Great Lakes Health Connect (GLHC) is one of the largest health information exchanges (HIEs) in the country. A 501(c)(3) nonprofit organization, GLHC is comprised of a network of 129 hospitals and 4,000 primary, specialty and allied care organizations, and a registry that houses more than 11 million unique patient records.
But for an HIE of this size and scope, to improve services across the state, the organization’s leaders knew they needed to remedy a disconnect that existed between provider and community-based organizations, and ensure that patient data and records could be shared easily throughout the continuum of care.
As a result, GLHC ended up adopting a technology platform—Holon Solutions’ CollaborNet platform—inclusive of three patented technologies that surface relevant patient-specific insights such as transitions, risk scores, care gaps, food insecurities or pre-authorizations for patients. GLHC leaders believe that many other care collaboration platforms on the market miss much of this relevant data. Ultimately, all this information can be sent to providers’ electronic health record (EHRs) at the point of care.
The pilot project of this collaboration was the Flint region of Michigan, which has made national headlines in recent years for its struggles with poverty and poor water quality. As detailed in this piece last year from Healthcare Innovation, working with the Greater Flint Health Coalition (GFHC) and Michigan’s State Innovation Model (SIM) program, GLHC helped link 85 providers and more than 40 community-based organizations in the Flint region, ensuring they had access to social determinants data, enabling them to provide better care in the struggling region.
Aiming to prevent ED overutilization and aligning Medicaid beneficiaries with needed care, GFHC developed a short SDOH screening survey that is administered to every beneficiary, to ask about their food, transportation, housing, substance use, water, employment and other needs. Based on those responses, providers can access CollaborNet to refer the beneficiary to the appropriate community-based organization.
Since November 2017, the GFHC SDOH screening tool, combined with the facilitated referrals through GLHC, and extensive coordination of resources, has helped the Genesee County Community Health Innovation Region—a partnership of diverse healthcare organizations—reduce ED visits among its attributed Medicaid population by 15 percent, while helping thousands of beneficiaries receive access to appropriate care and community-based services, according to the HIE’s officials.
As a whole, GLHC surpassed access to more than 1 million closed-loop referrals statewide from fall 2017 to early 2019 using the CollaborNet application, with a total of more than 3.5 million attachments shared. The point-of-care platform is accessible to more than 11,229 users at 824 different organizations across the state, including three of Michigan’s largest health systems.
Doug Dietzman, CEO of GLHC, recently discussed these efforts—and how partnering with GFHC allowed for the collection of SDOH data in an impactful way—in an interview with Healthcare Innovation. Below are excerpts of that interview.
Can you describe why the volume of data was getting so complex to manage for GLHC?
I think we have gone through a couple of HIE eras. Initially, there were a lot of interface engines that didn’t have any application functionality, per se, other than that data could be exchanged. In the early days, back in 2008 to 2010, we would hear questions such as, where is the app? Where is the MPI? Where is the longitudinal record?
So some of the vendors that we [met with] came forward with product solutions that answered the “where is the app” question, but we got to a point that in our technology transition, we needed a blend. We couldn’t just rely on apps, because as we were going to our customers, the types of integration they wanted to do were very different. For example, what a podiatrist wants is different from what a cardiologist wants, and what a hospital needs is different from a skilled nursing facility needs.
Beyond just the old ADT [admission, discharge, transfer] and lab results, you were starting to see different versions of CCDs [continuity of care documents] and query-based models. And the amount of technology and standards that were coming forward as the industry evolved were changing at a pace that some of those application vendors couldn’t keep up with. So we got some applications that we can work with [via CollaborNet], but there’s also the HIE platform/interface engine that we used to have. So we can go in and configure in some of our own capabilities to meet those customer-specific needs.
How is SDOH playing a role in all this?
There is a lot of interest in it, and like other issues in healthcare, it’s talked about it like it’s a single thing and is uniformly being done—but neither are true. For this project we were supporting—the State Innovation Model program—SDOH was a key element of it. As we get into it and spent time in our workflows out at the local level, [we wanted to know], is the data even being captured? If it is, are they asking the same questions so that if we pull the data together it means something? Can we analyze it consistently?
We were fortunate in the project we worked on, with the Greater Flint Health Coalition, from an operational standpoint, that it got the stakeholders around the table agreeing to do a common screening, which would end up with common answers. Our [network] was then the piece that could figure out whether it was an interface, or another means of getting the data from those providers, then pool it together, do the reporting and analysis, and figure out what needed to happen with these folks. Absent that process, [spearheaded] by the Greater Flint Health Coalition, it would be very hard today for an HIE or anyone else to go into a community and just have the SDOH data be available in any sort of meaningful way. We are so early on in that information being collected.
What key lessons were learned from partnering with a community-based organization?
There were two pieces to what we were doing—collecting and analyzing data so we could understand what percentage of the population of the folks we are serving said they had a water, housing, or transportation need. Beyond that, at the point those screens were being taken, if someone identified that they had [such] a need, we also would provide the close-looped referral infrastructure that was [necessary].
So we signed up the housing authorities, the water folks, and other social organizations to be part of that network. This way, we could be sure that if folks said they had a problem, we could refer to them to places where they could get their problems resolved, and then listen to the closing of the loop to determine whether we were successful or not. Those were the two ‘must-haves’ to determine the problem we were trying to solve.
