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Laying the Foundations for the New Healthcare: A Map of the New, Data-Driven Landscape

March 28, 2017
by Mark Hagland
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IT leaders at organizations like Geisinger Health, VITL, and Orlando Health are offering maps for success in laying the foundations for enterprise-wide analytics
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The Danville, Pa.-based Geisinger health System and the Burlington, Vt.-based Vermont Information Technology leaders (VITL), that state’s statewide health information exchange (HIE), are among those moving forward very rapidly, and showing the way to a new future.

At Geisinger Health, senior IT leaders, including senior vice president and CIO John Kravitz, Bipin Karunakaran, the vice president in charge of data management, and Joseph Scopelliti, IT director, data management, have been helping to lead their colleagues forward in moving to leverage data and analytics, with their major focus the creating of a Unified Data Architecture (UDA), which integrates all of the analytic platforms at Geisinger Health System. The key component of the UDA has been the creation of the Big Data (Hadoop) platform, the creation of which was the first phase of the project (in that, they say, the Armonk, N.Y.-based IBM Healthcare has been a partner). In a one-year timeframe, the team established a big-data platform, based on Hadoop and other open-source components.

What is key here has been the push on the part of the organization’s senior IT executives to facilitate robust end-user analytics self-service, a goal that has required very significant foundational IT architecting. “In the past, if data analysts wanted to do some research or analysis, they would have to request research from the data team,” Scopelliti notes. “Now, all of a sudden, with the data warehouse, they could do this themselves, and data analytics exploded, in a good way. And IBM came in and helped us with this. And we ran with that until 2012. And then we decided that we needed a different data warehouse, so we moved to a TeraData data warehouse with stronger computing capability. And we’re still running that. We have thousands of reports and dashboards that are running on clinical decision support information systems.”

Joseph Scopelliti

Ultimately, what is emerging is exactly what Kravitz, Karunakaran, Scopelliti, and their colleagues have been intending: a hyper-robust data platform that will allow for a new generation of data use, data sharing, and data analysis. Has it been hard work? Definitely, Scopelliti testifies. “Last summer,” he says, “we were putting in 10 to 12-hour days, six to seven days a week, to create the Hadoop platform. But that platform is a key component of the UDA. A colleague and I did a presentation at a conference a few months back, and we made a statement: Most people in healthcare see a big data platform as a supplement; they’re very hesitant to put all their eggs into one basket. But we see this as a replacement. We think we can retire the data warehouse, and that the UDA will effectively take its place, with most of the work being on the Hadoop platform. And our goal is to achieve that within 18 months.”

What’s more, Scopelliti says, in order to do this, “You’re taking all the traditional data warehouse sources—roughly 20, including the Epic EHR [from the Verona, Wis.-based Epic Systems Corporation], other clinical data, financial data, claims data—and channeling all those sources into the data platform. But the key is that the team wrote a data ingestion pipeline, and they wrote it in Map-Reduce and Java code. And so the idea is that it makes it very accessible—it allows us to ingest new source data very quickly. Now we have a quick way of ingesting data into the Hadoop platform. So you build the hardware infrastructure, set up the underlying code to ingest data—and now, we have the task of migrating all of the existing analytics programs into that infrastructure. My team’s primary task is the building and maintaining of the hardware and software for this program. And any new development, we’re trying to do in the new platform.”

John Kravitz

Vermont’s Comprehensive Push Forward with Actionable Data

At VITL up in Vermont, Michael Gagnon, the HIE’s chief technology officer, reports that his organization has spent several years developing the infrastructure to support robust data analytics work on the part of all of the HIE’s participant organizations. VITL, which officially opened in 2005, was born out of public-private collaboration, and that collaboration continues to fuel its pioneering work. VITL was created by the Vermont Association of Hospitals and Health Systems, in conjunction with the state government of Vermont. It now encompasses 14 hospitals, all 11 of the state’s hospital organizations, plus two hospitals in New York and one in New Hampshire, as well as 130 medical practices. “We knew that we’d be collecting data for population health early on,” Gagnon says. “Even our first HIT plan anticipated a hybrid data model between a federated model, the de rigueur model at the time, and a centralized model with a data repository that could be used for population health.”

Michael Gagnon


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