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Top Ten Tech Trends 2017: Health Systems Find Partners for Multi-Sector Data Sharing

March 21, 2017
by David Raths
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Using the EHRs to gather social determinant data
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“Deep learning” is probably the hottest term in healthcare these days, but coming in a close second might be “social determinants of health.” What economic and regulatory forces are making health systems focus their energy on gathering data on social determinants and share data more broadly across sectors?

One is the transition away from a fee-for-service payment system to one that rewards providers for the value of care they offer, which adds a level of accountability. “That has created a pretty dramatic awakening for those in a position to be receptive, in that they control only a very narrow portion of an individual’s or a population’s health,” says Alison Rein, senior director of evidence generation and translation for Academy Health in Washington, D.C. Rein leads the Community Health Peer (CHP) Learning Program, a partnership with the Office of the National Coordinator for Health IT (ONC) to establish a national peer learning collaborative of 15 communities to address specified population health management challenges through increased sharing and use of electronic data.

Alison Rein

Health systems don’t have as big an impact as they think they do on the real things that drive cost, Rein says. Instead, she says, “They need to figure out how to work with others outside their system if they really want to thrive in a few years. It is no longer OK to spend an increasing proportion of our gross domestic products on healthcare services without getting any better outcomes.”


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Some providers have started by focusing on the social needs of “high utilizers” or “familiar faces” in the emergency room. That spotlight helps people to understand social determinants as a concept, but the place where the ultimate return on investment will be is further down the line, says Peter Eckart, co-director of Data Across Sectors for Health (DASH), which was launched by the Robert Wood Johnson Foundation to identify barriers, opportunities, promising practices and indicators of progress for multi-sector collaborations to connect information systems and share data for community health improvement.

CHP and DASH have joined forces with a few other efforts to create All In: Data for Community Health, which is helping communities build capacity to address the social determinants of health through multi-sector data sharing collaborations. Together, All In represents the insights from 50 community collaborations across the country.

Peter Eckart

Eckart says All In’s work is experimental. “We believe it to be true that a focus on the social determinants gives us a more complete picture of what is happening to individuals and communities. But it has been hard to make a return-on-investment argument because there have not been enough places where it has been tried. That is why our work exists.”

Collecting social determinant data in the electronic health record (EHR) at the point of care is another challenge being addressed in several projects.

Building Social Determinant Tools into EHRs

Jennifer DeVoe, M.D., chair of the Department of Family Medicine at Oregon Health Sciences University in Portland, is working on pilot projects to gather social determinant data in the EHR. She says a primary care team sees people often and can identify some of these needs.

“We are looking at ways to use that data to help us identify people at risk and trigger referrals,” she explains. “As a primary care physician, I can identify a patient who has a cardiovascular condition and who might need to be referred to a cardiologist, and I can put that consult into my EHR, and hopefully information flows back to me,” she says. “The analogy would be in partnering with social service agencies and others who address a patient’s social vulnerabilities. Certainly it is not as easy as referring a homeless patient to a housing service, but it is a first step.”

She says her team also has experimented with a set of community vital signs. By bringing those into the EHR, they could know who is living in an area that is vulnerable and potentially act on that information.

Jennifer DeVoe, M.D.

Devoe calls this area of research very nascent, but she believes it has incredible potential. “Zip code is more predictive of health outcomes than genetic code is,” she says.  “After collecting this information in the EHR, the next step for us is figuring out how to partner more effectively with the larger communities of organizations.”

Andrew Hamilton, chief informatics officer and deputy director of the Alliance of Chicago Community Health Services, is working on another EHR-related project sponsored by the National Association of Community Health Centers. The goal of PRAPARE (Protocol to Respond to and Assess Patient Assets, Risks, and Experiences) is to create and implement a national standardized patient risk assessment protocol to assess and address patients’ social determinants of health.

The Alliance helped develop questions in the protocol and built the tool in the EHR so that it could be collected in the clinical workflow. They also structured the data so it could be used for reporting and analysis. “Some of the data elements we wanted, such as level of educational attainment, were new to the work flow and new to the EHR collection, so they required thinking about where to put the fields. We didn’t want to haphazardly start adding fields to databases.”

One issue each clinic in the pilot had to work through was which staff members they wanted gathering the social determinant data from the patient and how to explain to patients why this new data is being gathered.

Andrew Hamilton

“Now that we have identified sustainable strategies to collect these data,” Hamilton says, “the next phase of our work is focused on how we use the data to enrich the plan of care. That includes referrals we might make to community service providers that can help patients address those concerns, particularly around transportation, housing and legal aid. Another goal is to use the data at an aggregate level in a community to talk with public health authorities and other interested stakeholders about things that the community might need to invest in.”

Role for HIEs

Some regional health information organizations are playing a role in social determinant projects, Eckart says. Altair Accountable Care for People with Disabilities is a DASH grantee that, with funding and leadership from Lutheran Social Services of Minnesota, is integrating behavioral health providers into the regional health information exchange to improve care coordination for patients with disabilities. “These behavioral health organizations are working with the HIE to move from competing with each other to collaborating with each other,” Eckart says.

In another example, a program led by Baltimore City Health Department includes CRISP (Maryland’s HIE), community-based organizations and nonprofits, and faculty at Johns Hopkins and the University of Maryland. They are leading a citywide effort to reduce falls among residents age 65 and older. They are creating a real-time data surveillance system that will track fall-related emergency department visits and hospitalizations. The project is also integrating core medical data with other health, housing, environmental and social service data related to fall risks. “The relationship between the health department and HIE is an important part of what they are doing, in terms of using multi-sector and city data and health data provided by CRISP as a way to hot-spot falls in the city,” Eckart explains.

In a CHP-supported project in Southwest Washington state, the Providence Center for Outcomes Research and Education is building a shared data system that will aggregate public records, insurance claims, and public health data for community-based population health management. They will conduct a multi-sector analysis that brings together data on healthcare encounters, housing assistance, school attendance, and corrections to identify at-risk populations.

“These projects are starting to allow communities to generate hypotheses and explore the impact of what they are doing,” Rein says.

Rein and Eckart say all the organizations they support have to work through technical and policy issues around consent and data sharing. Another level of difficulty is that many of the organizations don’t see themselves as data holders or curators or even connected to health, Rein adds. “As with any health IT effort, there are sociocultural dimensions. There are strong governance and business dimensions. I tend to think of interoperability requiring alignment across all those things, including business process alignment. We have found that the smaller the project, in terms of the number of entities, the more likely it is that they can come together around a common vision and establish lines of communication, and shared interest and the accountability to make it happen.”

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NCQA Moves Into the Population Health Sphere With Two New Programs

December 10, 2018
by Mark Hagland, Editor-in-Chief
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The NCQA announced on Monday that it was expanding its reach to encompass the measurement of population health management programs

The NCQA (National Committee for Quality Assurance), the Washington, D.C.-based not-for-profit organization best known for its managed health plan quality measurement work, announced on Dec. 10 that it was expanding its reach to encompass the population health movement, through two new programs. In a press release released on Monday afternoon, the NCQA announced that, “As part of its mission to improve the quality of health care, the National Committee for Quality Assurance (NCQA) is launching two new programs. Population Health Program Accreditation assesses how an organization applies population health concepts to programs for a defined population. Population Health Management Prevalidation reviews health IT solutions to determine their ability to support population health management functions.”

“The Population Health Management Programs suite moves us into greater alignment with the focus on person-centered population health management,” said Margaret E. O’Kane, NCQA’s president, in a statement in the press release. “Not only does it add value to existing quality improvement efforts, it also demonstrates an organization’s highest level of commitment to improving the quality of care that meets people’s needs.”

As the press release noted, “The Population Health Program Accreditation standards provide a framework for organizations to align with evidence-based care, become more efficient and better at managing complex needs. This helps keep individuals healthier by controlling risks and preventing unnecessary costs. The program evaluates organizations in: data integration; population assessment; population segmentation; targeted interventions; practitioner support; measurement and quality improvement.”

Further, the press release notes that organizations that apply for accreditation can “improve person-centered care… improve operational efficiency… support contracting needs… [and] provide added value.”

Meanwhile, “Population Health Management Prevalidation evaluates health IT systems and identifies functionality that supports or meets NCQA standards for population health management. Prevalidation increases a program’s value to NCQA-Accredited organizations and assures current and potential customers that health IT solutions support their goals. The program evaluates solutions on up to four areas: data integration; population assessment; segmentation; case management systems.”



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At the D.C. Department of Health Care Finance, Digging into Data Issues to Collaborate Across Healthcare

November 22, 2018
by Mark Hagland, Editor-in-Chief
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The D.C. Department of Health Care of Finance’s Kerda DeHaan shares her perspectives on data management for healthcare collaboration

Collaboration is taking place more and more across different types of healthcare entities these days—not only between hospitals and health insurers, for example, but also very much between local government entities on the one hand, and both providers (hospitals and physicians) and managed Medicaid plans, as well.

Among those government agencies moving forward to engage more fully with providers and provider organizations is the District of Columbia Department of Health Care Finance (DHCF), which is working across numerous lines in order to improve both the care management and cost profiles of care delivery for Medicaid recipients in Washington, D.C.

The work that Kerda DeHaan, a management analyst with the D.C. Department of Health Care, is helping to lead with colleagues in her area is ongoing, and involves multiple elements, including data management, project management, and health information exchange. DeHaan spoke recently with Healthcare Informatics Editor-in-Chief Mark Hagland regarding this ongoing work. Below are excerpts from that interview.

You’re involved in a number of data management-related types of work right now, correct?

Yes. Among other things, we’re in the midst of building our Medicaid data warehouse; we’ve been going through the independent validation and verification (IVV) process with CMS [the federal Centers for Medicare and Medicaid Services]. We’ve been working with HealthEC, incorporating all of our Medicaid claims data into their platform. So we are creating endless reports.


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Kerda DeHaan

We track utilization, cost, we track on the managed health plan side the capitation payments we pay them versus MLR [medical loss ratio data]; our fraud and abuse team has been making great use of it. They’ve identified $8 million in costs from beneficiaries no longer in the District of Columbia, but who’ve remained on our rolls. And for the reconciliation of our payments, we can use the data warehouse for our payments. Previously, we’d have to get a report from the MMIS [Medicaid management information system] vendor, in order to [match and verify data]. With HealthEC, we’ve got a 3D analytics platform that we’re using, and we’ve saved money in identifying the beneficiaries who should not be on the rolls, and improved the time it takes for us to process payments, and we can now more closely track MCO [managed care organization] payments—the capitation payments.

That involves a very high volume of healthcare payments, correct?

Yes. For every beneficiary, we pay the managed care organizations a certain amount of money every month to handle the care for that beneficiary. We’ve got 190,000 people covered. And the MCOs report to us what the provider payments were, on a monthly basis. Now we can track better what the MCOs are spending to pay the providers. The dashboard makes it much easier to track those payments. It’s improved our overall functioning.

We have over 250,000 between managed care and FFS. Managed care 190,000, FFS, around 60,000. We also manage the Alliance population—that’s another program that the district has for individuals who are legal non-citizen residents.

What are the underlying functional challenges in this area of data management?

Before we’d implemented the data warehouse, we had to rely on our data analysis and research division to run all the reports for us. We’d have to put in a data request and hope for results within a week. This allows anyone in the agency to run their own reports and get access to data. And they’re really backed up: they do both internal and external data reports. And so you could be waiting for a while, especially during the time of the year when we have budget questions; and anything the director might want would be their top priority.

So now, the concern is, having everyone understand what they’re seeing, and looking at the data in the same way, and standardizing what they’re meaning; before, we couldn’t even get access.

Has budget been an issue?

So far, budget has not been an issue; I know the warehouse cost more than originally anticipated; but we haven’t had any constraints so far.

What are the lessons learned so far in going through a process like this?

One big lesson was that, in the beginning, we didn’t really understand the scope of what really needed to happen. So it was underfunded initially just because there wasn’t a clear understanding of how to accomplish this project. So the first lesson would be, to do more analysis upfront, to really understand the requirements. But in a lot of cases, we feel the pressure to move ahead.

Second, you really need strong project management from the outset. There was a time when we didn’t have the appropriate resources applied to this. And, just as when you’re building a house, one thing needs to happen before another, we were trying to do too many things simultaneously at the time.

Ultimately, where is this going for your organization in the next few years?

What we’re hoping is that this would be incorporated into our health information exchange. We have a separate project for that, utilizing the claims data in our warehouse to share it with providers. We’d like to improve on that, so there’s sharing between what’s in the electronic health record, and claims. So there’s an effort to access the EHR [electronic health record] data, especially from the FQHCs [federally qualified health centers] that we work closely with, and expanding out from there. The data warehouse is quite capable of ingesting that information. Some paperwork has to be worked through, to facilitate that. And then, ultimately, helping providers see their own performance. So as we move towards more value-based arrangements—and we already have P4P with some of the MCOs, FQHCs, and nursing homes—they’ll be able to track their own performance, and see what we’re seeing, all in real time. So that’s the long-term goal.

With regard to pulling EHR information from the FQHCs, have there been some process issues involved?

Yes, absolutely. There have been quite a few process issues in general, and sometimes, it comes down to other organizations requiring us to help them procure whatever systems they might need to connect to us, which we’re not against doing, but those things take time. And then there’s the ownership piece: can we trust the data? But for the most part, especially with the FHQCs and some of our sister agencies, we’re getting to the point where everyone sees it as a win-wing, and there’s enough of a consensus in order to move forward.

What might CIOs and CMIOs think about, around all this, especially around the potential for collaboration with government agencies like yours?

Ideally, we’d like for hospitals to partner with us and our managed care organizations in solving some of these issues in healthcare, including the cost of emergency department care, and so on. That would be the biggest thing. Right now, and this is not a secret, a couple of our hospital systems in the District are hoping to hold out for better contracts with our managed care organizations, and 80 percent of our beneficiaries are served by those MCOs. So we’d like to understand that we’re trying to help folks who need care, and not focus so much on the revenues involved. We’re over 96-percent insured now in the District. So there’s probably enough to go around, so we’d love for them to move forward with us collaboratively. And we have to ponder whether we should encourage the development and participation in ACOs, including among our FQHCs. Things have to be seen as helping our beneficiaries.

What does the future of data management for population health and care management, look like to you, in the next several years?

For us in the District, the future is going to be not only a robust warehouse that includes claims information, vital records information, and EHR data, but also, more connectivity with our community partners, and forming more of a robust referral network, so that if one agency sees someone who has a problem, say, with housing, they can immediately send the referral, seamlessly through the system, to get care. We’re looking at it as very inter-connected. You can develop a pretty good snapshot, based on a variety of sources.

The social determinants of health are clearly a big element in all this; and you’re already focused on those, obviously.

Yes, we are very focused on those; we’re just very limited in terms of our access to that data. We’re working with our human services and public health agencies, to improve access. And I should mention a big initiative within the Department of Health Care Finance: we have two health home programs, one for people with serious mental illness issues, the other with chronic conditions. The Department of Behavioral Health manages the first, and the Department of Health Care Finance, my agency, DC Medicaid, manages the second. You have to have three or more chronic conditions in order to qualify.

We have partnerships with 12 providers, in those, mostly FQHCs, a few community providers, and a couple of hospital systems. We’ve been using another module from HealthEC for those programs. We need to get permission to have external users to come in; but at that point, they’d be able to capture a lot of the social determinants as well. We feel we’re a bit closer to the providers, in that sense, since they work closely with the beneficiaries. And we’ve got a technical assistance grant to help them understand how to incorporate this kind of care management into their practice, to move into a value-based planning mode. That’s a big effort. We’re just now developing our performance measures on that, to see how we’ve been doing. It’s been live for about a year. It’s called MyHealth GPS, Guiding Patients to Services. And we’re using the HealthEC Care Manager Module, which we call the Care Coordination Navigation Program; it’s a case management system. Also, we do plan to expand that to incorporate medication therapy management. We have a pharmacist on board who will be using part of that care management module to manage his side of things.



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