Since 2009, the healthcare industry has been intently focused on the thorny problem of EHR adoption. Goaded on by meaningful use and barely able to keep their heads above water as they navigated the financial and workflow challenges inherent in digitizing their organizations, providers spent several years without the ability to do much else. In 2014, however, as we move into Stage 2 of Meaningful Use and its requirements to begin leveraging all that data, analytics is suddenly becoming an enormous opportunity for providers to get ahead of the curve.
Steve Fanning, VP of Healthcare Industry Strategy at analytics giant Infor, spoke to HealthITAnalytics to discuss some of the biggest trends in healthcare analytics and some of the best practices to adopt when building a meaningful analytics infrastructure on top of the platform of electronic health records.
Where is the industry right now in the process of adopting analytics?
Everyone’s talking about analytics. What I find is fascinating is everyone talks about it differently. It’s one of these topics where everyone uses the same word but means something very, very different. If you’re meeting with a clinician, obviously, it’s much more the clinical decision support. Some people will even just articulate, “Oh, you have a basic electronic health record. That means you have analytics,” which a lot of people would dispute.
And then we obviously spend a lot of time with the CIOs and CFOs of organizations. And from their perspective, it’s really around the financial decision support as the overall economics are moving to more value-based reimbursement.
When it comes to macro trends, we’re seeing a lot of investment around analytics. I’ve heard CIOs describe it as the starting line. One of the things that we are really starting to see, and the reason for the acceleration around analytics, is that everyone’s very focused on meaningful use, and ICD-10
, and getting an electronic health record in.
Now that people have core business systems digitized, as well as the core medical information digitized, and the ability to interoperate, we’re finally in a position to be able to start doing some of the analytics, and we’re seeing a lot of diversity from there. But really, at the center of it are clinical outcomes and managing cost.
What are some of the trends you’ve been seeing as analytics capabilities start to grow?
I think meaningful use has prompted a wave of investment around the clinical analytics, and I think that is where a lot of people have been starting their analytics investments. They started in clinicals, but then very quickly moved into the rest of the information that was available. And I think with the change in reimbursement that’s starting in 2014, we’re really seeing an aggressive uptake in the investigation of cost and getting to the bottom of cost.
One of the other trends that we’re seeing is medical device integration. We have customers like Boston Scientific and St. Jude Medical, where we’re actually now collecting and reading data off of those medical devices, and then either adding that to their electronic health record or adding it to the analytics.
If you think you have a lot of data right now with an EHR, you have to multiply that number by about five when you start adding all the device information that people are looking at in terms of either reading their blood pressure on a daily basis, or your scale at home, or these medical devices. And all that adds to the clarity that you get around analytics because you’re looking at a dataset much, much bigger than just the core clinical information.
I see organizations attempting to standardize, and we’re absolutely advocates of standards. And then I think the exchange of information – in particular in terms of coordinating care across a continuum under an ACO umbrella will absolutely be critical.
What can we learn from other industries when it comes to collecting effective insights?
I’ve spent some time working in analytics in retail. Organizations like Target are very accustomed to using highly diverse sets of analytics. In healthcare, we have to develop technologies that are much more converse in diverse datasets and not just clinical data. If I start in clinical data, I sort of make some assumptions about all the other data to follow. And it could be social information; it could be financial information, supplies that were used, pharmaceuticals, et cetera.
I think we have a lot to learn here. In terms of best practices, where can we get started? I subscribe to the HIMSS Analytics adoption model. If you don’t have an EMR in place, if you don’t have a core set of business systems and the ability to exchange information electronically, if you still are in the paper era, I kind of think of that as the Bronze Age. And you can spend all the money you want on analytics, but you don’t have the raw materials to even start on that journey.
So, I would say these core infrastructure investments, while they’re not as exciting, they’re not analytical in nature, they are prerequisite for any analytics investment. As a result, now that we’re moving into Stage 2 Meaningful Use, I think we’re coming along. And we actually sponsored the HIMSS EMR Adoption Survey this past HIMSS conference. And we saw some pretty positive numbers in terms of the adoption of electronic medical records and the ability to exchange core clinical information.
What’s going to be a little bit challenging, and what has worked well in other industries, is that there’s going to need to be a collaboration that is different than what we’ve had in healthcare today. The insurance or financial companies in particular really moved up a notch, I think, when they started collaborating with academic institutions, as well as manufacturers, distributors, and other partners, even weather providers, to come up with much more sophisticated data analytics and really leveraging some of the new technologies available.
What are your predictions for 2014?
One thing that you’re going to see in 2014, is more of the harvesting of this passive data exhaust that patients give off. I think you’re going to start to see an advancement of our ability to leverage information either from your running app or your blood pressure cuff or medical devices, to start adding to your overall health picture.
I think the other big thing that we’re going to start seeing is really a geography-based view of information. So, analytics have very much always been about “how many over an entire population”. Now that population health has become under an ACO umbrella, I think you’re going to see analytics move from just core metric statistics to some of the geo-hotspotting that we’re starting to see. I think that’s going to be much more mainstream and much more of an expectation when it comes to new solutions.
Related White Papers: