The Danville, Pa.-based Geisinger Health System is an integrated health system that serves more than 3 million residents across 45 counties in central, south-central and northeast Pennsylvania, and a part of southern New Jersey (with its acquisition in October 2015 of the Atlantic City, N.J.-based AtlantiCare health system). In the fiscal year ending June 30, 2015, Geisinger documented an operating profit of $160 million on $4.56 billion in revenues, while AtlantiCare’s operating profit in calendar year 2014 was $43.7 million on revenues of $805.3 million.
The physician-led system is comprised of approximately 30,000 employees, including nearly 1,600 employed physicians, 12 hospital campuses, two research centers and a 510,000-member health plan, all of which leverage an estimated $8.9 billion positive impact on the Pennsylvania economy. Geisinger has repeatedly garnered national accolades for integration, quality and service.
Geisinger continues forward in numerous areas as a pioneer, including in the leveraging of data analytics and the ongoing expansion of population health work. Nick Marko, M.D., a practicing neurosurgical oncologist and the health system’s chief data officer, spoke last month with HCI Editor-in-Chief Mark Hagland about the data infrastructure that the health system is architecting in order to support continuous clinical performance improvement.
Meanwhile, also last month, John M. Kravitz, senior vice president and CIO at Geisinger, spoke at the Health IT Summit in Cleveland regarding the health system’s transition from the use of an enterprise data warehouse to creating big-data platforms. Recently, Kravitz, who became CIO nearly four months ago (he had been an associate CIO previously, and has been at the health system for six-and-a-half years), spoke individually with Hagland about that transition and about the broader context of Geisinger’s current initiatives. Below are excerpts from that interview.
Geisinger continues to be a real pioneer in the industry. Given that, you’ve got a lot on your plate, as CIO. How do you see your role right now, and what are your priorities?
We’ve got a number of new initiatives—some of the things you’ve seen with regard to our big data platforms, with the goal of moving decision-making to real-time. A lot of our work with the enterprise data warehouse has been around same-day availability of data, to look for gaps in care and respective issues we want to help resolve. But going forward, we want to do it in real-time, as I said at the conference. We want our patients using iOS-type devices like iPads, in waiting rooms, and we want them to enter questions based on their condition, so that ultimately, we can take that data and churn it very quickly within a matter of seconds, and provide them with data for analysis and decision-making.
John M. Kravitz
Could you provide an example of this?
Let’s take a patient has diabetes, for example. With diabetes, you typically have a couple of key performance indicators (KPIs)—one is your hemoglobin a1c, which is a bloodwork-based exam; others can include a foot exam, an eye exam, etc. In the old world, we’d have our enterprise data warehouse, which would churn the data and look to see if a patient hadn’t had an a1c test or foot or eye exam recently, for example, so an order would run the next time they are seen again, by a PCP, an endocrinologist, or in the ED. The order would be programmatically, automatically done, via a care gaps analysis.
Now, going forward, what we’re planning by September or October of this year, is to be able to use a tool called DatStat—it’s a very user-friendly tool that actually resides on an iOS device on an iPad. We would give the patient an iPad in the waiting room, in this case, for diabetes. How are you feeling? Have energy? Tired or listless? Etc. And the key thing is that we have data from our Epic system, or lab system, or documented results from prior visits. So when they’re answering the survey and hitting the button, it would update Epic with that day’s episode of care. And with the big-data, Hadoop platform, we’ll be able to churn that data in seconds, automatically. The only manual intervention involved would be handing the patient the iPad. So that’s one of the initiatives we have going. We call it CareGaps. This is one of the ways in which we’re trying to close out those gaps in care.
And we have them for a number of conditions—CHF [congestive heart failure], COPD [chronic obstructive pulmonary disease], CAD [coronary artery disease], and asthma; and we also have them for rheumatoid arthritis and a lot of other chronic illnesses. And the concept is, collect the data in the waiting room.
And perhaps you could share another example of a high-priority focus for you and your organization?
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