Thinking Really Big About Data: UPMC’s Lisa Khorey Talks About What’s Behind the Organization’s Groundbreaking Five-Year Initiative | Healthcare Informatics Magazine | Health IT | Information Technology Skip to content Skip to navigation

Thinking Really Big About Data: UPMC’s Lisa Khorey Talks About What’s Behind the Organization’s Groundbreaking Five-Year Initiative

December 3, 2012
by Mark Hagland
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Lisa Khorey shares her perspectives on UPMC’s five-year, $100 million enterprise analytics initiative

On October 1, the 20-plus-hospital University of Pittsburgh Medical Center (UPMC) health system announced a new five-year, $100 million enterprise healthcare analytics initiative to foster personalized medicine and other core strategic healthcare IT goals for the organization, partnering with several prominent vendors—Oracle, IBM, Informatica, and dbMotion.

In a press release made public on that date, the UPMC organization noted that “UPMC today announced that it intends to create a best-in-class data warehouse that brings together clinical, financial, administrative, genomic and other information that today is difficult to integrate and analyze.” The press release also included this quote from Steven D. Shapiro, M.D., UPMC’s chief medical and scientific officer: “Every patient is different; every patient has a unique story. This comprehensive analytics approach will enable us to treat each patient in a personalized way, to produce the best possible results.”

Shortly after the announcement of the initiative, HCI Editor-in-Chief Mark Hagland interviewed Lisa Khorey, vice president of enterprise systems and data management, regarding the initiative’s importance and its implications for the U.S. healthcare system. Below are excerpts from that interview.

What was the origin of this initiative, and what are UPMC’s  strategic goals in all this?

The organization aims to really bring together new models of care, based on good science and smart technology. You can look at it as a triangle, with all three elements feeding each other. And that model really works for us, because we have a very integrated organization, where we’re trying to improve quality, decrease cost, etc. We’re an integrated provider-payer system with close academic ties, and a culture of innovation. And it’s one where these goals are very present every day in our organization. So it forces an awareness of how we might be able to solve these problems.

The Center for Innovative Science, which will open in 2014, is our operational approach to good science and innovative models of care. And one of the questions we want to ask through the center is, how do we better understand medicine? So the center will basically focus on personalized medicine and on cancer and aging.

Lisa Khorey

Meanwhile, as we’ve moved forward as an organization, we have a “happy” information management problem, in that we spent ten years becoming very digital, creating a truly digital environment. And that’s terrific, but the number of vendors that it takes to solve the problem of care delivery through electronic systems requires so many participants that you end up with siloed data. Medicine is very complex in itself, and as a business, it’s very complex as well. So the consumer data set, the business data set, and the clinical data set, those are all separate sets.

And our enterprise program and agenda are about putting data to work, becoming much more actionable, being able to qualitatively measure, and to use sophisticated software and data models, to support the science agenda and the emerging models of care, and really to sum up, to become more precise in our delivery of care, which includes reducing variation. In brief, what needs to be done is to elevate relevant information and make it more available to end-users. It’s not unlike what has happened in every other industry; the challenge for medicine is that it’s the most complex data set anywhere. Our aim through this program and investment and the banner of personalized medicine, is to take all that information and data and the business problems and the information management agenda, and to put them all together, and to bring that information to life to improve patient outcomes.

Our goals are so simple; they’re as simple as a doctor talking to a patient. We want to elevate that experience to be as accurate and positive an experience as possible, and to improve the outcomes of every such encounter. So, why UPMC, why this effort? When we positioned it inside the organization and started to transform our organization to bring the different areas together—research, corporate finance, the whole provider division, and our health plan—then we looked over what we had done for the past ten years. And our investment in information technology and electronic medical records over the last decade really put us on a track to come together holistically to solve this problem together across all the lines of business; and then there’s just our science agenda, which is raising the bar on patient care. That’s why this is happening in this particular organization right now.

Might this add another layer of complexity, or will it simplify things?

In the end, it will simplify things, and things that are simple are efficient. And that’s the information management challenge, right? To simplify and harmonize. But to get to simple, you have to wade through a whole lot of complex; and that’s the biggest challenge of the program. We did spend some time looking at what had gone on before this in other organizations and other industries, and what incents people and brings value. And what’s worth even doing? Not everything that can be counted should be measured. But the most challenging part really is the “soft” things: how do you keep the executive team engaged? How do you keep the stamina of the program engaged? How do you think globally but act locally? And the most challenging part really is the blocking and tackling.

What kinds of internal teams will be involved in this initiative?

We tried not to matrix it too much. We really put together two teams. And we thought, how do we create a path between the nurse all the way up to the top of the organization? It’s a transformation project; and a whole operational structure was defined, and it follows the organization, meaning that the Institute for Personalized Medicine is the key nexus team between the University of Pittsburgh and UPMC; and there’s a provider division person, a payer division person, a finance person; so there’s a whole team of people at that second level who are empowered. And then there’s a whole set of workgroups involved, a spider web of workgroups. There will probably 20 different workgroups involved altogether. Our intention was not to govern through a bureaucracy, but actually to enable decisions to be made.

Executing across an organization as big and complex as yours is always challenging.

It is, but it’s our very size and complexity that led to this realization, that no single part of the organization could solve these problems by itself. We have lots and lots of analytics—data warehouses, business intelligence, all kinds of stuff—but they always hit a limit. There’s always some piece of data that’s missing. So if you really want to understand science and variations in patients and patient care and to find all those inefficiencies across the entire organization, then you have to look at the whole data set.

Will you be over the whole program?

I only serve in a role over the technology part of it; Dr. Steve Schapiro will be over the entirety of it.

What should our readership think about this, and do?

What we really needed to do was to stop focusing on what we would do in the next six months, and really set a north star on what we hoped to achieve in the next five years or so. We had already been deploying EHRs since 1999; and we wanted to set our focus on things a little bigger and a little further out, so that we could determine what we did not need to do. The thing is that if you just make a list, everything is really priority one, and it really paralyzes you. So focus on your north star; and then derive efficiencies from that. A lot of what we’re doing here was already here; but we just had to be a bit more inclusive. And finally, I’ve learned that everybody does not change on day one; the value will come.



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