At St. Louis’s Mercy Health, an Analytics-Driven Performance Push
Major data analytics-fueled clinical and operational performance improvement has been taking place at Mercy Health, the 45-hospital, 300-clinic integrated health system that is based in the St. Louis suburb of Chesterfield, Missouri, and which serves patients and communities in four states—Missouri, Oklahoma, Arkansas, and Kansas.
Leveraging powerful data analytics tools, Mercy leaders have made dramatic progress in a number of clinical areas and services, from the large perioperative area, to cardiology, to laboratory, to pharmacy.
Among those helping to lead an organization-wide charge on operational performance improvement are Gil Hoffman, Mercy Health’s CIO, and Curtis Dudley, its vice president of integrated performance solutions.
Among other things, Hoffman and Dudley collaborated with a large, system-wide team of colleagues to develop a system-wide cost-per-case perioperative dashboard, which provided a wealth of opportunities for the organization’s clinical and administrative leaders to improve performance along a number of dimensions, through monitoring, measuring, and improving costs and clinical outcomes of a variety of surgical procedures. Indeed, using key cost and outcomes data related to surgical procedures across the entire integrated system, Mercy Health achieved $9.42 million through cost reduction, the elimination or minimization of the use of certain surgical products, reduced supply utilization variation, and best practices across perioperative departments in the system.
As Hoffman and Dudley note, Mercy Health has a very high volume of surgical procedures—about 210,000 procedures annually—with the system’s second leading driver of cost coming from surgical supplies and implants. The health system’s leaders looked at that reality and also at the opportunity to impact quality and the patient experience, and went to work, with the system’s perioperative team and technology services team partnering to create a set of custom dashboards launched through an information portal for one-stop access to high level metrics, reports and data exploration tools for immediate answers, faster decisions and more agile process improvements. The interactive dashboards leverage cutting-edge technology to provide a holistic view, consolidating large sets of diverse clinical, operational and financial data into a single platform.
Prior to 2012, determining surgical costs at Mercy was an unstructured, manual process. At the time, surgeon preference cards and product contracts (which contain supply cost) were the only methods available to determine the cost of surgical procedures. Without data as evidence, there were varying opinions as to the best practice, price and product for a given procedure. As a result, there were significant variations in the cost per surgical case across Mercy. But, through the use of dashboards, along with extensive governance development, clinician and staff training, and the leveraging of health IT (including the extensive leveraging of the HANA platform from the Charlotte-based SAP), the leaders of the initiative were able to make significant progress, with a system-wide cost savings of $9.42 million across perioperative departments for all surgical procedures as calculated through January 2016, after launching the initiative in 2013. Among other elements, Mercy’s median cost per case for total knee surgery dropped from $7,045 with an interquartile range of $1,999 in 2014, to a median cost per case of $5,527 and interquartile range of $901 in 2016. In addition, following dashboard implementation, there has been a significant drop in costs of intraoperative implants and supplies per case related total knee arthroplasty.
Recently, Hoffman and Dudley spoke with Healthcare Informatics Editor-in-Chief Mark Hagland to discuss some of the elements of their organization’s success to date with this system-wide performance initiative. Below are excerpts from that interview.
Tell me a bit about the secret of your success so far with this wide-ranging initiative?
Gil Hoffman: Part of the secret is that our team really focused on how to look at the best outcomes, and then determined what were the best practices involved, and determined how to deliver those good outcomes as efficiently as possible, by reducing costs and improving care.
Curtis Dudley: I’ve been at Mercy health for 27 years. I came from our supply chain division, and have been there for 20 years. I led our Texas warehouse system implementation, the implementation of our Lawson ERP and deployment of that system system-wide, and through that, our supply chain system that we created, which has won a number of awards. A lot of that has been enabled by analytics and data, and that is what brought me to corporate headquarters four years ago. I’ve led our OR operations, supply chain, etc.
And when I came into this role four years ago, I knew we would need data and analytics. So we did a current-state analysis; and what we found in nursing, in lab, in pharmacy, in perioperative, in cardiology, everywhere, was that people were running native reports inside applications, and spending a lot of hours in Excel trying to merge them. So we wanted to unify the delivery experience of analytics, so that people could simply go quickly to analytics and reports. We set out to do this through our business intelligence platform. And, as we prepared to move forward with this initiative, we went to our chief nursing officer, our vice president of laboratory, and to periop, and asked those leaders which metrics drove their business. And because I had knowledge of the periop business and data, and had built a cost-per-case dashboard in Cognos, I went there first. That’s why a lot of our case studies and areas of focus have been in periop.
Curtis Dudley
So we took a service line- and data mart-oriented approach, pulling data from Epic, from Lawson, from an outside data cleansing service, from our outside contractors—and it’s a challenge to pull all those sources of data together. So we spent a lot of time creating a data platform. And we found that there is so much data involved in periop that, to provide an effective data mechanism, we couldn’t show people thousands of lines of raw data. What we needed to do was to roll up those rows of records into dashboards; but traditional means wouldn’t work. We were on Oracle, and Oracle is great, but it just wasn’t robust enough to do this. And we had a long relationship with SAP, partly because of Epic. So we loaded the data in a HANA environment. SAP Business Objects is the suite of tools we leveraged, and SAP HANA is the data platform involved.
So we were able to load all this data, including multiple years of costs per case, and drill down into the individual service or specialty level, or by doctor. But the key thing that’s enabled our success is a variation-oriented approach. So, for example, the dashboard helped us see why one doctor was doing a total knee replacement for $10,000 per case, versus another at $4,000 per case. So using SAP-Hana, we were able to drill down that far. And because the data set was so big, loading into this Hana PLATFORM, I could load these 40 million rows of data, and view it all. Over three years of data in periop, documenting every case, over 210,000 procedures a year, across three full years, that led to the 40 million lines of data.
And because we can real-time-interact with that, we can ask questions, and get to those answers in real time. So I can find out that the reason that this doctor is more expensive than the other doctor is that he’s using specific supplies, for example. So we can work with this and work with the clinicians. And Gil, the HANA investment was pretty extensive, right?
Hoffman: Yes, putting this volume together provided us with these reports, in a reasonable time, when it would have meaningful use.
What are your thoughts on optimizing data use, as a CIO?
Hoffman: I’ve been with Mercy going on five years now, and I came from outside healthcare. And it seemed to me when I got here that healthcare had been sitting on a ton of data for years, but hadn’t been using it to dramatically improve patient care or efficiency. But data really is becoming the tool that gets things done better than they’ve been done before. And using analytics is becoming more and more critical to the success of healthcare. For Mercy, it’s made a dramatic difference in patient care, in the patient experience, in our business work—the ability to get data in real time because of the tools.
Dudley: We saved $9.4 million in cost-per-case reductions this year in periop. That just has periop numbers, but we saved $9 million in cardiology, $1 million in lab, and $2.5 million in pharmacy.
Where did those large doses of savings come from?
Dudley: In cardiology—it’s all come about by taking a variation-oriented approach. One great example involved cardiac stents. It turned out that Mercy had 1.62 stents implanted per patient, versus 1.42 stents per patient, on average nationwide. And when we analyzed that, we found that where we were implanting two stents per patient, there were single stents available that had the same clinical outcomes. So our success in that area required looking not only at costs, but also at quality outcomes, including infection rates, complication rates, etc. So that was an important part of this, improving quality and lowering costs, and improving patient satisfaction.
And where did the $1 million savings come from, in the laboratory area?
Dudley: There was a rapid, expensive cardiac test used in our ER departments, and we switched that out with a test used in the lab that was less expensive; there were a few other similar situations, around unnecessary lab tests or overtesting. We were testing for a heart attack inside the ER many times, when clinical evidence shows that there should be a 2-4-hour gap between giving the heart attack test, otherwise, there’s no benefit.
And the pharmacy savings?
Dudley: In the pharmacy, we have a lot of inventory across our network—we have Omnicell cabinets everywhere, and we were able to analyze the inventory quantities in the cabinets, and found where there was inventory that wasn’t moving, and could shift inventory to where it was needed. So there was a cost element, and also, some medications that weren’t being utilized that were taking space, and also, we could get meds that were needed into those cabinets, so there were patient and nurse satisfaction elements in having certain meds made more available, per reducing medication inventory stored.
What have been the biggest lessons learned so far in all this?
Dudley: There have been so many learnings. A couple I would highlight: the challenge in doing this work. There’s a big technical challenge, involving creating the data platforms. Tools like the HANA platform, and also Hadoop—having a robust, high-performing data platform makes this possible. A lot of times, you underestimate or undervalue how important that is. The second lesson learned is that there’s a journey to be pursued with the business people. Along the way in delivering these metrics, we help them analyze their business in ways that couldn’t be done otherwise. With cardiology, lab, and pharmacy, we were able to help them better understand how their internal operations work. All this time in healthcare, putting in systems and asking clinicians and others to enter data into systems, we hadn’t given them data back in ways that could improve care and efficiency. We’re doing that, and the clinicians are valuing that.
Hoffman: And there’s more to this than just metrics. It takes different types of talent from different people, to bring together those correlations and data points, to take action and make better decisions. There’s just so much to learn from this, to better the patient outcomes and experience. It’s more than just the metrics, more than just measuring certain levels of performance; you’ve got to be able to interpret those pieces of data.
What would you say to CIOs and CMIOs about your experience so far?
Hoffman: Every CIO needs to look at how they can leverage the data they have to improve operations. I’m not sure that everybody has the time and capacity to do this—you have to invest the time it takes to get information out of these systems. So make the investment to get the value out of these systems to be able to learn everything you can learn.
Dudley: And I would just add that there’s really not a choice here. It’s do-or-die time, and it’s incredibly important for organizations to do this. And I don’t know that organizations need to reinvent the wheel. There are numerous collaborative ways to get to this. But you don’t have to reinvent the wheel; there are a lot of people you could partner with to make this happen.
