Ochsner Health Systems came by its big data organically. That is to say the IT folks did not so much kick-off a big data strategy as begin aggregating internal systems – only to realize “wow, we have a lot of data here.”

Government Health IT Contributor Kate Spies spoke with CIO Chris Belmont (pictured at left), and enterprise information architect Jonathan Stevenson about the providers’ big data plans, how it intends to employ predictive analytics to improve patient care after an Amazon fashion, and the challenges particular to public health.

Q: How has Ochsner been approaching big data thus far?
Belmont: Ochsner started more or less automating and collecting clinical data with Dr. Lynn Witherspoon - who’s now our Chief Medical Information Officer - who created a database to start storing lab results, and that morphed into an electronic medical system that’s been serving us well probably up until about a year ago. It’s actually still in production today. But we needed to replace it with something more enterprise-based, something that would be a little more agile, a little more flexible and scalable as Ochsner continues to grow. We collected the data, but the issue is getting it back and getting it into the right hands. We also, over the years, have aggregated about 38 different systems that collect clinical data; we have a total of about 225 information systems that we support here at Ochsner. And all of those systems, more or less, keep their data in islands.

The real value is not necessarily reporting out of those individual transactional systems, it’s the ability to aggregate and correlate that data horizontally across those organizations. So for example, if we want to look at labor and how that’s used, it would be nice to say, ‘Okay, we had this many lab tests,’ and then to match that against how many hours worked, which is in another system, and then to say, ‘what does that look like from a productivity perspective?’ So that’s just one example of thousands of opportunities we have out here to look at the data. And again, the big data piece more or less evolved because if you look at the systems that we’re aggregating today in our current systems warehouse, if you slam all that together, plus the number of years that a lot of the system has been running, it just kind of showed up as big data. We didn’t go in with a ‘big data strategy’ – once we drew it altogether, we realized, ‘wow, we have a lot of data here.’ And it’s not just big data in quantity, but it’s big data in complexity as well; the data doesn’t always match when you take it from different systems and put it together. So there are data governance decisions that need to be made around that.

Q: Why is Ochsner working to mobilize big data?
Stevenson: Healthcare in itself is changing. It’s morphing into a different market essentially, where we’re going to be held responsible not just for the volume of patients that we manage but also for the actual outcomes relative to the volume of patients. So the magic in making that successful for any organization is the data. So why are we undertaking this strategy? It’s because we have to, not because we really have any choice relative to the way the market is moving.

Q: Why is the healthcare industry behind in terms of harnessing big data?
Belmont: At the end of the day, big data is here to help us take care of our patients better, and also to service our community better. And one of the reasons I think we’re behind has just been this traditional approach of using the data for specific cases, versus using our data for operations, and not more on how do we look to serve our community better, and serve our patients better. Unfortunately, what healthcare does is a lot of retrospective reporting, so we gather up the data, we give it back, and say this is what happened yesterday, or last week, or last year. We’re not doing well at what other industries have done – whether it’s finance or retail, and so on – to do more of the surveillance and predictive stuff.

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