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At The HIT Summit-Washington, DC, a Robust View of Population Health

October 27, 2016
by Mark Hagland
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A lively discussion around population health challenges and opportunities took place at the HIT Summit in Washington, D.C.

A very robust discussion around the challenges, opportunities, and incentives around population health management took place on Oct. 26, during the Health IT Summit in Washington, D.C., sponsored by Healthcare Informatics, and held at the Ritz-Carlton Tysons Corner in the Washington suburb of Tysons Corner, Virginia. Not only did panelists engage in lively discussion, numerous audience members gave impassioned comments and asked many questions, leading to a discussion that all those involved in agreed was a meaningful one at this moment in the evolution of the U.S. healthcare system.

Drexel DeFord, CEO of the consulting firm Drexio Digital Health, led the panel discussion, entitled “Population Health Strategies to Improve Outcomes and Coordination of Care.” He was joined by Sule Calikoglu Gerovich, Ph.D., director of the Center for Population-Based Methodologies at the Maryland Health Services Cost and Review Commission, in Baltimore; and Robert S. Rudin, Ph.D., an information scientist, at the Washington-based RAND Corporation.

“I want to start with the term population health,” DeFord said in opening the discussion. “Sometimes, it’s good just to define population health. And I think back to being a ‘recovering CIO,’ spending a lot of time talking about big data. I like the joke about population health being like teenage sex,” he said: “everyone talks about it, and everyone thinks everyone else is doing it, but a lot fewer people are doing it than people think.”

Gerovich said she is fully aware of some of the contradictions in creating population health strategies. “My background is in public health,” she noted, “and at Hopkins”—she received her doctorate from Johns Hopkins University—“the School of Medicine was on one side of the street, and the School of Public Health was on the other side, and we used to say that that was the widest street ever,” she said. “To me, population health is the seeping of public health concepts down to the provider level. Everyone is defining population health differently, but in the end, it’s thinking about prevention and outcomes.”

What’s more, Gerovich added, “In Maryland, we have all-payer rate-setting: Medicare, Medicaid, private payers, all pay the same prices. And the commission that I work with looks at the costs that different hospitals face, and regulates the charges and ChargeMasters at the hospitals. We’ve been thinking about population health, and how we can incentivize providers when they come to their door and beyond.”


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(l. to r.) Drexel DeFord, Sule Calikoglu Gerovich, Ph.D., and Robert Rudin, Ph.D.

“I agree with that,” Rudin said. “The key aspect of what makes something a population health program is that it is proactive, as opposed to reactive. It’s about not waiting to treat a patient, but devising strategies to identify [at-risk] patients ahead of time. In our study, we found three goals within this population health strategy. The first basic goal is to identify high-risk patients; the second goal is to identify the subset of patients who can be helped and treated—and there’s a big drop-off between who’s doing #1 and #2. And goal three would be to identify subsets of patients and match them to specific interventions. Very few are yet doing #3. In a lot of models, the variable most predictive of hospitalization is previous hospitalization; but the whole goal is to try to prevent the first hospitalization. So the predictive capability is still very poor; really, no one’s doing it really well right now.

“I’ve always thought of it as being like a soccer field,” DeFord said: “you’re trying to intercept the patient before they cross the mid-field line—and if you can keep them far, far away from the sick end of the soccer field, even better. Meanwhile, Bob, you mentioned analytics—can you talk more about that?”

“There’s a near-consensus here: in terms of predicting who the high-risk patients are, most everyone agrees that the big bottleneck is in the data, not the analytics.,” Rudin responded. “The gap is in the data: there are major problems in using data to predict. We found three categories for data. Claims data has some advantages: it’s longitudinal, it covers multiple doctors; but it’s very limited in terms of the advanced kinds of information needed. EHR data is richer, but it’s limited by organization. It’s also very dirty. Problem-list data is pretty well known to be wildly inaccurate and incomplete. So EHR [electronic health record] data’s got a lot of problems. Also, there’s a lot of missing data. And as Dr. Williams said a little while ago, some of the most predictive data is around social rather than clinical variables. The third type of data would be around the patient him/herself. The problem is that there are so many types of data that might be relevant. For example, use of a wood-burning stove is very predictive of respiratory illness. Now, are you going to ask all of your patients whether they use wood-burning stoves? There are probably not a lot of patients in New York City that are going to answer affirmatively. There are also problems not only with input but also data output. Change, the dreaded ‘c word.’ This requires training and other elements as well. So we have a long way to go to become truly predictive.”

“I agree,” Gerovich said, “and I see that some of the data needed is at the population level. So someone needs to also be thinking about the clustering level, rather than just about the individual. My apologies to clinicians here, but they really have a hard time moving from thinking about the individual patient to the larger population. If clinicians see one false negative or data error, they tend to lose patience, too. So we have a lot of cultural change that needs to take place to help clinicians understand how this should work.”

“Yes,” DeFord said, “sometimes, clinicians are looking for a reason to not change. A group of us had dinner last night and spent a lot of time talking about the culture of medicine, and how difficult changing that is. You see the same things in the surveys and interviews you do. Can you talk about the change challenge?”

“Yes, never underestimate how difficult the tiniest change in clinical practice is,” Rudin responded. “We heard that over and over again in our interviews—that to have a good predictive model, you need good-quality inputs, and you need to do something with the outputs. And that requires understanding what your data points are, and what to do with them, and integrating them into your habits.”

“The incentives also matter,” Gerovich said. “Since I’m in the payment world, we think a lot about incentives, and what matters. So it’s not all about clinicians; it’s also about all the incentives—making sure we have the incentives for them to do the right thing. I was a nurse, and I know other clinicians, too. I think if we do the incentives right from a payment perspective, and we think a lot about care management reform, then I think there is a door opening, and in the past couple of years, things have already changed.”

In a comment from an audience member who had just given a presentation at the Summit prior to the population health panel, Marc S. Williams, M.D., director of the Genomic Medicine Institute at Geisinger Health System in Danville, Pa., said, “The points you made about the data are worth exploring a bit more. First, of all, when you have reliable data and present that to the clinicians, we do go through a kind of Kubler-Ross process of denial and anger and acceptance—and many times, if you have good, reliable data and show that data to clinicians—a lot of times, there doesn’t have to be a lot of cultural impetus to change, you’ll change because you’re not as good as your peers,” and those kinds of revelations immediately produce behavioral change, Dr. Williams said. “And the other thing that’s interesting—getting reliable data that’s clinically meaningful, can change behaviors,” he added. “Second, we have an Einstein problem: Einstein famously said, not everything that can be counted is meaningful, and not everything that’s meaningful can be counted. So when you go to clinicians and say, you’re going to be measured on this—the clinicians may say, that’s not clinically meaningful. So at Geisinger, we’re trying to worth through that. The thing is that outcomes measures are built around the lowest common denominator.”

“That’s in some ways the meaningful use challenge, right?” DeFord responded. “Because some of the measures are seen as not even mattering.”

“I agree, the measurement has to change,” Gerovich said. “We have process measures: do you do this for a heart attack patient? And with some measures, everyone has reached 95 percent, so the measure becomes meaningless. And we have to decide what the mean population health and quality measures are, and let providers figure out the specifics.”

And the Summit’s co-chair, Dave Levin, M.D., said this: “As we discussed over dinner, I believe everything comes down to people, process, and technology. And I’m really excited about the concepts and promise of population health; but I’m really fearful that we’re screwing it up. There’s so much focus around the technology and the analytics, around population health. And in many organizations, it’s one neuron connected to t, and when the population health neuron fires, it leads to the ‘I need analytics’ neuron. But the real need is for actionable data,” he said. “Health systems are rushing out to buy these tools, but they’re not looking at their care processes or care coordination, and basically know nothing about patient engagement. So we’re going to end up repeating a lot of the mistakes of the past. And you can always tell an organization is in trouble when they say, ‘We need coordinators for our care coordinators’! So we need to step back a bit. So the question is, do you see what I see, which is people focusing too much on technology and not enough on people and process?”

“I completely agree with that,” Rudin responded. “In terms of people, processes, and technology, this isn’t just a healthcare thing; there’s a long history of experience with the idea that if you just bolt technology onto bad processes, or as they say, pave the cow path, you won’t really change anything. So you have to co-develop the processes and the technology in parallel; they have to be designed together. And that’s not just true of healthcare. I would say also, I think there’s a lot of confusion about what these terms mean. And we’ve heard a lot from providers that in terms of coordination of care, there’s a lot of smoke and mirrors out there. They would look at products out there, and see that it wasn’t what they had in mind. Or vendors were doing vaporware tests to test the market. So we really need to define what these terms mean; and if you simply identify patients at high risk, that’s not actionable.”

Additionally, Gerovich offered, “Even if you give the data to people, they need a focus. In Maryland, since I’m a state official, we think a lot about the care coordination. There are good things that we need to leverage, and we need to think about what we can do collaboratively. Health information exchange is great in Maryland; all of our hospitals are connected; and when the patient comes to the ED, you can see the patient’s history, and send alerts. So we’re trying to connect to providers, to see what they need at the point of care. And you can’t do everything all at once. And we need work in terms of long-term version and how we get there.”

“We’re singing from the same sheet of music all the time about people, process, and technology,” DeFord said. “And as a recovering CIO, I’ve implemented lots of systems—EHRs, revenue cycle, etc. And what you realize when you’ve implemented them, is that you’ve taken a train wreck, and you’ve implemented a fast, efficient train wreck. So you see the problems that were always there, and you then get to fix those problems. I’m a big believer in the Toyota Production System and Lean—and I think this idea of really looking at processes, and figuring out what pieces you can reengineer, sometimes at very low cost, is a really great first step. I don’t know that we necessarily do that very well—but then do the technology insertions once you’ve gotten that figured out. It’s a real challenge.”

Rudin added that, “One thing we’ve heard is that when provider organizations are taking on risk in bundled payments, the providers have to decide how to divvy up all those payments, and that’s not always easy. And one provider system, they weren’t able to execute contracts, because they couldn’t figure that out. So the idea would be that if you could make the process more efficient, you could make some changes. So maybe if you could get someone to a community health center, that might be more efficient; but that’s the theory.”

“We’re really in this transition from a fee-for-service-based system to value-based payment, and it’s like a cow with two hooves over the fence and two hooves still on the ground on the one side, and we’re all wrestling with that transition.”

Meanwhile, an audience member who identified herself as a physician said this: “As I’ve dealt with the challenges of adopting one EMR after another, and after 30 years, I think, we need to focus on getting a good patient history. And what I’m finding—let’s find the path together. I could create a big rap sheet on things IT has done that has made patient care difficult, I could go on and on, but this has been a struggle for us in adopting this new technology, and we’re all guilty. What I hate,” she added, “is the fragmentation of care that I think is worse than ever. I can’t pick up a chart now and get the story anymore. We’re getting all these different codes and three different ways of saying hyperlipidemia. And it’s hard to read notes from specialists and know what’s going on. So let’s focus on the getting the history of the patient.”



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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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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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