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Big Data Innovation: University of Colorado Health Sets Its Sights on Precision Healthcare

June 4, 2014
by Kayt Sukel
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University of Colorado Health leaders are harnessing big data to achieve personalized medicine

University of Colorado Health (UC Health) takes its mission to “push the boundaries of medicine” very seriously.  This young health system, an umbrella organization that encompasses the renowned academic institution, the University of Colorado Hospital, as well as existing additional health systems in Colorado Springs and Fort Collins, is investing strongly in innovative programs to deliver the best care to its patients.  And Steve Hess, UC Health’s CIO, says one of the system’s most vital investments is in the future—and the implementation of precision medicine through big data technologies.

“Big data is a term that is overused, I think.  But the way I look at it is that we have all these computer systems that are capturing and storing millions of bits of information.  When you look at all that information in whole, it doesn’t mean anything.  It’s just a lot of noise,” says Hess.  “But by building the right kind of big data engine, with the right kind of analytics, you can filter out the noise and find actionable information that allows you to deliver the right care at the right time.  That’s what we want to do.”

Steve Hess

Hess will be one of the speakers at the Health IT Summit in Denver, July 22-24, sponsored by the Institute for Health Technology Transformation (iHT2). Hess will participate in a panel discussion entitled “Health Information Exchange: A Cornerstone of Data-Driven Medicine.” (Since December 2013, iHT2 has been in partnership with Healthcare Informatics, through its parent company, the Vendome Group, LLC.)

The organization is building these kinds of tools to aggressively pursue precision medicine. “Some call it personalized medicine,” says Hess.  “But the idea is that we set up the right infrastructure in place so we can access the right data to treat people instead of diseases.  By focusing on that actionable data, we can treat patients by what we know about them from multiple perspectives, including genomic and other information, so we can individually link them to specific treatment protocols, medicines or non-medication therapies that will work for them.”

Michael Ames, associate director of Health Data Compass at UC Health, says that this project is truly unique.  UC Health is in a position to build the infrastructure from the ground up, without being hamstrung by legacy systems.  And such a green-field project leaves the organization open to planning for the future, instead of focusing solely on present needs and protocols.

“In most cases, data warehouses have been built incrementally, and each piece has been targeted for a specific project or outcome,” he says.  “One of the things we are really excited about is that we aren’t tied down by existing infrastructure.  We have a very strong collaboration between our four institutions and we’ve leveraged that to figure out what we need to build to reach our future goals.”

Ames says that, across UC Health, there are departments and researchers collecting cutting-edge and potentially pertinent data in silos for their own specific purposes.  But, if those data points are kept separate, they can’t be linked to specific patients and their health records later on when they may be needed.

“It’s an expensive proposition—taking data that may be of unknown value outside of its originating context and putting it into an unstructured database alongside the data warehouse,” he says.  “But if that data is valuable, even to one person, it’s worth it.  So we’re implementing what we call a ‘say yes’ approach to data so we’ll always have access to something that may be a catalyst for discovery later.”

Michael Kahn, M.D., Ph.D., co-director of the Colorado Clinical and Translational Sciences Institute’s Translational Informatics group, and the director of UC Health’s Enterprise Data Warehouse Project agrees.  “We are really looking at this as a platform for discovery,” he says.  “We are starting there.  And if you start there instead of at some business intelligence place, then you can really focus your attention on what it takes to get all your data in a format so that it can be part of the analytics.  It drives you into a different space—one that can really differentiate your health system and the care that it delivers.”

UC Health leaders admit that they are still in early stages of this project.  The group is currently in a “planning and preparation” phase and knows that true precision medicine is still years away from reality.  But Hess says their attempts at harnessing big data involve a true pioneer effort—and it is more than worth the time and effort to ensure that the infrastructure they build can serve patients for decades to come.

“A lot of what we’re doing hasn’t been done before.  There’s not a tried and true blueprint to follow to build this kind of system,” he says.  “There are not many organizations across the country that have the resources, money and people to be able to do something like this.  You need the faculty.  You need the researchers.  You need the grants.  You need that infrastructure.  You need some governance.  We are just at the very beginning of this but we have a lot of the necessary components in place.  And we are going to succeed.”