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Plunging Ahead: Advanced Physician Organization Leaders Move Forward to Manage Risk

July 19, 2017
by Mark Hagland
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Even as the leaders of many physician organizations worry about the implications of the 2018 proposed rule for the QPP under MACRA, senior leaders at pioneering physician-lead organizations are charging ahead into risk-based contracting—and learning a lot

In the middle of the summer of 2017, many patient care leaders have understandably been focused on the June 20 release of the proposed rule for 2018 for the Quality Payment Program (QPP) under the MACRA (Medicare Access and CHIP Reauthorization Act of 2015) law, covering both the MIPS (Merit-based Incentive Payment System) program and the other side of the MACRA law, governing participation in advanced payment models (APMs). There is considerable complexity in the 1,058-page proposed rule; and much in the rule might change before it’s made final. But much of the discussion of the proposed rule, in the weeks following its release, was around the level of rigor and pace that should be embedded in forward progress around compelling physicians in practice more deeply into value-based healthcare payment.

Meanwhile, the leaders of more advanced medical groups say that the discussion around the details of MACRA’s requirements feels deeply secondary to the future they’re already building. Their organizations are already involved in taking on some level of financial risk in risk-based contracting, whether through federal accountable care organizations (ACOs) or ACOs sponsored by private health insurers, or through bundled-payment contracts (again, federal or private), or through any one or more of a broad range of population health-focused contracts of all kinds. And these medical group leaders have been spending the last few-to-several years learning how to collect and analyze data and use that data to feed continuous clinical and operational performance improvement, while at the same time building learning organizations, and transforming the physician cultures in their organizations. In other words, they’re already way ahead of the MACRA compliance game.

What’s exciting about that is that physician practice-based/clinic-based care remains at the core of the area of potential for change in healthcare, particularly when it comes to patients with chronic illnesses. Hospitals, health systems, health plans, employers, and governments all have a deep investment in efforts to improve patient outcomes and the patient experience, reduce costs and improve operational efficiencies; but it is in the physician practice setting that the most immediate interventions can be made—and the senior clinical and administrative leaders of the most advanced medical groups are making those interventions, and learning a great deal in the process.

One medical group leader whose attitude illustrates this perspective is Jeffrey LeBenger, M.D., chairman and CEO of the Berkeley Heights-based Summit Medical Group, a multispecialty physician group practice that covers a broad swath of northeastern New Jersey. Asked about the proposed 2018 rule for the QPP under MACRA, Dr. LeBenger quickly brushes the question aside. “I’m not concerned about that at all,” he says. “You’ve got to set up a model of care and make the economics work for you. If you can do that,” he says, there is a clear path to success. Indeed, he says, he and his colleagues have already zoomed past any of the core outcomes requirements mandated by the QPP.

Looking back at the last couple of years, LeBenger reports that “We’ve done very, very well in our population health process, meaning that we beat the market in PMPM [per member per month] costs in the state of New Jersey by almost 8 percent in the past year. What we found out” in terms of how to achieve success under risk-based contracts, “is that you must share data with your physicians, meaning that you have to scrub it, you have to fix it, and you have to work with financial and clinical data together. And it has to be timely data—you need timely data from the payers. And you have to put the right data into the right health information exchange. And you have to understand where your high-cost points are in your model of healthcare.”


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Jeffrey LeBenger, M.D.

LeBenger further clarifies what he believes is and is not essential to medical group leaders wading into the ocean of risk-based contracting. “Everybody says it’s population health, population health,” he says. “To be honest, I think that’s a bit wrong. You have to look at your model of healthcare. We’re getting very close to 800 providers; we’re in seven counties. And what we’ve done is that we’ve created high-acuity urgent care centers with imaging and with specialists; and we’ve created high-risk clinics for our high-risk patients. We do transitions of care for our sickest 5 to 10 percent of patients. We have home healthcare. We have medical directors at 70 percent of the long-term facilities we’re in. We compensate based on outcomes. And we follow the patient-centered medical home concept; and we really manage the patients out of the hospitals. For us, a hospital is a center for tertiary or quaternary care. We look very closely at monitoring patients out of the hospital.” It’s all of those factors—essentially, creating a data-driven care management system around one’s covered populations, especially for all those patients with chronic illnesses—that is at the heart of success in this emerging world, he emphasizes.

LeBenger’s perspective is shared with all of those interviewed for this story, who agree that:

  • The leaders of medical groups pursuing risk-based contracts, or considering doing so, need to develop core strategies that risk-stratify their covered populations and shift very strongly towards a care management-driven system of care that focuses on upstream interventions that avert ED visits and inpatient hospitalizations to the extent possible.
  • Medical group leaders need to develop highly sophisticated data and information systems that accurately bring together and analyze clinical information from their electronic health records (EHRs) and claims data from the payers with whom they’re contracting, in order to identify any gaps in care or care management; and they need to dovetail those information and analytics processes with multidisciplinary care management processes.
  • The health risk assessment and population health analysis process, and the process of using data analytics to empower multidisciplinary team-based care management processes, must in turn be tied into physician incentivization, including compensation.

In the case of Summit Medical Group, LeBenger notes that “How we get doctors to manage things better is that we provide up-to-date monthly dashboards,” which he and his fellow leaders use to incent their physician colleagues towards optimizing clinical and financial performance within the group. With support from those metrics, he says, “We compensate our doctors 20 percent based on quality, outside of direct productivity. And that’s true for our primary care doctors and specialists alike.”

A few hours north of northeastern New Jersey, in New York state’s Hudson Valley, the leaders of Crystal Run Healthcare have been on a trajectory similar to that of Summit Healthcare’s. The 400-plus-physician multispecialty group, based in the town of Middletown, has been succeeding at ACO and population health work for several years now. And what have Crystal Run’s leaders learned in the past couple of years? “We’ve learned, number one, that it is a lot easier to improve quality than it is to lower cost, because for the most part, quality is under the direct control of the organization,” says Scott Hines, M.D., the group’s chief quality officer. “So we’ve built a lot of systems around closing gaps in care for cancer screenings, immunizations, well-child visits, etc., and we really are in control of that. When it comes to cost, we’ve done a lot to monitor and reduce variations in care that are provided within our four walls and have resulted in greater standardization of care according to best practice guidelines, eliminating unnecessary or duplicative services; but the problem is that when the patient goes outside our walls to the ED or some other venue, we can’t control that. So trying to keep people in the most appropriate site of service has been our greatest challenge. The knee-jerk reaction for many patients is to go to the ED.”

Like their counterparts at Summit Medical Group, Crystal Run Healthcare’s leaders have been focusing to a considerable extent on driving clinical performance improvement through data, including through physician dashboards. “One dashboard that we’ve spent a lot of time updating and tweaking is what we call our payer quality scorecard,” Dr. Hines notes. “We look at our performance across the different metrics we’re accountable for—either a pay-for-performance-based metric, or a shared-savings or shared-risk incentive with potential quality gains.” Crystal Run is a participant in the Medicare Shared Savings Program for ACOs (MSSP); in addition, it has risk-bearing contracts with Aetna and with Blue Cross Blue Shield in its area, and a shared-savings arrangement with Cigna; and it is currently negotiating additional commercial risk contracts.  It also participates in three Medicaid managed care contracts in the state. A propos of all that activity, he reports, “We’ve built a payer quality scorecard that breaks it down by payer, shows the measures for each payer, and shows what we have in terms of data.”

Scott Hines, M.D.

Hines notes the importance of that analytics tool. “When we were relying solely on the payers’ claims data, there was at least a three-month delay/lag,” he says. “So we asked for specific numerators and denominators from the payers, for each of their measures.” In this context, the denominator is the patients included in a measure, and the numerator is the subgroup of patients that the health plan involved has determined are compliant with a particular measure. “And we take that information and feed it into our payer quality scorecard, and that captures any internal data, and shows us where we are in real time on those measures. We’re trying not to have any surprises, so that the payer says, for example, your benchmark was 75 percent for breast cancer screening, and you only hit 72 percent—that kind of thing.”

And what’s been learned from that process? “In the past, Hines, says, “we’ve asked for specific populations for each measure. We used to take each attributed population—say, 8,000 patients in a contract—and we’d feed those numbers into the scorecard, and the prediction was off by 15 to 20 percent for each measure, for two reasons. First, many measures had continuous enrollment criteria—the patient had to be enrolled for 12 months continually to be measured, and we had patients who weren’t, so that was distorting that number. And second, when you looked at the measure specification, we were applying the current year’s HEDIS (Healthcare Effectiveness Data and Information Set) specifications, but some of the payers were using specifications from, say, 2014 or 2015, so there would be mild differences in the inclusion or exclusion criteria, the lookback period, etc., so again, it was a source of discrepancy.” In other words, constant refinement of analysis and processes, is essential for success under increasingly-demanding risk contracts.

Advanced Medical Groups Seen Tilling New Ground

The kinds of work that Drs. LeBenger and Hines and their colleagues are engaged in at Summit and Crystal Run—the constant reiterations and refinements of strategic planning, data collection and analytics processes, and continuous clinical improvement processes—really is at the core of their success under risk-based contracting, those leaders agree. And so do industry experts and observers, including Matthew Cinque, executive director, performance technology at the Advisory Board Company, the Washington, D.C.-based advisement and research company. “The medical groups and physicians who have been involved in population health for any length of time, given that the ACA [Affordable Care Act] has been live for more than seven years—have evolved forward,” Cinque says. “The types of questions they’re asking and the needs they’re developing as they pick off the low-hanging fruit, are changing now. Early on, they focused on things like reducing utilization by frequent fliers in the EDs and elsewhere, and were asking questions like, which patients have been to the ED at least three times in the past year? Five years ago, that was very valuable information, and they’ve done a fair bit with that. Some of the questions people are asking now are around getting a better understanding of the predictive models used today, including asking about the social determinants of health, and using that data to factor into prediction of utilization; also around other forms of the psychosocial determinants of health.”

Matthew Cinque

Cinque goes on to say that “There’s been more success in identifying high-need or high-risk patients, with some opportunity for actionable intervention—either passing that data or list off to care managers, or circulating it among physicians. On the latter point around getting the physicians to actually use the data to improve outcomes—when you get down to the level of the individual physician who’s seeing 30 patients a day—success in actually changing behavior is still in its infancy. The vast majority of physicians are still operating primarily under fee-for-service” payment arrangements. The challenge on a practical level, as he puts it, is that “Not only do you have 100 diabetics who have uncontrolled A1c, but you’ll say, I want you to focus on these 40 who are in our risk-based contract—and in terms of focusing on the higher-compliance versus the lower-compliance patients—there are not many places that have cracked the nut on that.” As he sees it, one major element in success will come out of “wrapping care management functions and operations around physicians,” in order to lift some of the weight of trying to get patients to change their health-related behaviors, off the physicians.

"One Foot in the Boat” Continues For Now

All those interviewed for this article agree that one of the fundamental challenges in all of this remains what many in the industry are referring to as the “one foot in the boat, one foot on the shore problem” in U.S. healthcare, as even the most advanced patient care organizations still have a significant proportion of their revenues coming from fee-for-service payment models, even as they try to move forward to broaden their risk-bearing contract portfolios.

In making that shift over time, one of the core challenges remains convincing physicians in any physician organization to begin to shift forward, even as the incentives coming from the purchasers and payers of healthcare remain mixed, and sometimes not strong enough yet to compel revolutionary change. “It’s never easy; it’s always hard work,” says Mark DeRubeis, CEO of the 100-provider (85 physicians, 15 advanced-practice clinicians) Premier Medical Associates group practice in Pittsburgh. “But understanding what we need to change, and the kinds of leadership that are needed, and the necessary elbow grease, we’ve pretty much had the right attitudes among our physicians. And we are a physician-led organization, and we’ve found that that carries a good part of the weight,” he says, but quickly adds that “The hardest thing is that the healthcare system at large wants to effectuate a lot of change. Sometimes, federal policy leaders hit the mark in what they want to accomplish what they want, and sometimes, they just end up adding administrative burdens.”

He goes on to say that, fundamentally, “What’s been very difficult is financing the changes. Usually, the money isn’t sufficient, meaning that any money we’ve ever earned through quality is usually just plowed back into the organization for the next big thing, so to speak. It’s always up to the organization to figure out how to finance things; and it’s always, in healthcare, perform first and get paid later, so you really have to sell your physicians on the ROI” of moving forward on these initiatives.

The complexity of moving forward into risk while also managing fee-for-service payment-based operations at the same time is considerable, agrees James Whitfill, M.D., chief medical officer at Innovation Care Partners in Phoenix (formerly Scottsdale Health Partners). “For physicians who are paid by work RVU [relative value unit], whether in an employment model, or if they’re billing fee-for-service, it’s very hard to take them away from their core incentives to provide things that drive operational improvement, and it’s still common to see a work RVU-based productivity focus,” Whitfill notes. And he says, “Even though more advanced [physician] organizations are comfortable with their revenue cycle and EHR data, having the claims data coming in continues to be a brand-new space for providers, and getting your hands around that, particularly when you have multiple payers, is hard.”

James Whitfill, M.D.

That said, Whitfill reports that, “We’re seeing that in our clinically integrated network, physicians are starting to understand this model. They’re understanding two primary mechanisms. First, we’re doing face-to-face quarterly meetings among our CIN leaders, of which I’m one, and our primary care physicians. It’s myself and other leaders with each practice, once a quarter. And after about three quarters, they begin to understand what this is about. But it takes those meetings, one-on-one or one-on-two. Also, we front-load revenue to practices in value-based contracts as we move into a contract, while letting them know that those payments might have to stop. That helps. So those two things, we feel, have gotten the attention of providers and driven engagement perhaps more than in some other organizations.”

Hospital-Based Organizations Moving Forward, Too

The landscape looks a bit different for the leaders of physician organization divisions of hospitals and integrated health systems, but the journeys certainly parallel each other. At the vast 21-plus-hospital UPMC health system in Pittsburgh, Oscar Marroquin, M.D., the health system’s chief analytics officer in its health services division (which includes its hospitals and its physician groups), notes that “We’ve been using our analytics infrastructure and teams to leverage the information that lives in our electronic medical records as well as in our billing systems, to understand patient flow, what the phenotypes are of the patients our PCPs care for, what the distribution is of risk—when we manage patients on the outpatient side, to describe the level of health risk. We’ve done a fair amount of work in that space, that has led to identification of opportunities related to which practices are the best-performing ones in terms of their ability to keep patients healthier and out of hospitals, versus others, and that has allowed us the opportunity to dig deeper to understand why,” Dr. Marroquin says.

One very interesting example at UPMC is around the inflammatory bowel disease (IBD) patient-centered medical home that’s been created at the health system, and which has brought together UPMC gastroenterologists, psychiatrists, social workers, and other clinicians, to help optimize the management of IBD. The program, led by an IBD-specializing gastroenterologist, has reduced both inpatient hospitalizations and ED visits; and its PCMH (patient-centered medical home) focus has allowed it to track patients longitudinally in ways that had not previously been possible, Marroquin notes.

Even at hospital organizations that are near the beginnings of their journeys into risk, learnings are emerging. For example, the 208-bed St. Joseph Hospital in Nashua, New Hampshire, is participating in the Transforming Clinical Practice Initiative (TCPI) out of the Center for Medicare & Medicaid Innovation (CMMI) at the Centers for Medicare and Medicaid Services (CMS). And some of the innovative work that leaders at St. Joseph are pursuing had already been moving forward when the hospital was participating briefly in the Pioneer ACO program, reports Becky Williams, R.N., the hospital’s care coordination manager. For example, Williams notes, she and her colleagues have helped to universalize depression screening on the part of the 80 physicians in the hospital’s physician network, which has improved depression diagnosis and early intervention. She is hoping that the hospital’s participation in the TCPI program yields many additional advances in the near future.

Advice for Healthcare IT Leaders

When it comes to offering advice to healthcare IT leaders, including CIOs and CMIOs, those interviewed for this article are in agreement: all of the IT infrastructure, analytics, dashboarding, and other work that physician organizations implement must be done as part of broader, consensus-driven strategic efforts. “Information technology supports operations, as opposed to the other way around,” says Premier Medical Associates’ DeRubeis. “What I’ve seen many organizations do is to turn that over to IT and say, OK, you put it in for us, you plug it in, and we’ll come along afterwards. And in our experience, you don’t get the type of engagement from the physicians, when you do it that way.”

Crystal Run’s Hines adds that “One of the first things to acknowledge is that the data’s never going to be perfect. And particularly early on in the journey, when you’re just starting dashboards for the physicians, for example, emphasize that this is the first version of this, and it will be tweaked over time, so encourage the providers to look at their data and assess their data, and find any faults in the data to make it stronger in the end. And second, try to make the data of delivery as simple as possible—whether it’s a speedometer type of thing, or color-coded like green-yellow-red, so that literally, in one screenshot, providers can see their performance.”

Finally, says Innovation Care Partners’ Whitfill, “With regard to the one-foot-on-the-dock situation, it’s going to be hard to work this out” in the next several years, as physician groups continue to function partly in the fee-for-service world, even as they move further into risk-based contracting. In that regard, he says, “Any IT-facilitated improvements you can make to efficiency and workflow will be a benefit to your physicians, regardless of whether you’re being paid fee-for-service or fee-for-value. And the same thing is true of analytics: being able to navigate both worlds will increasingly require data scientist-level expertise. And we’ve made investments in the EHR over the last 10 years. The next step has to be making efficiency in workflow, and analytics to make sure we’re going in the right direction.” 

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Is Big Data the New Moneyball?

November 14, 2018
by Pamela Dixon, Industry Voice
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The new healthcare chief data officer can provide your playbook and data strategy

Anyone who has seen the movie Moneyball, a movie about baseball, will remember the opening scene— old guys talking around a smoky table with marked-up stacks of paper outlining the pluses and minuses of draft prospects. The old guys “critique” these prospects with the knowhow of hard-earned experience, and they talk with the familiarity of a weekly poker match.  

So when they are presented with a buttoned-up computer kid from Yale who will present his draft picks to them, there is a moment of surprised silence.  The kid clicks off his list of little known players to stares of disbelief, and he explains matter-of-factly, “The picks are based solely on statistical analysis.”  That’s when you see their world get upended.

Healthcare may be caught in a similar moment, on the edge of a fundamental shift.  In Moneyball, the shift from money driving decisions to information driving the decisions upended the World Series and, subsequently, the game of baseball.  Big data may similarly upend healthcare.

Admittedly, our opening scene in healthcare has some old guys in the room—half of doctors in the U.S. are over 50 years old—and, yes, they show resistance to change.  Meanwhile, healthcare consumers are in the bleachers increasing pressure for a big win.  And coming on to the playing field is big tech, betting on its AI prowess and other technology tools to address big data. Can it fix healthcare?


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Source: CB Insights

Big Tech’s Growing Interest in Healthcare

Following the money, we see big tech’s interest in healthcare starting to grow in 2012 (see above). In 2012, the top-10 tech companies that were involved in healthcare equity deals were worth about $277 million. In 2017, that grew to $2.7 billion. Driving part of the interest is big data.

“It’s not the data,” said Dr. Eric Topol, director of the Scripps Translational Science Institute. “It’s the analytics. Up until three-to-five years ago, all that data was just sitting there. Now it’s being analyzed and interpreted.  It’s the most radical change happening in healthcare.”

What’s in it for Big Tech?

Data-rich Facebook and Google make their money on advertising—an industry worth $200 billion, which is small compared to healthcare’s $3 trillion industry.  David Friend, managing director at account firm BDO, estimates a major opportunity for these two tech giants. “In theory, if this is done right, you’ll have 15 Facebooks and 15 Googles. That’s what’s up for grabs.”

While driving a profit is one opportunity, the ability to capitalize on data is key to developing consumer-centric models of care, improving patient outcomes, and lowering costs—which are all critical for healthcare.  Healthcare systems are working to accomplish the same goals using big data analytics, sometimes together with big tech companies.  A few examples:

  •          Stanford University School of Medicine, in conjunction with Apple’s new app, Apple ResearchKit, enrolled more than 11,000 patients—in 24 hours—which is more than most medical studies achieve in a year, and they collected much more data in 24 hours than they could have otherwise. This was an “eye opener” for them.
  •         The Centers for Medicare and Medicaid Services (CMS) was able to prevent a $210.7 million in fraud in just one year using big data analytics. 
  •          Allina Health System, an integrated delivery system of 13 hospitals and 82 clinics in Minnesota, realized more than $45 million in performance improvement savings over the past five years in a project targeting only cardiovascular care across the system.

So back to our opening scene, we have the old guys in the room resistant to change.  We have the consumers demanding change from the bleachers.  We have big tech on the playing field applying tools to big data to create some wins.  We have a few healthcare providers coming on to the field using data to create wins. But who is our buttoned-up computer kid, the one that puts together the “moneyball” playbook?  Enter the chief data officer; he or she is there to provide your playbook and your data strategy.

The CDO role is generally tasked with oversight of a comprehensive data strategy, enabling a data-driven culture, creating operational efficiencies and, in some organizations, revenue opportunities. These leaders provide the organization with a clear set of objectives and goals.

The chief data officer enters the scene when healthcare is on the threshold of a major shift. In addition to transforming care, controlling costs and enhancing revenue, data can be used to negotiate competitive rates with insurers, set more accurate (and justifiable) prices for healthcare procedures, and create the transparency that consumers are demanding. Understanding the flow of data will also find hidden opportunities to control costs and enhance revenue. Just your basic “moneyball” playbook.

While the CDO role has gained broad acceptance outside of healthcare, adoption has been very slow inside healthcare.  According to the International Institute for Analytics, which ranked various industries’ ability to harness data, healthcare providers came in last—lagging behind all other industries and all other healthcare segments, including health insurers.

"Moneyball" helped level the playing field by looking at information. This is where healthcare providers also start playing the game with new tools and a new type of leader.

Pamela Dixon, managing partner


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Olympic Marathons: Performance Improvement Initiatives Help to Power the Long Race

November 14, 2018
by Mark Hagland, Editor-in-Chief
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Organizations on the leading edge are also strategically leveraging information technology and data analytics as a key facilitator to continuous performance improvement, particularly on the clinical side

At a time when the leaders of patient care organizations are facing intensifying pressure to shift away from a dependence on volume-based payment and to plunge into value-based care delivery, what strategies can help them lead their organizations to success under new paradigms? With Seema Verma herself, Administrator of the Centers for Medicare & Medicaid Services (CMS), bluntly warning hospital, medical group, and health system leaders that she and her fellow senior federal healthcare officials will be pushing hard to compel providers forward into value-based contracting, IT-facilitated continuous performance improvement strategies are looming large as a critical success factor in the shift to value.

Indeed, speaking during a webinar on August 27 sponsored by the Accountable Care Collaborative, Verma responded to questions about CMS’s effort to push provider organizations to take on two-sided risk in the context of the agency’s accountable care organization (ACO) programs, particularly the Medicare Shared Savings Program (MSSP).

Asked by the webinar host, Mark McClellan, M.D., director of the Duke-Margolis Center for Health Policy and co-chairman of the Accountable Care Learning Collaborative, about provider feedback on the proposed changes to the MSSP ACO program, Verma responded, “I think many people recognize that it’s time to take that next step and it’s time to evolve the program; it’s been six years. We also understand that there may be providers that are not ready. But, our focus is to work with providers that are serious about making the investments and providing better care for lower cost.” What’s more, she intoned, “We’re trying to transition the structure to encourage providers to take on risk because we know that is going to deliver better outcomes.”

And while none of that rhetorical forcefulness—some might even call it saber-rattling—should come as a surprise from Verma, it’s also true that she fully realizes how challenging the overall transition is turning out to be for the vast majority of patient care organizations, which have more-or-less-contentedly been inhabiting a discounted fee-for-service payment world, even as the discounts have progressively bitten more deeply into their operating revenues.

The reality? On the hospital and health system side of the industry, hospital senior leaders long ago shaved off excessive expenses when it came to such areas as the supply chain and facilities management. And what remains to tackle now is the Moby Dick of operations: reworking processes at the core of patient care delivery, in order to achieve significantly improved cost-effectiveness and patient outcomes; everything else has already been tackled. In short, it’s become eminently clear that clinical and operational transformation cannot happen without the thorough reengineering of core care delivery processes.


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In that context, larger numbers of hospital and health system (and a few medical group) leaders have plunged ahead over the past decade-plus, and have moved to incorporate the use of formal performance improvement methodologies, among them Lean management, Six Sigma, the Toyota Production System for healthcare, and PDSA (Plan Do Study Act, formerly PDCA, or Plan Do Check Act) cycles of improvement, in order to achieve clinical and operational transformation. In practice, the quality leaders at most patient care organizations have liberally mixed the use of various methodologies, while others have relied primarily on one methodology, but have allowed the blending of concepts from others.

What’s more, the organizations on the leading edge are also strategically leveraging information technology and data analytics as a key facilitator to continuous performance improvement, particularly on the clinical side. Indeed, they are finding IT facilitation to be essential to success in achieving transformational change.

In Asheville, A Comprehensive Push Forward into Value

One of the patient care organizations that has been moving ahead determinedly in its use of IT-facilitated continuous performance improvement strategies is Mission Health, a six-hospital, 11,000-employee health system based in Asheville, North Carolina.

There, Chris DeRienzo, M.D., Mission Health’s chief quality officer, and Dawn Burgard, director of clinical performance improvement, have been helping to lead a comprehensive effort for several years, one that has already borne significant fruit. Back in 2010 and 2011, Mission Health leaders began mapping care delivery processes, adding in an analytics platform in 2013 and 2014. Burgard, who came to Mission Health in 2012, with a master black belt in Six Sigma and a certification in Lean management, and Dr. DeRienzo, who came in 2013, have turbocharged efforts in the organization since then. Among other developments, they early on brought on a cadre of 21 Lean management engineers, known as quality improvement advisors, or QIAs, and have built an enterprise-wide data warehouse.

One key tool that the leaders at Mission Health have built has been a dashboard called the Ambulatory CPM Explorer Dashboard, which is bringing near-real-time data to physicians. Among the accomplishments in the past few years:

  • A 20-percent increase in full sepsis bundle and a 32-percent reduction in mortality from sepsis
  • 12 lung cancer deaths avoided with 37 percent increase in screening
  • 9 fewer rib fracture deaths and $350,000 in reduced direct costs
  • A 42-percent reduction in in-hospital stroke mortality
  • 11,000 more women screened for breast cancer, 6,000 more people screened for colorectal cancer, and a seven-fold increase in depression screening

And, in two specific areas—among numerous others—Mission Health leaders have leveraged performance improvement cycles to build and optimize key initiatives. One has been the creation of the organization’s Readmissions Predictor initiative, which has dramatically enhanced ambulatory care managers’ ability to efficiently predict which patients might be at the highest risk for readmission, following discharge. That initiative began in early 2017, and has been led directly by Dr. DeRienzo and by Mission Health’s CIO, John Brown.

Spending over a year to build, test, and validate the program, Mission Health leaders created a dashboard that uses smart algorithms to provide care managers with up-to-the-minute data every morning at the start of the workday, helping them to determine which individuals, post-discharge, are most likely to end up being readmitted, and allowing them to start their days focusing on those at highest risk for readmission.

A second very important initiative, which began a year and a half ago, has involved applying the Explorer Dashboard to monitor patient flow into and through the emergency department, and to take steps to respond to emerging patient-flow blockages created by surges in patients presenting in the ED. Now, Burgard reports, “We have triggers on our home page, so everyone in the hospital knows what surge status we’re in. And once a new color is triggered”—from a range of four colors (green, yellow, orange, red) that indicate the degree of blockage—"there’s a whole bunch of standard work—a Lean term that involves the standardization of the elimination of variation in processes—that teams and managers are expected to do, depending on surge level,” she says. “That’s the power of standard work. It allows us to get into that predictive space and helps us to become more efficient with the way we staff.” Using this set of processes, patient volume surging that had peaked at 4 percent of patients who left before being seen, in the summer of 2016, is now down to 1 percent, with the ability to see 300 patients every day in the flagship hospital’s ED now a standard volume that has been made the norm.

The core recipe, DeRienzo notes, has included the following: a reliable enterprise data warehouse; a reliable data visualization environment; “more structure in clinical program leadership among physicians, nurses, and administrators”; a cadre of Lean management engineers; and, “trusted advisors.”

At UPMC, Patient Engagement for Improved Outcomes

Numerous quality improvement methodology-infused initiatives are moving ahead as well at the 40-hospital UPMC health system, based in Pittsburgh. There, says Tami Minnier, R.N., M.S.N., UPMC’s chief quality officer, “We use all of them”—especially Lean management, Six Sigma, and PDSA principles and strategies. But, she quickly adds, “Coming into healthcare from manufacturing, I learned early on that healthcare wasn’t quite ready for all the terminology around performance improvement methodologies, so we avoid technical terminology here. I have a black belt in Lean, but I don’t get into the intricacies,” she testifies. “I found that it turned people off. We had people say, ‘We don’t build cars.’”

Instead, Minnier has helped to lead forward a number of initiatives, and, she says, “We use whatever tool makes most sense at the time, and have blended them over time over the 12 years that the Wolff Center has been in existence”—referring to the UPMC Wolff Center for Quality, Safety, and Innovation—“and over time, we’ve raised the bar and have introduced things like run charts, fishbones [the fishbone tool for root cause analysis], some of the tools people find useful. But we don’t say, let’s have a big Kaizen on Tuesday afternoon! We’ve been a bit savvy about how we do it.”

And, as one of her key partners in those endeavors, MaCalus Hogan, M.D., vice chair of orthopedic surgery, and medical director for outcomes and registries at the Wolff Center, says, “I’ve been educated in the Lean environment and learned a lot from Tami and her team. Efficiency is key” in every endeavor, he says. “And in the surgical environment, things are geared around doing things well and efficiently.” Together, Minnier and Dr. Hogan have been leading an initiative that has significantly improved both patient engagement, and improved clinical and satisfaction outcomes, around the entire cycle around total hip and knee replacement surgery, which they and their colleagues have implemented across the six highest-volume total joint replacement surgery facilities in the UPMC system. “We needed to go further in clinical care improvement, encompassing from how we prepare patients, to alignment on who were good candidates,” Minnier explains.

And, Minnier says, “One of the things that we learned early on was that there was pretty inconsistent preparation of patients planning to come in for hip or knee replacement. Some doctors and their offices did this really fantastic job of preparing their patients for surgery, and some didn’t quite have it together. So we did a good current-state assessment, using Lean and PDSA approaches. We looked at the current state of variations, and what types of resources and materials people had in place, and then brought together a new model of change, centered around an orthopedic nurse coordinator in every site. That role was to protect and prepare every patient for surgery, and most importantly, to think about what their care at home would be like after surgery.”

The initiative began three years ago, with the orthopedic nurse coordinators being brought in two-and-a-half years ago. Those coordinators, also referred to as “navigators,” ensure an orderly, comprehensive process to prepare patients and provide them with online education. Leveraging the organization’s patient portal, MyUPMC, office physicians can prescribe educational materials during the office visit, just as they’d prescribe medications. And, she says, “The process improvement of having an ortho nurse coordinator, coupled with the technology support, really allowed patients to arrive at a preoperative phase in a much more prepared, organized manner, to anticipate what would happen when they got to the hospital and how they’d be taken care of.” And, as a result of intensive continuous improvement cycles, “We’ve been able to eliminate pretty much all of the variation,” she testifies. “And every single member of these ortho nurse navigators, they meet on a monthly basis, share each other’s practices, they’ve become a resource group unto themselves. That’s how you perpetuate and sustain change.”

In the context of the joint replacement improvement process, Dr. Hogan and Minnier saw clearly the advantage of Hogan’s being a foot and ankle surgeon rather than being a joint replacement surgeon. As such, he brought into the process a level of credibility as a fellow surgeon; yet at the same time, he was in a different subspecialty, so he could not be seen as a threat to the joint replacement surgeons. And the results have been impressive: consistent educational and preparational processes, improved patient satisfaction, and in many cases, enhanced recovery outcomes.

The Power of Harnessing Analytics

Industry leaders interviewed for this article agree on the core truths about all this: that using formal improvement strategies, of whatever specific type, will yield results; and that part of the power of this to achieve clinical transformation is in effectively harnessing IT and data analytics to facilitate such work.

“In my experience, it doesn’t really matter which methodology you choose, but that you choose an improvement methodology or methodologies, and stick with your strategies; it’s the discipline that matters,” says George Reynolds, M.D., the clinical informatics executive advisor for CHIME (the Ann Arbor, Mich.-based College of Healthcare Information Management Executives), and principal in Reynolds Healthcare Advisers, LLC. Dr. Reynolds, who served as the CMIO at Children’s Hospital & Medical Center, in Omaha, Nebraska, for 11 years, and CIO for the last five years of that tenure, reports that “We did a version of PDCA [Plan Do Check Act—an earlier version of Plan Do Study Act], which is very easy to teach, but lacks the rigor and the discipline of Lean and Six Sigma. We would do well [at Children’s], but it was hard to maintain the changes.”

Meanwhile, Dr. Reynolds says firmly, leveraging data and analytics to power performance improvement cycles is “absolutely central to everything you do. And it doesn’t necessarily have to be really fancy bells and whistles, though I love fancy bells and whistles. You can do a lot with an Excel spreadsheet. You can do a lot with some fairly simple tools. But the more advanced tools become valuable” as organizations move forward into deeper and broader efforts.

Early on in the Proverbial Journey of 1,000 Miles

What remains disconcerting is how far behind most U.S. patient care organizations are starting out, says Robin Czajka, service line vice president for cost management at the Charlotte-based Premier Inc. Asked where she thinks the healthcare industry is, if this phenomenon could be compared to the proverbial journey of a thousand miles, the Chicago-based Czajka says that “I would say that we’re at the very beginning of it, frankly, having been in the industry for 25 years. You see pockets of great performance, and areas where we haven’t made any progress at all,” she says. “Some organizations are short of staff and mired in taking care of increasingly sick patients. So this needs to be a top priority. And we’re looking at a 5-percent growth year-over-year” in hospital costs. “The Medicare fund will be insolvent if we keep on this trajectory.”

What’s more, says Mary Frances Butler, a senior adviser at the Chicago-based Impact Advisors consulting firm, the level of progress in this area “will depend on the type of hospital.” There is a continuum of advancement, she notes, “from small community hospitals, all the way up to the mega-systems like Intermountain and Geisinger [the Salt Lake City-based Intermountain Health and the Danville, Pa.-based Geisinger Health], who have been at it a long time. Intermountain is an example of a leader in this. And, to the extent that leader organizations have been able to facilitate conversations through the C-suite and into the IT group, to get out of their silos,” they’ve made greater progress, she notes.

Premier’s Czajka has mixed sentiments with regard to the mixing or blending of specific methodologies. “It’s both good and bad; you can create some kinds of success, but you do lose some things; I’ve personally seen Lean be effective when done rigorously,” she says. “But as long as it’s cyclical, monitored, and sustainable, and as long as there are checks and balances,” any combination of methodologies can be made to work well, she says. The absolutely critical success factor? “Success in this area is always data-driven,” she insists. “And with Six Sigma, you take data over time and look at it and act. A lot of organizations will see a blip, for example, bed sores, and will react to it. But it may turn out to be a special-cause variation, maybe they got an unusual surge of admissions from a nursing home or something. When you start to employ a system like Lean, problem solvers become problem framers. So you need to look carefully at the data and analyze it, and act over time.”

The Power of Data-Focused Teams

One lesson shared by those in the trenches is the power of creating and nurturing purpose-specific teams focused intensively on the management of data to power performance improvement, particularly in the clinical area. Oscar Marroquin, M.D., a practicing cardiologist and epidemiologist in Pittsburgh, has been helping to lead a team of data experts there. That team, of about 25 data specialists, was first created five years ago. Of those, half are IT- and infrastructure-focused, and, says Dr. Marroquin, “The rest are a team of folks dedicated to data consumption issues. So we have clinical analysts, data visualization specialists, and a team of data scientists who are applying the right tools and methods, spanning from traditional analytical techniques to advanced computational deep learning and everything in between. Our task is to use the clinical data, and derive insights”—and all 12 clinically focused data specialists report to him.

And that work—“allowing people to ask questions to generate opportunities”—has paid off handsomely. Among the advances has been the creation of a data model that predicts the chances that patients who are being discharged will be readmitted. The model, based on the retrospective analysis of one million discharges, is also helping case managers to more effectively prepare patients for discharge, specifically by ensuring that patients being discharged are promptly scheduled for follow-up visits with their primary care physicians. “If those patients are seen within 30 days of discharge,” he notes, “there’s a 50-percent reduction in their 30-day rate of readmission.” The program is now active in six UPMC hospitals.

What it Really Means to be Data-Driven

Those industry leaders interviewed for this article are agreed on what healthcare IT leaders should know both about the adoption of performance improvement methodologies generally, as well as about the leveraging of IT and data to achieve success in clinical and operational transformation.

“If you’re going to embark on a Lean Six Sigma-driven journey, it rises and falls based on leadership,” says Mission Health’s Burgard. “We know that the methodologies work. But I always say, Lean is not a set of tools, it’s a mindset for how you’ll transform your organization. The same thing is true with technology. It all rises and falls on leadership. And senior leaders need to understand the methodology and the tools. That applies to technology, too.”

“I’ve been really impressed with the degree of partnership of our CIO John Brown, with our PI team,” says her colleague DeRienzo. “When I think about continuous improvement, there’s so much overlap between the improvement processes and the data processes. And by driving alignments across the entire system, including across the different teams, we’ve been able to make much broader progress.”

Importantly, says Premier Inc.’s Czajka, “It’s crucial to accept that data shouldn’t be the enemy of the good. The data is never going to be perfect,” she says. “Just make sure it’s directionally accurate.” What’s more, she says, “You need to train your people to use the data correctly. I can’t tell you how many times I meet with clients and they have these great data systems they’ve purchased, but no one is trained to work well with it. And,” she says, “figure out the data points that will actually drive improvement. I went into a member hospital that had about 100 data points they were asking people to focus on, in a dashboard. You can’t ask people to do that.” Working with leaders at that hospital, she was able to get them to narrow down those 100-some data points to 11 that could be focused on, for process improvement.

In the end, says UPMC’s Marroquin, “If we all are serious about transforming the way we care for patients, we need to do it in a data-driven way. There has to be a philosophical belief and commitment to do that, and then you have to create a team that’s dedicated to this work. I don’t think this is achievable in an ad hoc way.” Finally, he says, “This work is not for the faint of heart; it takes time and effort, but if you have the philosophical belief and institutional commitment, it’s doable.”

Related Insights For: Analytics


You Have to Learn to Walk Before You Can Run With Predictive Analytics

November 11, 2018
by David Raths, Contributing Editor
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Health systems report obstacles in turning their big data into actionable insights

The title of a recent webinar says all you need to know about predictive analytics in healthcare: “Within Sight Yet Out of Reach.”

The Center for Connected Medicine, jointly operated by GE Healthcare, Nokia, and UPMC, put on the webinar and partnered with HIMSS on a survey on the state of predictive analytics in healthcare.

The survey of 100 health IT leaders found that approximately 7 out of 10 hospitals and health systems say they are taking some action to formulate or execute a strategy for predictive analytics. But despite the buzz and potential, there are obstacles for health systems that want to turn their big data into actionable insights.

Although 69 percent said they are effective at using data to describe past health events, 49 percent said they are less effective at using data to predict future outcomes. They cite a lack of interoperability and a shortage of skilled workers as barriers. “They want to put all that data to work to provide insights as we deliver care, but it is not an easy task,” said Oscar Marroquin, M.D., chief clinical analytics officer at UPMC. “They are having trouble getting access to the data in useful and standardized formats and don’t have the people in place to apply machine learning techniques.”

The top five use cases cited in the survey are:


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• Fostering more cost-effective care

• Reducing readmissions

• Identifying at-risk patients

• Driving proactive preventive care

• Improving chronic conditions management

UPMC’s journey into the analytics space was jump-started by an institutional commitment to building the analytics program and a recognition that it needed to be a more data-driven organization. “We were never able to consume our data to drive how we deliver care until we had a dedicated team to do analytics,” Marroquin said. “Traditionally these functions were done as a side job by team members in IT systems. We have found having a dedicated team is absolutely necessary.”

Mona Siddiqui, M.D., M.P.H., chief data officer at the U.S. Department of Health & Human Services, says she is focused on the interoperability aspect across 29 agencies. “We are looking at how we are using data across silos to create more business value for the department,” she said. “We don’t have that infrastructure in place yet,” which leads to one-off projects rather than tackling larger priorities. She is focusing on enterprise-level data governance and interoperability structures. “I think the promise of big data is real, but I don’t think a lot of organizations have thought through the tough work required to make it happen. Practitioners start to see it as buzzword rather than something creating real value. There is a lot of work that needs to happen before we see value coming from data.”

Noting the survey result about human resources, she added that “the talent pool is an incredible challenge. While we talk about sharing data and using it for business intelligence, we don’t resource our teams appropriately to fulfill that promise.”

She said the move to value-based care has made predictive analytics more important to health systems. “It is a data play from the ground up,” and now we are starting to see the real impact in terms of managing chronic conditions. “More organizations like UPMC are seeing this is about data and measurement and bringing in not just data they have, but resources and data they may not have had access to previously.”

Travis Frosch, senior director of analytics at GE Healthcare, said that hospitals generate petabytes of data per year, yet only 3 percent is tagged for analytical use later on. “So 97 percent goes down the drain,” he added, suggesting that organizations need to start small. “If you are an organization that does not have maturity in analytics, start with traditional business intelligence to build the trust and foundation to move toward higher level of analytics maturity,” Frosch said. “Pick projects that don’t require tons of data sources. If you get a good a return on investment you can open up the budget to further your analytics journey. But you have to have a unit in place to measure the impact.”


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