As they look to tame their data and turn it into actionable insights, many payers are significantly ramping up their data analytics strategy by building a data lake, housing both structured and unstructured data. Serving 1.5 million members, Excellus BlueCross BlueShield of New York is making significant progress on its own data lake journey. On the latest episode of our “From the Trenches” podcast, we speak with Tom Morley, manager of analytics and data strategy for Excellus. We caught up with Tom at the 2019 Health Datapalooza conference in Washington, D.C., where he took part in a panel discussion on data lake opportunities and challenges moderated by Cotiviti.
Interested in learning more? Cotiviti's Sumant Rao, senior vice president of performance analytics, offers insights into data lake opportunities and potential pitfalls to avoid in our recent white paper, "A new ecosystem for payer intelligence: How data lakes could feed insights for improved health."
| About the podcast | About our guest |
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| From the Trenches is a healthcare podcast from Cotiviti, a leader in healthcare data analytics, exploring the latest trends in healthcare quality and performance analytics, risk adjustment, payment integrity, and payer-provider collaboration. Check out all our episodes in your browser, or subscribe on your favorite apps including Apple Podcasts, Spotify, Google Play, and Stitcher. |
A couple years ago we started down the path, kind of an analytics and data transformation journey, to try and better meet the needs of the health plan from an analytics and data perspective. A big foundation for that journey was our investment in a data lake to better support both our predictive analytics and a lot of the big data needs of the health plan and of the industry.
That was a couple years ago. We've made a lot of headway in terms of investing in that technology and setting it up. We're starting to actual solve new problems in new ways using that new platform, particularly in the predictive analytics space and also with some clinical information acquisition. Our data science team, for example, right now is doing a lot around predictive member risk analytics and predicting high cost claim analytics and so forth as we ramp up and improve upon our medical management program. That's a really exciting journey that we're going on with various stakeholders throughout the health plan.
We're also partnering a lot with our health information exchanges in New York State, and a lot with the provider networks and systems that we have in New York State, to try and get our hands on real-time clinical information and how we can get that in the hands of the right people at the right time within the health plan, again to support a lot of the medical management programs that we have going on. A lot of exciting stuff.
The exciting thing is there's a lot of opportunity all over the place. I think the most exciting one personally I would say is that work surrounding the predictive analytics for the high cost claimants and to predict member risk. It's a big need within the health plan right now. We're revamping the way we manage population health. A big piece that goes into that is our ability to stratify and segment the population and understand the risk cross-population and try and match that up with the clinical programs and those who are doing the outreach and engagement with our members to drive quality care, and get the right care to the right people at the right time to ensure that they have an optimal care path and make sure that we're being as efficient as possible when it comes to costs.
As I mentioned before, we're on our data lake journey right now. New platform, new technology, new way for us to manage information. Really exciting technology, but it's also a difficult journey to try and figure out where you go with this new technology while also delivering value to the business at the same time, and also managing and getting value out of your legacy platforms as well.
As we see new opportunities that are coming through and new areas for us to partner with the rest of the health plan and the rest of the business to deliver value, trying to make those decisions around: are we doing something in the new platform, in the new world, with this new data lake? Is it something that we have to kind of rely on our old platforms for? Is it a hybrid of both? And how do we manage through that?
I think that's really the hardest piece there, but I think that we've got great leadership within the analytics and data division at Excellus and great leadership and great engagement from across the health plan. It's something that we're definitely working through.
That's where my role comes into play. That's the world that I personally live in every day. Everything that we do within the health plan, within analytics and data, it's use case-driven. We really try and engage with business stakeholders, understand their strategic roadmap, and understand where data and analytics fits in.
We ask a lot of the questions like: what insights or information do you need? What problems are you trying to solve? Who is sort of on the front lines? Who needs this information? Who needs this data? When do they need it? Why do they need it? There's a lot of engagement upfront around just asking “what is that use case” and how will information or insights help you solve your problems or help us drive better quality, help us drive better cost decisions, whatever it might be.
We use that to build out sort of a conceptual solution, or conceptual roadmap, that really gives us an understanding as to how for this particular use case we go from data and information into insights and action. It's really getting down to what's the point at which we're trying to drive action and how do we make sure that we're providing the right solutions to the right people so that they can access that information, whether it's reporting, or it's just access to pure data, or it's integration in downstream applications, whatever it might be. It's really understanding that upfront use case.
I think it might be cliché to say but, faster, cheaper, and easier to scale, I guess, in a cheaper way. But I think more importantly too—and I think we're starting to experience this now—is more engagement across the enterprise, across the health plans, for example.
Data management is not just something that lives in IT anymore, not something that just lives in an analytics and data division anymore. It's something that leaders, executives from across the health plan, have to be engaged in.
If we're managing data as a strategic asset, you have to ensure that you're optimizing the value out of that asset. That means that folks from across the enterprise, those that are data stewards, those that understand the data domains, whether it be member information or product or provider information, they have to be at the table engaging in the management and governance of the data.
I think we're starting to build that foundation now. It's critical for us to make sure that our data lake doesn't turn into a data swamp. You hear people say that a lot. I think that 10 years from now it's just going to be a part of operations. It's going to be how people do their jobs. It's going to be a priority on strategic roadmaps, not just for IT executives or A&D executives, it's going to be a priority on the roadmap for all executives across the company.