As executive vice president for strategy and analytics, Jeff Kraut is the top ranking data officer at Northwell Health, the largest healthcare provider and private employer in New York State.
In recent years, the 21-hospital network’s shift from a fee-for-service to a performance-based business model has led to an intensive effort to gather, collate and harness data from across the sprawling 61,000-employee healthcare system.
Last week, Contributing Editor Elliot Kass caught up with Kraut on Northwell’s latest data and analytics initiatives. What follows is an edited version of that conversation.
What’s the current focus of Northwell’s analytics effort?
We’re focused on liberating our information—on taking all the siloed data that we have in the organization and deriving value from that disparate, heterogeneous information. We’re about making our data actionable and getting data we’ve never had, or couldn’t organize, and generating insights that lead to actions.
We’re looking at harnessing more of the information that’s coming in through our EMR, combining it with information we have about community health and social determinants, and bringing in more of the concept of personalized medicine. That includes understanding the genetic information that we have on our patients and how that informs and shapes clinical decision-making and treatment options.
Can you give us some context? What’s the background and overall significance of the data and analytics mission at the healthcare network?
I’ve been with the health network for 22 years. When the health system was first formed, my job was to develop a culture of using data when there were a limited number of tools and a limited amount of data available. Now, we have a wide assortment of very sophisticated tools, and a massive volume of data and information that we’re able to collect.
We’re moving from a fee-for-service, volume-based business model to a value-based system where we are held accountable for patient outcomes. We view analytics as the intersection of three major information flows:
- Clinical informatics, which include patient results, observations, medications and discharge summaries.
- Administrative informatics, including patient demographics, such as where they live, who’s treating them, their diagnosis and CPT codes.
- And data [stemming from] clinical research, which is an evolving base of knowledge that’s constantly being updated.
Our view of analytics is how we bring these three streams together to create an optimal and cost-effective patient outcome.
What’s been your team’s greatest accomplishment to date?
The movement toward population health and changing not only clinical behavior, but patient behavior as well—that’s been some of the most exciting stuff that I’ve witnessed during the past two years here.
We’ve created this understanding of accountable-care analytics that lets us identify gaps in care and the need for transitional care, complex care and advanced illness management. And we’ve shown real progress in managing our costs and utilization.
What’s been your biggest challenge?
We’re challenged by the volume and complexity of the data that’s coming in and the need for a sophisticated analysis of that data. My challenge here is that no one person is ever going to provide that for an organization—it only comes from collaboration across the enterprise.
I see my role in terms of creating a culture that permits that to occur. How do we make the data available and actionable, given the constraints that we’re under for security and privacy? And how do we use the data to differentiate ourselves in the marketplace in terms of providing a superior patient experience—and achieving a competitive and financial advantage because we’ve learned how to deliver those services more efficiently?
Getting people to appreciate and value the role of data—it’s like a religion for me.
What are the most important new technologies that you’re embracing?
We literally just flipped on Explorys [the IBM clinical data analytics platform originally developed by the Cleveland Clinic] 45 days ago, and we’ve built our own enterprise-wide data warehouse and some phenomenal tools for understanding population health.
We’ve been using some Tableau [business intelligence] tools and have designed some very sophisticated dashboards that integrate a lot of our data and make it actionable, particularly with regard to managing high-risk populations.
Drawing on your experience, what advice would you offer other chief data officers and informatics executives?
The job of the chief data officer is to break down the silos, remove roadblocks to innovation and help move this whole thing along with a degree of urgency that can only occur if the CDO has a direct link into the senior leadership group, which has to buy in and support that individual.
If you’re the kind of person who wants to control all the flows and make all the decisions—I don’t think that’s going to work given the speed at which an organization has to move or the challenges that it has to overcome to get to that next level.
The best chief data officers are going to hire people who are smarter than they are, who know more than they do and who create an environment that is collaborative, team-based and geared toward supporting the people who are on the front lines [of the business].
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