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Mastering the Complexities of MSSP ACO Payment at Janesville, Wisconsin’s Mercy Health System

June 14, 2016
by Mark Hagland
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Ladd Udy of Mercy Health System shares his learnings around optimizing coding under the MSSP program

Things are moving forward on a number of fronts at Mercy Health System, a five-hospital, 80-clinic integrated health system based in Janesville, Wisconsin. In January 2015, the former Rockford (Illinois) Health System merged with Mercy to create the combined, community hospital-based system.

Significantly, both the old Mercy Health and the old Rockford Health were participants in the Medicare Shared Savings Program; the old Mercy had joined the MSSP program on Jan. 1, 2014, while the old Rockford had joined on Jan. 1, 2015. Senior leaders at the merged health system are currently preparing to bring the two ACOs together as a single ACO in 2017. That ACO will coordinate the care of 20,500 Medicare beneficiaries—11,000 from the Mercy ACO and 9,500 from the Rockford ACO.

Given the extensive involvement in the Medicare ACO program, there naturally is ample motivation among Mercy Health’s senior executives to optimize their organization’s reimbursement from Medicare. But as the health system’s executives have been learning, along with the leaders of all the other MSSP ACOs, there are nuances and complexities around MSSP benchmarking. One of those has been around hierarchical condition categories, or HCCs, which assess the health condition of the individual patient. Originally introduced by the federal Centers for Medicare & Medicaid Services (CMS) to risk-adjust Medicare Advantage payments to participating health plans, the use of HCCs in the MSSP program is proving challenging to participating ACOs.

The challenges built into the CMS-HCC model are ones that Ladd Udy, director of population health and ACO, and his colleagues at Mercy Health System, have steadily been unwrapping as they’ve been delving into care management under the MSSP program. Udy and his colleagues have partnered with the Salt Lake City-based 3M Health Information Systems, in efforts to optimize reimbursement under the system. Udy will be speaking on the topic “Using Hierarchical Condition Categories to Manage Population Health,” on June 28 along with Donna Smith, a senior 3M consultant, at the Healthcare Financial Management Association’s annual ANI Institute, to be held at the Venetian Sands Convention Center in Las Vegas.

Udy recently shared with HCI Editor-in-Chief Mark Hagland some of the learnings that have been gleaned so far from this work at Mercy Health System, and which will be the subject of his and Smith’s HFMA ANI presentation this month. Below are excerpts from that interview.

Let’s begin by discussing the core issues around hierarchical condition categories. What are the fundamental issues for ACO leaders?

Well, to begin with, our efforts are still relatively young, and it takes a year before you even have the data back from CMS. But the focus has been around the MSSP program’s use of the hierarchical condition categories, which show the prevalence of certain types of illnesses in our population. They use that model, which encompasses both quality and cost outcomes, and the payment element of the model involves the cost outcomes tied to our benchmarks. They [Medicare officials] look at three years of historical spending on a patient, and also apply a risk-adjustment factor to determine how healthy or sick your population looks based on your claims.

And so the HCC model tells them whether you’re hitting your cost benchmarks?

Well, they use the model to determine what your benchmark is in the first place. Then they give us our target, our benchmark, saying, based on the HCC and based on your claims, this is your benchmark.

So you’re using analytics to determine your accuracy of your spending on patients?

Well, to determine how accurately we’re documenting how healthy or sick each patient is.

So inevitably, becoming successful in this area takes you back to coding, then, correct?

Yes, it does. And the other tricky part of this model is that it resets each January 1. So for example, let’s say that a patient has a diabetes and has their foot amputated. And then we see them in the clinic and assess their condition and document that, and it goes into the encounter diagnosis. So the patient will be newly risk-adjusted. But on January 1 of the next year, that resets, and goes essentially to zero. So if we don’t assess a wound or amputation, it drops off the risk adjustment for that patient. So we have to make sure that we’re correctly risk-adjusting each patient.

Tell me about the mechanics of applying the solution. Are they difficult?

Well, getting it accurate and having accurate measurement, has been a significant challenge, not just for us, but for ACOs everywhere. Everybody who hasn’t participated in a Medicare Advantage arrangement until now is struggling with this. There is a small handful of providers who’ve been getting capitated payments from Medicare—and they probably have a pretty good handle on this, because they’ve worked with this. And this could be a difference between $800 PMPM [per member per month], versus $2,500 PMPM. On a fee-for-service basis, if we simply put down “diabetic,” we’ll get paid for the claim, but overall, our risk adjustment will be off. And that’s the problem we’re facing. Our data is telling us that our Medicare population is healthier than the average Medicare population by our significant amount.

So right now, you’re digging into this, and figuring out where the problems and gaps are, correct?

Well, we’re getting closer, yes; that’s what led us into this. We saw in our data that we looked healthier than the average Medicare population. Other sources of data conflict. When you think of Wisconsin and even Illinois, you think of beer, cheese, and brats—that’s part of the culture. And anecdotally, we don’t feel we’re healthier than other populations; but we need the data. And the crux of my presentation, what we’ve done is, we’ve figured, OK, there are different ways of approaching this. We thought this was hitting us in the MSSP. But we also have contracts with the state of Wisconsin, for Medicaid enrollees. Wisconsin runs Medicaid through a managed care organization. We have 14,000 Medicaid patients, and we’re capitated, and they risk-adjust it as well.

What turned out to be the core issue or set of issues? Doctors’ ability to code more precisely and optimally?

Yes. We were only putting a single diagnosis on a claim, just enough to get paid, and weren’t putting down secondary diagnoses on a regular basis, because we didn’t have a reason to do it until now. And we’ve found we weren’t alone there, either, a lot of ACOs are in the same boat.

Can you provide a couple of examples of typical situations involving sub-optimal coding on the part of physicians?

A typical one is when a physician codes for diabetes without complications, as opposed to diabetes with retinopathy or nephropathy—those are typical secondary diagnoses that are very common and yet which often physicians neglect to code for.

And what is the financial difference between the coding without complications and the coding with one or more complications?

Diabetes without complications doesn’t get a risk adjustment factor at all. With complications, it could be 0.37. So, consider that the average risk per patient is 1; so that could be as much as 1.37, when complications are added in. That could make that much of a difference. And Medicare rebalances every year, so that the average risk for the average Medicare patient is 1.0. And Diabetes with complications adds 0.37. The starting point for each patient is 0, and the average ends up being 1. Certain things like acute cancers have a 2.5 risk adjustment, for example.

How far do you think you’ve been off on average, altogether?

Well, that’s tough to determine, because it doesn’t affect our fee-for-service payments, only our benchmark.

How would you describe your “off-ness,” qualitatively speaking?

I would say overall that the bulk of our Medicare population looks to be 20 percent healthier than average.

Does that mean you could be losing 20 percent of your ACO payments?

No, because the risk adjustment is only one component of the overall spend.

But it’s significant?

It is, yes.

When did you and your colleagues begin the work to analyze your coding in this area?

We first started seeing the discrepancy about 18 months ago now. But for a long time, we didn’t really know what to do about it. So that led us to discuss what to do, and how we could impact that score and make sure it’s accurate. So for the last 8-9 months, we honed in on the strategy. And what we’ve done is that we’ve figured out how we can identify which patients, in the medical record, have a condition that hasn’t yet been assessed in the calendar year. And we’ve created a pop-up alert for this for the provider, so that when the patient is in the clinic setting, the alert will tell the provider, hey, this is something to assess. We made it active for all patients, they’re all a part of the registry. It looks at the patient’s active problem list in Epic. And if they have an active problem that hasn’t been listed as an active diagnosis within the calendar year, this alert pops up. And the same alert comes back next year.

How many patients has the alert fired for so far?

I’m looking at a report from back in April, right now. And as of that time, we had been live for six weeks, and it had already populated for about 1,000 patients within six weeks. We had it fire for all patients, not just Medicare. So we knew that risk adjustment was hitting us in other contracts, too, Medicaid, Blue Cross—so we made it go live for all patients. But if that rate held, we’re looking at 8,000 patients a year who have one of these conditions that needs to be assessed.

What percentage of your patient population is that?

It’s going to be 8,000 out of 150,000 patients—probably about 5 percent of patients who have one of these conditions on their active problem list.

So are you working with doctors on improving their coding?

Yes. First, we brought 3M in to educate providers in the mid-fall; we had a mandatory meeting, which meant that about 40 percent showed up. They educated them on what the model was and why it was important, and we subsequently went live with best practices, via a one-page sheet. The providers are the ones who have to list the encounter diagnosis; a staff member can’t do that.

What have the biggest learnings been in all this so far?

A couple of things. One is that there’s not a single way best way to approach this. I’ve had conference calls with people in ACOs at other organizations. Everyone seems to have a different approach. There’s not a single solution that works for everyone. And it does take some patients, because the true score that matters comes from CMS. We can measure on our own, but if it doesn’t matter their score, it doesn’t count. And we only get a report from CMS once a year. So it’s challenging, and there are no slam-dunk solutions at the moment. But not doing anything will have negative implications for most providers, whether they know it or not.

Given all this, what would your advice be for fellow leaders of ACOs?

To do something. Do something that’s reasonable for your organization and fits with your culture. You have to determine the urgency. If you’re already in capitated payment, this is very urgent. If you haven’t taken any downside risk yet, it’s important, because you eventually will have downside risk, so you’ll need to do it, but it may not be super-urgent yet. But it’s important, and has required a lot of physician education. We’ve had to do it over with a number of doctors. So yes, it requires several rounds of education. And our approach is young, and I’m sure we’ll tweak it more with time. And as we come closer to accepting downside risk, it will become more important.

Can CIOs, CMIOs, and other informaticists play an active role in this?

Yes, sure. We have an internal IT person who works on the Epic pop health suite of tools, Healthy Planet. That’s the person who put together and built the best practice alert, and determined when it the alert would fire. And without her, we wouldn’t have known what it was possible to do and when.

 


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CMS: 93% of Clinicians Get Positive Payment Adjustments for MIPS Year 1

November 8, 2018
by Rajiv Leventhal, Managing Editor
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Ninety-three percent of MIPS (Merit-based Incentive Payment System)-eligible clinicians received a positive payment adjustment for their performance in 2017, and 95 percent overall avoided a negative payment adjustment, according to a CMS (Centers for Medicare & Medicaid Services) announcement today.

The first year of MIPS under MACRA’s Quality Payment Program (QPP) was dubbed by CMS as a “pick your pace year,” which essentially enabled clinicians to avoid payment penalties as long as they submitted at least the minimum amount of quality data. As such, in its announcement, CMS did admit that the overall performance threshold for MIPS was established at a relatively low level of three points, and the availability of “pick your pace” provided participation flexibility through three reporting options for clinicians: “test”, partial year, or full-year reporting.

CMS said that 93 percent of MIPS-eligible clinicians received a positive payment adjustment for their performance in 2017, and 95 percent overall avoided a negative payment adjustment. CMS specifically calculated that approximately 1.06 million MIPS-eligible clinicians in total will receive a MIPS payment adjustment, either positive, neutral, or negative. The payment adjustments for the 2017 program year get reflected in 2019.

Breaking down the 93 percent of participants that received a positive payment adjustment last year, 71 percent earned a positive payment adjustment and an adjustment for exceptional performance, while 22 percent earned a positive payment adjustment only. Meanwhile, just 5 percent of MIPS-eligible clinicians received a negative payment adjustment, and 2 percent received a neutral adjustment (no increase or decrease).

Of the total population, just over one million MIPS-eligible clinicians reported data as either an individual, as a part of a group, or through an Alternative Payment Model (APM), and received a neutral payment adjustment or better. Additionally, under the Advanced APM track, just more than 99,000 eligible clinicians earned Qualifying APM Participant (QP) status, according to the CMS data.

CMS Administrator Seema Verma noted on the first pick-your-pace year of the QPP, “This measured approach allowed more clinicians to successfully participate, which led to many clinicians exceeding the performance threshold and a wider distribution of positive payment adjustments. We expect that the gradual increases in the performance thresholds in future program years will create an evolving distribution of payment adjustments for high performing clinicians who continue to invest in improving quality and outcomes for beneficiaries.”

For 2018, the second year of the QPP, CMS raised the stakes for those participating clinicians. And in the third year of the program, set to start in January 2019, a final rule was just published with year three requirements. Undoubtedly, as time passes, eligible clinicians will be asked for greater participation at higher levels. At the same time, CMS continues to exempt certain clinicians who don’t meet a low-volume Medicare threshold.

Earlier this year, CMS said that 91 percent of all MIPS-eligible clinicians participated in the first year of the QPP, exceeding the agency’s internal goal.

What’s more, from a scoring perspective in 2017, the overall national mean score for MIPS-eligible clinicians was 74.01 points, and the national median was 88.97 points, on a 0 to 100 scale. Further breaking down the mean and median:

  • Clinicians participating in MIPS as individuals or groups (and not through an APM) received a mean score of 65.71 points and a median score of 83.04 points
  • Clinicians participating in MIPS through an APM received a mean score of 87.64 points and a median score of 91.67 points

Additionally, clinicians in small and rural practices who were not in APMs and who chose to participate in MIPS also performed well, CMS noted. On average, MIPS eligible clinicians in rural practices earned a mean score of 63.08 points, while clinicians in small practices received a mean score of 43.46 points.

Said Verma, “While we understand that challenges remain for clinicians in small practices, these results suggest that these clinicians and those in rural practices can successfully participate in the program. With these mean scores, clinicians in small and rural practices would still receive a neutral or positive payment adjustment for the 2017, 2018, and 2019 performance years due to the relatively modest performance thresholds that we have established. We will also continue to directly support these clinicians now and in future years of the program.”

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HHS Secretary Azar: HHS Is Planning New Mandatory Bundled Payment Models

November 8, 2018
by Heather Landi, Associate Editor
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The Centers for Medicare & Medicaid Services (CMS) is revisiting mandatory bundled payment models, possibly for radiation oncology and cardiac care, according to Health and Human Services Secretary Alex Azar, which signals a strong about-face in the Trump Administration’s policy about bundled payment initiatives.

HHS is reexamining the role that mandatory bundled payment models can play in the transition to value-based care, Azar said in a keynote speech at the Patient-Centered Primary Care Collaborative Conference on Thursday. HHS published Azar’s comments.

In the published remarks, Azar said the Trump Administration is revisiting mandatory bundled payments and exploring new voluntary bundled payments as part of the Administration’s goal of paying for outcomes, rather than process.

“We need results, American patients need change, and when we need mandatory models to deliver it, mandatory models are going to see a comeback,” Azar said.

In his speech, Azar said, “Imagine a system where physicians and other providers only had to worry about the outcome, rather than worrying about their staffing ratios and the individual reimbursements for every procedure they do and every drug they prescribe. That kind of payment system would radically reorient power in our healthcare system—away from the federal government and back to those closest to the patient.”

He continued, “One way we can do that is through bundling payments, rather than paying for every individual service. This is an area where you have already seen testing from CMMI for several years now—and I want to let you know today that you are going to see a lot more such ideas in the future.”

Azar highlighted the Bundled Payments for Care Improvement (BPCI), which, he said, has shown significant savings in several common inpatient episodes, including joint replacement and pneumonia.

During his speech on Thursday, Azar said, “I want to share with all of you for the first time today: We intend to revisit some of the episodic cardiac models that we pulled back, and are actively exploring new and improved episode-based models in other areas, including radiation oncology. We’re also actively looking at ways to build on the lessons and successes of the Comprehensive Care for Joint Replacement model.

“We’re not going to stop there: We will use all avenues available to us—including mandatory and voluntary episode-based payment models,” he said.

One industry group, the American Society for Radiation Oncology (ASTRO), already has voiced concerns about a mandatory payment model. In a statement issued Thursday afternoon, Laura Thevenot, CEO of ASTRO, made it clear that the organizaiton strongly supports a radiation oncology alternative payment model (RO-APM). "ASTRO has worked for many years to craft a viable payment model that would stabilize payments, drive adherence to nationally-recognized clinical guidelines and improve patient care. ASTRO believes its proposed RO-APM will allow radiation oncologists to participate fully in the transition to value-based care that both improves cancer outcomes and reduces costs."

Thevenot said ASTRO has aggressively pursued adoption of this proposed model with the Center for Medicare and Medicaid Innovation (CMMI). However, Thevenot said the group has concerns "about the possibility of launching a model that requires mandatory participation from all radiation oncology practices at the outset."

Further, Thevenot said any radiation oncology payment model will represent "a significant departure from the status quo." "Care must be taken to protect access to treatments for all radiation oncology patients and not disadvantage certain types of practices, particularly given the very high fixed costs of running a radiation oncology clinic," Thevenot stated.

Back in January, CMS announced the launch of the voluntary BPCI Advanced model, noting that it “builds on the earlier success of bundled payment models and is an important step in the move away from fee-for-service and towards paying for value.” The BPCI Advanced model includes more than 1,000 participants that are receiving episode-based payments for over 30 clinical areas, Azar said.

“BPCI Advanced is a voluntary model, where potential participants can select whether they want to join. But we’re not going to stick to voluntary models. Real experimentation with episodic bundles requires a willingness to try mandatory models. We know they are the most effective way to know whether these bundles can successfully save money and improve quality,” Azar said.

The Obama Administration introduced mandatory bundled payment for care for heart attacks and for cardiac bypass surgery in July 2016.

In the past, CMS Administrator Seema Verma has said that she does not support making bundled payments mandatory, and former HHS Secretary Tom Price, M.D. had strongly opposed mandatory bundles, going so far as to direct the end of two mandatory bundled payment programs—one existing and one previously announced. In November 2017, CMS finalized a rule, proposed in August 2017, that cancelled mandatory hip fracture and cardiac bundled payment models.

As per that final rule, CMS also scaled back the Comprehensive Care for Joint Replacement Model (CJR), specifically reducing the number of mandatory geographic areas participating in CJR from 67 areas to 34 areas. And, in an effort to address the unique needs of rural providers, the federal agency also made participation voluntary for all low-volume and rural hospitals participating in the model in all 67 geographic areas.

On Thursday, Azar acknowledged that his statements signaled HHS was reversing course on its previous stance, noting that last year the administration reduced the size of the CJR model and pulled back the other episode payment models, including those on cardiac care, before they could launch.

Azar, who was confirmed as HHS Secretary earlier this year, signaled early on that he diverged from Verma and Price on his views about mandatory bundled payments. During a Senate Finance Committee hearing in January on his nomination for HHS Secretary, he said, on the topic of CMMI [the Center for Medicare and Medicaid Innovation] pilot programs, “I believe that we need to be able to test hypotheses, and if we have to test a hypothesis, I want to be a reliable partner, I want to be collaborative in doing this, I want to be transparent, and follow appropriate procedures; but if to test a hypothesis there around changing our healthcare system, it needs to be mandatory there as opposed to voluntary, then so be it.”

During his speech Thursday, Azar pointed to the Administration’s first mandatory model, which was unveiled two weeks ago, called the International Pricing Index (IPI) Model for payments for Part B drugs. Azar said the model is a “mandatory model that will help address the inequity between what the U.S. and other countries pay for many costly drugs.”

Further, Azar said CMMI also will launch new primary care payment models before the end of the year, with the aim of introducing a spectrum of risk for primary care providers, Azar said.

“Before the end of this year, you will see new payment models coming forth from CMMI that will give primary care physicians more flexibility in how they care for their patients, while offering them significant rewards for successfully keeping them healthy and out of the hospital,” he said.

“Different sizes and types of practices can take on different levels of risk. As many of you know, even smaller practices want to be, and can be, compensated based on their patients’ outcomes,” he said. “We want to incentivize that, with a spectrum of flexibility, too: The more risk you are willing to take on, the less we’re going to micromanage your work.”

Azar also noted HHS’ efforts to examine impediments to care coordination, such as examining the Stark Law, the Anti-Kickback Statute, HIPAA, and 42 CFR Part 2. CMS has already launched and concluded a request for information on the Stark Law, and the Office of the Inspector General has done the same on the Anti-Kickback Statute, he noted.

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Dr. Sanjay Gupta’s Heartening Speech at CHIME18 Should Inspire U.S. Healthcare Leaders

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The story of an Amazonian tribe could serve as a motivational lesson for U.S. healthcare stakeholders

It was inspiring to hear Sanjay Gupta, M.D., the well-known neurosurgeon and medical reporter, give the closing keynote at the College of Healthcare Information Management Executives (CHIME) 2018 Fall CIO Forum in San Diego last week. Dr. Gupta, who serves as associate chief of the neurosurgery service at Grady Memorial Hospital in Atlanta, while also best known as CNN's multiple Emmy Award-winning chief medical correspondent, discussed the fascinating balance that he strikes between medicine and media.

“Oftentimes, I see people at their best, and sometimes at their worst. I get to travel the world, where I learn so much, but also teach others. Sometimes the dance between medicine and media can be awkward and emotionally challenging. But almost always, the stories we do have a significant impact,” Gupta told the Fall CIO Forum attendees.

What was perhaps most captivating about Gupta’s speech was when he spoke about visiting a primitive Amazonian tribe that appears to have the best heart health in the world. The Tsimane people of Bolivia do not speak a language, live a simple existence, and are disease-free, explained Gupta. So he went to visit the tribe with the goal to understand its lifestyle and what led to its members having such healthy hearts.  

Sanjay Gupta, M.D.

“I went spearfishing with one [tribe member], who thought he was 84-years-old, but he really didn’t know for sure. His shirt was off, and he was ripped, balancing himself on the canoe, just looking at the water, spearing fish. His eyesight was perfect. The entire indigenous tribe was just like this,” Gupta recalled.

After examining the Tsimane tribe’s diet, Gupta noted it was a hunter-gatherer society, meaning there was nothing technological. “The most mechanical thing I saw was a pulley for the well,” he said. Seventy percent of what they eat is carbohydrates—unrefined and unprocessed—while 15 percent of their diet is protein, and 15 percent fat, he added. “You need farmed food because oftentimes you don’t have successful hunting days, so the farmed food was the food in the bank. And they would do intermitting fasting, too. These are the people with the healthiest hearts in the world,” Gupta exclaimed.

When it comes to activity, when hunters are hunting, they’re never outrunning their prey, but rather outlasting it, noted Gupta. “We found that they walked about 17,000 steps per day. But they didn’t run; they only walked. They are active, but not intensively active. They also hardly every sit—they are either lying or standing all the time. And they would get nine hours of sleep per night, waking up to the rooster’s crow. There are no devices. Again, these are the people who have the healthiest hearts in world. They don’t have a healthcare system and don’t spend a dollar on healthcare,” Gupta stated.

What’s even more interesting about this tribe is that each of its members lives with some degree of a parasitic infection, which they usually get it early in life, have a few days of illness, and then just live with these parasites in their bodies for their entire lives. “The belief is that so much of the disease we talk about—that leads to this $3.3 trillion price tag [the total cost of U.S. healthcare spending in 2016]—is actually ignited or worsened by our immune systems. So the parasitic infections could be part of the reason they are protected from all types of diseases,” Gupta offered.

Essentially, it’s living this basic, undeveloped life that “inadvertently provides them extraordinary protection against heart disease,” noted a report in HealthDay last year. “Thanks to their unique lifestyle, most Tsimane [members] have arteries unclogged by the cholesterol plaques that drastically increase the risk of heart attack and stroke in modern Americans,” Gregory Thomas, M.D., medical director of the Memorial Care Heart & Vascular Institute at Long Beach Memorial, in California, said in that report.

Tsimane tribe (source: University of New Mexico)

You might be asking what the story of the Tsimane tribe has to do with U.S. healthcare since its lifestyle would obviously never be replicated in a developed country. And while that is true, it’s tough to ignore the $1 billion per day that our healthcare system spends on heart disease—compared to the Tsimane tribe that doesn’t spend a single dime, yet has the healthiest hearts in the world.

In this sense, perhaps we can use the Tsimane story to push ourselves to develop a greater understanding of why we spend so much money on healthcare and don’t have the results to show for it. Gupta asked this $3.3 trillion-dollar question in his speech—why does healthcare in the U.S. cost so much and what do we get in return?

“If you look at the statistics, it’s not impressive. More people die from preventable disease in the U.S. than in 12 other nations. People live longer in 30 other countries compared to the U.S.—including places like Chile and Costa Rica. We still have tens of millions of people who don’t have access, and we still spend all this money on healthcare. Why?” he asked.

Gupta explained that the nation’s high healthcare costs come down to the following: high administrative costs, technology, new drugs and development, and the cost of chronic disease—the last which is incredibly self-inflicted. About 70 to 80 percent of chronic disease is self-preventable, he said.

Indeed, as most of us know, about 5 percent of the U.S. population accounts for 50 percent of the healthcare costs. These are folks who are defined by illness, not by health, Gupta stated. This is why the modern-day healthcare system has proactively taken to targeting that 5 percent to improve their chances of preventing disease and staying healthy. “Data shows that home visits, nutritional counseling, one-on-one coaching, and diligent follow-up care can go a long way in preventing someone from getting sick in the first place, and from turning a disease into something more chronic. Some of these interventions can actually reverse disease. The die is not cast,” Gupta said.

For me, Gupta’s keynote highlighted the need for efforts around value-based care, care management, and population health to be intensified. A big part of that, as noted in the speech, is addressing patients’ social and environmental factors. It’s not at all surprising to see studies such as this one from earlier this year, conducted by researchers at the University of South Florida (USF) College of Public Health, Tampa, and WellCare Health Plans, and published in Population Health Management, which found that healthcare spending is substantially reduced when people are successfully connected to social services that address social barriers, or social determinants of health, such as secure housing, medical transportation, healthy food programs, and utility and financial assistance.

And with that, there is also an enormous opportunity for data and IT to play a role. Information sharing, so that providers have access to the right information at the point of care—no matter where the patient is—will be critical to reducing unnecessary costs. As will the robust use of data analytics, so that patient care organizations can be proactive in predicting which patients are at highest risk, when they might need services, and how to intervene at the appropriate time.

But to this point, Gupta, who noted that our society can get too caught up in high-tech, also suggested that “medicine seems to play by slightly different rules when it comes to innovation as opposed to other sectors. Sometimes, innovation moves painstakingly slow in respect to medicine.” At the end of the day, he said, it will be “the innovations that make us, [as a society], healthier, happier, and connect us in frictionless ways, that will be the biggest winners.”

So, will the U.S. population suddenly turn off their iPhone alarms, wake up to the rooster’s crow, and become a hunter-gatherer society? No, I would say that’s quite unlikely to happen. But hearing stories such as the one of the Tsimane tribe might just serve as good enough motivation to bring down the astronomical and unsustainable costs of U.S. healthcare.

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