system, and where's the most cost-effective, high-quality physician or hospital that that person should be going to," says Burghard.

If deployment of analytics technology has been halting in the past, it's undoubtedly on the rise. Frost & Sullivan projects the usage of advanced health data analytics solutions in hospitals will increase to 50 percent adoption by 2016.

Want to get more stories like this one? Get daily news updates from Healthcare IT News.
Your subscription has been saved.
Something went wrong. Please try again.