Geisinger’s Nick Marko, M.D.: What It Takes to Build a Data Infrastructure for Continuous Clinical Performance Improvement | Healthcare Informatics Magazine | Health IT | Information Technology Skip to content Skip to navigation

Geisinger’s Nick Marko, M.D.: What It Takes to Build a Data Infrastructure for Continuous Clinical Performance Improvement

May 7, 2016
by Mark Hagland
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Geisinger’s Nick Marko, M.D., shares insights on the creation of data infrastructures to support clinical performance improvement

Nick Marko, M.D., a practicing neurosurgical oncologist, is chief data officer at the Danville, Pa.-based Geisinger Health System. Dr. Marko arrived at Geisinger three years ago, following the conclusion of his residency and two fellowships, and has been practicing neurosurgical oncology since then. Two years ago, after leading… he was named chief data officer at the integrated health system, which is renowned for its innovative work in clinical performance improvement, including its ProvenCare program, which was created and nurtured under the aegis of former CEO Glen Steele, Jr., M.D., Ph.D.

Dr. Marko spoke recently with HCI Editor-in-Chief Mark Hagland regarding the advances that he and his colleagues have been making in leveraging data to improve clinical performance, organization-wide, at Geisinger, which encompasses 12 hospital campuses, two research centers, 30,000 employees including nearly 1,600 employed physicians, and a 510,000-member health plan, and which as an integrated delivery system serves more than 3 million residents through 45 counties in central Pennsylvania. Below are excerpts from that interview.

Geisinger has a wonderful legacy as an innovator in so many areas around clinical performance improvement and evidence-based medicine. What is the landscape now at the organization for leveraging data for clinical performance improvement?

I think the appetite for using data and information for providing excellent clinical care and an excellent patient experience is as strong as it’s ever been. What has evolved over time is a couple of things. One, we’re seeing the evolution of our data-driven quality innovations going from a series of one-offs or use-case scenarios, to where we’re really trying to build at scale. So when you look at our ProvenCare programs and other population health programs, we’ve been pretty successful at using data to improve care and processes in individual situations. The next logical step is of course taking that approach and making it just the way we do business, right? And I think the first real hurdle for any organization that wants to do that is that you’ve got to have a culture that embraces and looks at data.

And that’s non-trivial in healthcare. A generation ago, the way physicians were trained was individualistic and worked against that. And to some extent, the evidence-based literature movement really pushed towards moving away from the individual experiences of physicians and towards the collective experiences of many. And becoming a data-driven organization is part of the fruition of that. We’ve taken a step beyond just evidence-based medicine and meta analytics, to taking raw data from patients and looking at the data in real time and on the fly. So it’s not just, what one answer can I get to one question based on meta-analysis, but, how can I do this all the time?

So medicine is evolving towards that, and the way that Geisinger is evolving forward, is evolving towards that. So a data-driven culture is really part of Geisinger’s DNA now. And that’s great, because it makes it much easier for people like me to do what we do. If you have to constantly convince people that looking at data is a good thing, then that takes up 80 percent of your life. Now, that doesn’t mean we don’t have challenges: getting the right data into the hands of the right people at the right time, and making sure to maximize our resources around data use, and how we do this at scale, all remain challenges. And the scale issue is one of my biggest challenges. You can end up with 100 one-off solutions [in leveraging data and analytics to do clinical performance improvement work]. But if you’re really going to have it be truly a part of what you do every day, you have to build a stable backbone, because you can’t keep pace with one-offs; managing one-offs doesn’t scale.

So we’re working towards using our own long history of data here, tying into the best available data.

In other words, a complete end-user-capable data infrastructure?

Yes, and a culture that supports that. And similarly, you can have a ton of people who want to use information, but if they don’t have the back-end capability of using the systems, they won’t be able to use the data. So we have to live and breathe information in everything we do all the time.

What has it been like being a specialist physician in a position that is most commonly held by a PCP? How has being a specialist been different for you?

Yes; the data-driven, evidence-based culture, has largely been dominated by people in primary care. And that largely has been logistically driven. Those people can do clinic on Mondays and IT on Tuesday, for example. For us, we kind of have to be available at any time. I’m lucky that people here understand that my patients have to come first, and my schedule will be unpredictable, and people don’t look down on that.

You’d think that they’d be thrilled to have a specialist involved, right?

Yes, they are, but it’s a little bit like marrying a doctor and finding it out it’s different from what you thought! So the organization has to be accommodating, and the other thing is, the organization that specialists are more expensive. So they have to be willing to subsidize you at the specialty rate, because specialists just won’t take a gigantic pay cut. And we’re all doctors, but we have to have a skill set that contributes here. So you’ve got to have that organizational physician.


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