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Might Food Be the Next Frontier on the Population Health Horizon?

April 5, 2017
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Connecting patients’ nutrition, exercise, and other “lifestyle”-related characteristics to health risk assessment and then to care management, could be next in efforts among population health pioneers

Is now the time for the leaders of patient care organizations who are leading population health management initiatives to think broadly about some of the non-clinical aspects of health status, including food and nutrition, exercise, and other so-called “lifestyle choice” elements of health, in the context of care management efforts? Recent articles in The New England Journal of Medicine and Health Affairs certainly seem to point to that possibility. What’s more, a small number of patient care organizations are beginning to look at the sociodemographic and socioeconomic aspects of health status among their covered populations. Let’s look at what’s going on.

To begin with, I was fascinated to read a “Perspective” article that appeared online in The New England Journal of Medicine, entitled “U.S. Nutrition Assistance, 2018—Modifying SNAP to Promote Population Health.” The thought-piece, written by Sara N. Bleich, Ph.D., Eric B. Rimm, Sc.D., and Kelly  D. Brownell, Ph.D., examines some of the policy foundations of one of the key federal anti-hunger programs in the United States, in the context of current population health management initiatives among U.S. healthcare providers and plans.

“The Supplemental Nutrition Assistance Program (SNAP),” the authors write, “is the cornerstone of the nutrition safety net in the United States, helping 45 million low-income Americans — nearly half of them children — pay for food each month. SNAP is authorized by Congress through the Farm Bill, which also covers agricultural programs such as crop insurance and land-conservation measures. With an annual cost of $74 billion, the program accounts for roughly 80 percent of the spending authorized by the bill. As an entitlement program, SNAP is responsive to economic fluctuations — enrollment can expand rapidly when the economy weakens and shrink when it improves. SNAP is scheduled to be reauthorized in the 2018 Farm Bill, which will set U.S. food policy for the next 5 years and beyond. As Congress deliberates, it’s important to consider what changes to the program are feasible and also have the potential to improve population health. Above all,” they state, “we believe SNAP should be protected — and, ideally, expanded, since its current benefits don’t allow most families to purchase adequate food to maintain a healthy diet.”

The researchers note that, while SNAP was never initially designed to focus on nutrition, but rather, was intended primarily to reduce hunger. Originally known as the Food Stamp Program, it was initiated in 1961 but didn’t become a permanent, nationwide program until 1974. SNAP has improved food security for millions of Americans. In 2014, SNAP lifted 4.7 million people, including 2.1 million children, out of poverty.” As the authors note, the challenge for many low-income families today “is less about obtaining enough food and more about finding dependable access to affordable healthy food. Currently, SNAP benefits can be used to purchase virtually any type of food or nonalcoholic beverage from eligible retailers.”

The authors reference a study that made use of point-of-sale transaction data from a leading grocery retailer that found that SNAP-recipient families “allotted a higher proportion of their grocery bills to soft drinks than to any other item (about 5 cents out of every dollar, as compared with 4 cents among non-SNAP households). It also found that both SNAP and non-SNAP households spent roughly 20 cents per dollar on sweetened beverages, desserts, salty snacks, candy, and sugar. Past studies involving nationally representative dietary-intake data have suggested that SNAP participants have poorer-quality diets than nonparticipants with similar incomes.”

Meanwhile, an article in the March issue of Health Affairs broadens out the subject. In “Impact Of The YMCA Of The USA Diabetes Prevention Program on Medicare Spending and Utilization,” authors Maria L. Alva, Thomas J. Hoerger, Ravikumar Jeyaraman, Peter Amico, and Lucia Rojas-Smith describe an innovative program devised by the YMCA of the USA, with support from a Health Care Innovation Award from the Centers for Medicare and Medicaid Services, that has been providing diabetes prevention education and coaching to Medicare beneficiaries with prediabetes, in 17 regional networks.

As the researchers note, “The YMCAs [participating in the program] use an evidence-based curriculum based on the Y’s adaptation of the National Diabetes Prevention Program of the Centers for Disease Control and Prevention (CDC). The goal of the Y model is to get participants to lose 5 percent or more of their body weight and gradually increase their physical activity to 150 minutes per week.”

The authors note that “The curriculum comprises 16 core sessions that cover the following topics: healthy eating strategies, understanding fat and calories, and elearning about foods that are high in nutritional value; strategies for increasing physical exercise, including incorporating exercise as part of one’s lifestyle and setting and achieving exercise goals; and strategies for changing one’s environment to help facilitate weight loss, using positive thinking, managing stress, and improving motivation. During the core sessions, lifestyle coaches facilitate group discussions of behavior changes, challenges, and solutions.”

The results speak for themselves: the researchers found that, comparing participants and nonparticipants, “[W]e found that the overall weighted average savings per member per quarter during the first rhree years of the intervention period was $278. Total decreases in inpatient admissions and emergency department (ED) visits were significant, with nine fewer inpatient stays and nine fewer ED visits per 1,000 participants per quarter. These results,” the researchers state, “justify continued support of the model.”

Drilling Down to the Data

Now, what does all this have to do with providers’ and plans’ population health initiatives? A fair amount, as it turns out.  Just ask Justin Pestrue, administrative director of quality analytics at Michigan Medicine (the new name for the University of Michigan Health System), Ann Arbor, Michigan. On March 24, during the Health IT Summit in Cleveland, sponsored by this magazine, Pestrue presented “Effectively Using Sociodemographic Data in Healthcare Analytics,” a presentation that looked at sociodemographic and socioeconomic data, and the potential to leverage such data in efforts to move population health and accountable care initiatives forward.

As Pestrue told his audience last month, there is a very significant opportunity to leverage sociodemographic and socioeconomic data in new ways in order to more effectively care for patients in the context of accountable care organization (ACO) and population health work; and much of that opportunity has yet to be fully plumbed. As Pestrue noted, there is already a broad awareness of the fact that only a small proportion of patients’ health status can directly be impacted by care delivery in patient care organizations; some say that proportion accounts for perhaps 20 percent of the overall impacts on the health of individuals, with personal lifestyle and behavioral choices, personal environmental influences, and other influences being far stronger overall, he noted.

“[W]e have a real tendency to look at the data that’s easier to get—and that’s often the elements that are in our EHRs [electronic health records] and in our billing systems. But sociodemographic and socioeconomic data can do a really good job of helping us to better understand our patients,” he noted, with sociodemographic data include gender, race, ethnicity, age, and place of residence, and socioeconomic data including education level, income, etc., and both types of data being corralled together under the rubric “social determinants of health.”

In fact, in drilling down through the data they have, Pestrue noted that he and his colleagues are coming up with very interesting findings. For example, they’ve been drilling down several levels on location-related demographic data, scanning the service area around Ann Arbor by zip code. What they discovered was interesting, because zip code alone turned out to be a rather crude indicator of health status. Instead, drilling down to the sub-zip code level, they’ve found a variety of “hot spots” of neighborhoods of people with challenging sociodemographic and socioeconomic characteristics. And in one case, that work uncovered a sub-zip-code area—a neighborhood within the zip code in which Pestrue himself lives, which is a generally affluent area within the Ann Arbor metro area—in which the sociodemographic and socioeconomic characteristics of the population were far poorer, and in which ED visits and hospital admissions were higher. It turns out that that sub-zip-code area is a mobile home park.

And though he said that he and his colleagues have not yet moved forward to take action to identify individuals within that zone and health risk-assess them and get them into active care management, Pestrue told his audience that the potential is there to proactively intervene to improve the health status of such populations, using leading-edge analytics.

And clearly, there is potential here for a huge amount of progress in linking all these elements: looking at one’s covered population within any risk-based contract—whether an accountable care organization (ACO) contract with Medicare or with private payers, or involving any population health management initiative—and then linking the findings from any analytics work, into proactive engagement with patients who might be, as in the YMCA case study, prediabetic, to improve their health status before it worsens, through patient education, coaching, and care management.

Let’s be clear: the potential here is tremendous, absolutely tremendous. And as the public and private purchasers and payers of healthcare push the U.S. healthcare system further and further into value-based delivery and purchasing and further and further towards capitated or semi-capitated risk, bringing all these elements together will make economic as well as mission-based sense—really, it will.

So yes—the day is coming when patient care leaders will be diving far deeper on data and on linking that data to care management arrangements under ACO and population health contracts. And healthcare IT leaders will inevitably be drawn in very deeply on the analytics elements of this—as well as on the data architecture and interoperability efforts needed to connect it all together. Broccoli, anyone?





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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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