On Friday, September 28, Chris DeRienzo, M.D., a practicing neonatologist and the chief quality officer of the six-hospital, 11,000-employee Mission Health, shared a wealth of insights around the Asheville, N.C.-based health system’s experience with continuous quality improvement, in his presentation, “Building a Data-Driven Culture of Continuous Improvement.”
Dr. DeRienzo was speaking on the second day of the Health IT Summit in Raleigh, being held Thursday and Friday of last week. He spoke on the topic, “Building a Data-Driven Culture of Continuous Improvement.” As explained in the agenda’s description of the session, “Creating a data-driven culture of continuous improvement requires more than a string of buzzwords. Mission Health has successfully embedded this culture across both clinical and operational teams, leading to dramatic improvements in patient outcomes and more efficient hospital and clinic operations. Led by Mission’s Chief Quality Officer, Dr. Chris DeRienzo, this keynote presentation will walk attendees through Mission’s journey to instill continuous improvement through analytics using three tangible and specific case studies: Driving Clinical Continuous Improvement through Care Process Models, Improving ED Throughput, and Implementing a Machine Learning Model to Reduce Readmissions rates.”
At the outset of his presentation, Dr. DeRienzo, who has spent nearly five years at Mission Health so far, articulated why continuous performance improvement, achieved with the help of Lean management and/or other performance improvement methodologies, is so critical an element in the intended transformation of U.S. healthcare delivery. “Medicare and Medicaid alone are now spending $1.1 trillion a year, with that rate rising at a pace of $1,000 a second,” he noted. And, he asked, “Are we delivering a trillion dollars’ worth of value for a trillion dollars’ worth of spend? We’re among the most expensive healthcare systems in the world for every item” of significant expenditure. “Yet our population health outcomes are among the worst, with regard to life expectancy, obesity, and all the major items” on the list of key healthcare system indicators.” Indeed, he noted, “Industries get disrupted when they reach 20 percent of GDP, and that’s what’s happening to healthcare now.” What’s more, he noted, “Our life expectancy is now getting worse for the first time in generations”—and that development ought to concern healthcare leaders nationwide.
Given the “burning platform” facing the healthcare system overall, leaders at Mission Health began six years ago to build a performance improvement culture, Dr. DeRienzo told his audience. “We brought on quality teams, and started to build a system-wide enterprise data warehouse.
The core recipe, as he noted, 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.” Fortunately, he noted, “I’ve been able to build a team of 21 quality improvement advisors, ‘QIAs,’” all of whom have been trained in Lean management techniques and strategies.
“What do you do with that recipe?” DeRienzo asked. “This starts in orientation. Every single new employee of our health system is told, you have two jobs. Job number one is to do whatever you were hired to do; job number two is to make it better. So from day one, everyone needs to do what they can to improve the work. We tell them, it’s your job to go fishing, we give them the fishing rod, and we teach them how to fish.” And he presented a slide to his audience that showed a quote by President Theodore Roosevelt: “Real progress is won by people who take the next step, not those who theorizes about the two-hundredth.” As a result of their philosophy, DeRienzo noted, “In all of our QI work, we have found that we reach scale when we ask teams, think about the big vison, but focus your energy and resources on taking the next step: make it better tomorrow. And that’s really powerful.”
Chris DeRienzo, M.D., speaking on Friday at the HIT Summit
Meanwhile, in terms of the leadership requirements involved, DeRienzo noted that “We apply multidisciplinary teams that are committed to a Quadruple Aim victory. And in that, we need to start with a multidisciplinary team committed to a Quadruple Aim victory.” Further, he said, “That team has to be led by an engaged physician or provider practicing in the area where it’s going to be used. I’m a neonatologist. I can’t be leading a neurosurgery team. We need neurosurgeons to work on neurosurgery. The clinician has the ‘clinical gravitas’ of their partners, the respect. In other words, we want each effort in any particular specialty to be led by those who are practicing in that specialty; that leads to 100-percent alignment.”
Learning through doing
Dr. DeRienzo made it clear to his audience that none of this work is easy. Indeed, he said, “We’ve made just about every process mistake you could make without actually hurting anybody; we had gestational cycles as along as the gestation of the African elephant. We PDSAed our own PDSA cycles,” he said, referring to the “Plan, Do, Study, Act” principle underlying virtually all of the performance improvement methodologies. “You have to define a best practice, built the workflow around it, and measure the workflow,” he said, and referenced a protocol around COPD (chronic obstructive pulmonary disease) exacerbation, which has been implemented in 22 physician practices.
The key? “It’s folks figuring out how we take a best practice and make it as easy to use as possible, DeRienzo said. “Because when it’s frictionless for me to use a CPM—care process model—like water, I’ll flow in that direction naturally, 90 percent of the time. We build it into the workflow. Is it perfect? No. But is it a heck of a lot better than it was five years ago? Absolutely.”
Among the absolute critical success elements? An integrated and intuitive electronic workflow to implement protocols; and “unimpeachable” real-time data served within a reliable analytics platform that reaches the physician and patient patient level with use and outcomes. “When you put data in front of the doctor, and get past the, ‘my patients are sicker, my population is different, I don’t believe the data’ talk,” he said, “well, nobody got into medical school being a B student. And once you get them engaged, physicians will work to improve their clinical performance.”
Major advances have been made through the use of 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 cost
> 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
Enhancing tools around readmission prediction and sepsis decline
Dr. DeRienzo spoke extensively about the 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. After his presentation, he sat down with Healthcare Informatics Editor-in-Chief Mark Hagland to discuss that initiative in detail. Below are excerpts from that interview.
When did this initiative begin?
It began in early 2017.
Did you establish the initiative?
I share the data science team with John Brown, our CIO. And in one of our data science sessions, I said, we need to find examples of where data science can improve clinician workflow. I said, this is an example of where care managers are spending too much time on front-end work. And everyone said, this makes sense as a way to intervene in clinician workflow and improve outcomes and their work.
How long did it take to build the Readmissions Predictor?
It took over a year to build and test and validate. HealthCatalyst is our enterprise data warehouse vendor. We had to build the model and figure out where to site the server. Subject Area Mart (SAM). We’ve got this massive lake of tables, and when we decide to build a dashboard, our data architects build a data mart to speed the dashboard time. So the EDW has 20-some-odd just Cerner tables alone; and we’ve got a pipeline for Lawson and others. And it would take forever to search to reload the dashboards that we used for care management. So the tables get indexed. And the data scientists load tables into subject area marts, as with the sepsis dashboard. By 5 AM every weekday, the SAMs pull from the data mart, to refresh the dashboard.
Who was on the team developing it?
Data scientists, data architects, me, and as we moved along, representatives from the care management team; care management leadership. I was the physician leader.
What were the biggest challenges involved?
There were technical challenges—for example, the data science team having to figure out what the right model was. That was an enormous lift. And it was an enormous lift on the data architect side to figure out how to serve the model, once it was built; and a ton of implementation work, as we shifted the care manager workflow. In retrospect, I would have engaged our VP of care management far earlier in the process. At the outset, I asked, can we do this? In retrospect, I should have engaged Tina at the very beginning. We realized that implementation would take much longer and be harder than expected. I learned from that. Tina Donkervoet, R.N., is the VP of care management. She has been a tremendous partner, and very forgiving of the reality that we’re going to make mistakes and it’s not going to be perfect.
What have been the top-line results?
We now serve predictions consistently with 90-percent delivery by 8 AM. IN the past, they would just get a list of who’s discharged from Mission Hospital. It’s an 800-bed hospital, so we may have 100 discharges a day. And they w ere spending hours figuring that out. Now, we’re going to focus our interventions on folks who have the highest scores in the Predictor Tool. And the Predictor Tool serves predictions for 30 days. Probability scale is 0 to 1, in 0.1 increments. Intent: to serve a rank-order list. And not only that, if the care manager chooses to click into the patient case, they can use their clinical judgement to individualize evaluation.
Why is it so powerful to use Lean and other methodologies in this work?
The way that we can use analytics to scale Lean improvement is exemplified by my stories. In order to drive PDSA cycles, I need data to drive analysis, and then improvement—to see what’s working. For example, with regard to sepsis, I can look today at our sepsis dashboard, and know how many patients we hit the three-hour bundle yesterday; and which patients we missed on, and which doctors were taking care of those patients. And now my sepsis team leads have actual data to know why we missed. Maybe somebody had stage 4 failure and we had to delay the fluid. But having real-time data means that we can go much, much faster, than in a world where we did retrospective chart review.
Can you explain the three-hour bundle, in your sepsis intervention initiative?
If we can do all these things within a three-hour time period, the patient has much greater chance of survival. Things like fluid resuscitation, trending a lactate, getting antibiotics in within an hour. Those are all evidence-based data points that we know that, if we can make it happen, that patients with septic shock and severe sepsis, have a better chance of survival. This is not a predictor; we built a workflow to make sure things happen within the EMR, and the analytical tool to determine what we have. We have a clinical decline tool we use; we work with PeraHealth, using the Rothman index.
So the bundle tool helps you determine how well you’re performing?
Yes, and where we need to improve. It’s by definition retrospective. It’s like a baseball game, had we allowed bunter 3 to get to base… So the Sepsis Dashboard helps the leaders of the teams know where to intervene next. Tone of the first things in Lean, you do your first Plan Do Study Act, then what? There’s rarely one big-bang solution; it’s usually a combination of at least a few changes or interventions.
We can determine what the rate-limiting step is in a situation. In chemistry, the rate-limiting step of an equation is what slows the whole thing down. So, we determine what our rate-limiting step is. How to make it easy for a clinician to document a reperfusion exam? For one dose of a certain type of antibiotic to be administered? Knowing where to focus our energies next—that’s how analytics can super-charge continuous improvement.
What should CIOs and CMIOs think about, as their organizations move into continuous performance improvement work?
Anytime a CIO or CMIO is beginning to engage with continuous improvement work, the most important thing is to focus on things core to an organization’s mission. By building this analytics infrastructure, and focusing it on continuous improvement, we will improve outcomes and reduce total cost of care in a changing environment. So for IT leaders, make sure you’re relentlessly continuing the why. John [Brown, CIO] can tell you why these improvements are so powerful for clinicians. We’ve decreased mortality for things like rib fractures. And our CPM has meaningfully reduced mortality; connecting what we’re doing in IT to improvements that are changing lives is very powerful.