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What Can We Learn From Oregon’s Innovative Medicaid Experiment?

April 11, 2017
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Oregon’s Medicaid reform experiment has demonstrated innovation in care management

The March issue of Health Affairs carries a range of noteworthy articles under that issue’s theme of “Delivery System Innovation.”

One of the articles I found most compelling was “Oregon’s Medicaid Reform And Transition To Global Budgets Were Associated With Reductions In Expenditures,” by K. John McConnell, Stephanie Renfro, Richard C. Lindrooth, Deborah J. Cohen, Neal T. Wallace, and Michael E. Chernew. As those authors noted, “In 2012, Oregon initiated one of the nation’s most ambitious Medicaid delivery system reform efforts, creating 16 coordinated care organizations (CCOs) to care for 90 percent of its Medicaid enrollees. CCOs can be considered a type of accountable care organization (ACO), acting as regional entities that are accountable for healthcare quality and spending of a defined population.”

And this is a population at high risk, with many Medicaid enrollees either homeless or on the verge of homelessness; having multiple chronic illnesses, and long histories of poor health; and, of course, living in poverty, with all the challenges and complications that poverty poses. So it was fascinating to read this article, based on its authors’ thorough study of Medicaid managed care programs in Oregon and in Washington state. And here’s the thing: some of the innovations taking place in those two states, but most especially in Oregon, have really made a difference in managing the care of the Medicaid populations there, with implications not only for the managers of Medicaid programs nationwide, but for the leaders of the healthcare system overall, including for how healthcare IT leaders should be thinking about the data and information systems that will be needed for successful population health initiatives in going forward.

“Two years into its implementation,” the researchers write, “Oregon’s coordinated care organization model was associated with reductions in standardized expenditures for evaluation and management, procedures, tests, and inpatient services relative to Washington State’s Medicaid program. These reductions would be equivalent to savings of approximately 7 percentage points across the five service areas examined. The largest reductions were observed in the use of inpatient hospitalization. ED visits, which had been targeted through high-profile initiatives in each state, declined in both states, which no significant difference in the two-year average.”

The article’s authors do note that “Standardized expenditures for evaluation and management visits grew less in Oregon relative to Washington, a finding consistent with our analysis of primary care use. Primary care visits increased in Washington but declined in Oregon, even though Oregon’s CCO model emphasized enrollment in a ‘primary care home’ and other primary care access measures… This differential might reflect tightening primary care capacity in Oregon, potentially exacerbated by the 2014 Medicaid expansion,” which they note increased monthly enrollment by more than 450,000 people, or 84 percent.

Now, here’s the absolutely key section of this article: “Although markers of access decreased in Oregon, the state also reduced inpatient days, ED visits (overall and avoidable), and preventable hospitalizations. There are several possible explanations for these changes. First, CCOs engaged in a variety of nontraditional support services and transition programs that may have accounted for the reduction in ED and inpatient services, even if primary care visits went down. For example, CCOs substantially increased their use of community health workers, social workers, and care coordinators to engage their Medicaid enrollees outside of the clinical setting. These programs typically targeted adults and patients with multiple comorbidities, consistent with our finding that savings were primarily attributable to these groups. Second, the CCO model includes flexibility to spend on health-related services that are not part of the traditional ‘medically necessary’ medical care system. Thus, CCOs may have identified mechanisms to improve care and reduce spending, even if office visits for primary care decreased. For example, a recent study of supportive housing initiated with the CCO reform found reductions in overall healthcare use and expenditures among homeless people enrolled in the program.” Yes.

So what has happened in Oregon and in Washington state, but particularly in Oregon, is important, and very much worth reflecting on. To begin with these coordinated care organizations, or CCOs, have obviously been an absolutely critical success factor both in reducing utilization and resources, and in improving outcomes, among the Medicaid populations of those states. It goes without saying that these are needy individuals; they not only often have medical needs—including, frequently, multiple chronic illnesses—they also have intensive psychosocial and socioeconomic needs and issues. Some are homeless, others, teetering on the verge of homelessness. Many suffer from a lack of healthcare literacy. And nearly all are in need of psychosocial support and of services that are not purely medical in nature, as well as of course of medical services.

Not surprisingly, these Medicaid recipients can benefit tremendously from innovative approaches to care management and social service support, just as members of commercial health plans can. Indeed, given their often-fragile personal status, such care management and support are needed even more by this historically underserved population.


And here’s the key nugget: “CCOs substantially increased their use of community health workers, social workers, and care coordinators to engage their Medicaid enrollees outside of the clinical setting. These programs typically targeted adults and patients with multiple comorbidities, consistent with our finding that savings were primarily attributable to these groups.” In other words, care management becomes a form of social-care management that extends out far beyond the typical, relatively brief primary care visit in the clinic. And, the CCO model allows for care managers to spend flexibly in areas like supportive housing, where such spending can actually end up reducing overall healthcare resource utilization, even though the expenditures will not strictly be for clinical items.

None of this is absolutely new, of course. Back in the 1990s, I wrote about pioneering programs, including at Medica Health Plan in Minneapolis, that were helping to improve the health status of so-called “dual eligibles” (individuals eligible for both Medicare and Medicaid coverage), individuals who tend to be both poor and older, and often frail. Medica’s senior care managers and clinician leaders often uncovered gaps in what are called the “social determinants of health,” that definitely were not “clinical” in nature, but which had tremendous clinical implications. For example, that health plan often paid for things like installing handrails in hallways in the homes of dual-eligible members. Clearly, a handrail is far from “clinical” in nature; and yet if installing a handrail can avert a fall, which in most elderly people can be potentially devastating—and lead to a cascade of costs and expenditures that will be clinical—shouldn’t care managers go ahead and install that handrail?

This is the non-secret “secret” that has long been known among care managers working in the trenches in U.S. healthcare: that the vast majority of elements that impact the personal health of individuals are not strictly clinical in nature, but rather psychosocial, sociodemographic, and socioeconomic, and related both to the choices that individuals make in their lives, as well as to the social and economic environments in which they live and which they navigate.

And as I’ve long said, if care management can work for people in the Medicaid context, in which resources are constrained and needs are high, then it can work anywhere. And this new study proves it. What’s more, it’s clear that extending the concept of care management beyond strictly medical management, will require investment in very extensive information systems and in data analytics, in order to collect, store, manage, analyze, and use data that is far more expansive than the purely clinical data that currently exists in electronic health records and other clinical information systems in patient care organizations. For healthcare IT leaders nationwide, that will mean rethinking data itself—what kinds of data are needed, where they’re needed, and how data from very, very disparate systems can really be connected, for effectiveness in genuine population health work going forward.

So, yes—we absolutely can learn from the Medicaid reform initiatives in Oregon and Washington. I would urge everyone to read this article and consider its implications, because what’s happening in those states is where U.S. healthcare is headed—not only all the state Medicaid programs, but Medicare- and commercial health plan-based care and care management as well. And as I say, if they can accomplish these advances in Medicaid programs, it will be possible just about anywhere.



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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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