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One CIO’s Journey into Accountable Care: Baystate Health’s Vengco Offers His Insights (Part 1)

September 11, 2015
by Mark Hagland
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Joel Vengco, vice president and CIO of Baystate Health, shares his insights on ACO development work for a six-hospital health system

Accountable care organization (ACO) work continues to move forward at the Springfield, Massachusetts-based Baystate Health, a six-hospital health system serving large swaths of western Massachusetts. Anchored by flagship facility Baystate Medical Center in Springfield, the health system encompasses six hospitals, 80 medical groups, and its own health plan, Health New England, which has 200,000 members. Baystate Health serves 900,000 patients across four counties.

Meanwhile, Baystate Health joined the Medicare Shared Savings Program for ACOs in 2012, with its Pioneer Valley Accountable Care organization, or PVAC, which encompasses 90,000 lives. Joel Vengco, vice president and CIO at Baystate Health, spoke recently with HCI Editor-in-Chief Mark Hagland regarding his organization’s experiences to date with accountable care-driven care delivery. In this first part of a two-part interview, Vengco shares his insights on the early phases of ACO development.

Tell us a bit about your MSSP ACO.

It’s called Pioneer Valley Accountable Care, or PVAC. We started in 2012 with the other MSSP ACOs. Our Medicare ACO serves roughly 90,000 covered lives. We’re going to be pushing that above 120,000 this year. We we’ve seen some fairly decent savings.

Joel Vengco

Have you received shared savings back from Medicare?

The first year, we saved roughly $2.5-3 million. The next year, we increased that a bit, but were still around 1.5 percent savings for Medicare, and you have to hit 2-percent savings to get savings back. We haven’t quite gotten to that threshold yet.

What have been your biggest learnings so far in your participation in the Medicare Shared Savings Program?

Obviously, the first big hurdle is just really creating the necessary environment for collaboration across the continuum of care and the region. Part of what’s challenging about this environment is that you don’t own all the physicians, and yet everyone is responsible for that patient population, and is sharing both the expense, and the benefit if you do it right. So a lot of it has to do with sharing that infrastructure—everything from a governance structure, to the policies and procedures around information-sharing, and secure communications, to analytics that enable you to actually track the progress of your ACO. So it’s really back to the basics of collaboration, which is in many ways a fundamental principle, but is also sophisticated and complex with regard to an operation like that.

A lot of organizations are still having problems with attribution. Are you still?

Oh, sure. We do it [successful attribution], but it’s very manual. And our systems are still not quite at the level that they need to be at in order to manage attribution at a satisfactory level. Our data requires a lot of cleansing, because the systems are still in many ways dis-integrated. So it’s still hard to tell which payer or primary care physician a patient is associated with. We’re talking about dual-eligibles in that case.

And there are all sorts of risk elements that make tracking fairly complex, for those who are in this space.

What have your learnings been around the leveraging of analytics for population health in the ACO context?

So to start at the beginning, the biggest challenge at the outset is the liberation of data from various EHR [electronic health record] systems, various registration/scheduling (“reg-schedge”) systems, and all these require analytics to attribute a patient to a PCP and stratify that patient. So we’ve just recently gotten over the hump around the basic extraction issues. We’ve now gotten more data than we have over the past two years; we’re now working with a vendor partner that is developing an EDW for us. We’ve got a variety of analytics that we can start to run now.

But the first challenge, and the first learning around it, is that you’ve got to pull that data out of the EHR, and then normalize and cleanse it and aggregate that data if you’ve got multiple systems across your organization, and standardize it, to get a comprehensive view of the patient. So if you extract data from your EHR and your reg/schedge, and those are different, and associating patients to their providers is a very basic, fundamental thing to do, but it’s actually not as easy as one would think. A patient is not always associated with the correct PCP. So it becomes an ongoing thing. But the lesson here is that you have to take your time in curating and normalizing and standardizing the data, so that your analytics will be as precise as you can make them. Stratification becomes possible when predictive modeling becomes possible, but only when you’re able to extract the data and normalize it. That’s number one.

Number two is, creating reports and dashboards is great, but if you can’t make the data actionable by clinicians, it’s for naught. If you’re not able to give them something they can really use to manage their population, it’s a waste of time. So the challenge is, how do you make these analytics packages and reports, upfront and center, for the clinicians to make actionable?

And how do you do that? What turns the key for physicians and other end-users of this data and information?


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