Success in South Carolina

Irvin: It was led by our cardiologists, and then the nurses and others in various areas, such as pharmacy, the emergency room and surgery, became involved; we had physicians, nurses, and pharmacists all involved, depending on the specialty.

Isgett: Just to take one example, we came up with ‘rovers’—ICU nurses staffing the ICUs 24/7, who have been ‘roving’ and monitoring high-risk patients. That group of patients has included those on their own pain pumps, those who had recently been transferred out of the ICUs in the past 24 hours and into regular floor beds, patients who were in restraints for some reason, patients who had had a rapid-response call. Rovers would go and evaluate each patient determined to be at risk, and the rovers have also functioned as our rapid-response team. Using the team of rovers offers a perfect example of the kinds of mechanisms we’ve been employing in order to address mortality issues. We started with as-expected mortality, and developed solutions, such as the use of rovers; and once we’d achieved improvements, we ended up teaching classes for people from other organizations participating in the QUEST program. That shows you how the continuous improvement model works [in the QUEST program].

Irvin: And the nice thing about rovers is that the program acted proactively.

These types of solutions really are based on commonsense kinds of approaches, aren’t they?

Isgett: Yes, but I’ll be very frank: when I saw the outcomes with other hospitals getting significantly lower than expected mortality ratios, that was the first time it occurred to me that it could go to the next level [with regard to mortality reduction]. Because we were good, we were as expected. And that’s where the beauty of data comes in. If one hospital in the program achieved lower-than-expected mortality, we would all flock to them to find out what had happened.

What about the issue of getting buy-in from physicians? Can you comment on the data that you’ve been sharing with the physicians in order to get their buy-in and participation?

Irvin: Consider the data that the payers have; they haven’t always shared that data in the past. Now, we’re collecting the data and sharing it with the doctors directly. And the only way to get them involved is to show them the data and ask them to look at it and then let them decide where to go with it and what to fix. And sometimes, for example, you look at data across 10 surgeons doing appendectomies, and some may be high-cost and some low-cost, and they can sit down together and analyze things, and look at mortality and outcomes as well. And we can figure out what we can and should do differently, and is it order sets or protocols, or early intervention? The physicians really need to be involved every step of the way.

What were some of the key things the doctors did find that created change?

Irvin: One of the things learned relates conceptually to the use of checklists, something that Atul Gawande, M.D., has written and spoken about. For example, we found that when the doctors failed to make use of the stroke order set in their ordering process, they would almost always forget at least one thing. So getting them to see that standardization is not a bad thing, as you’re handling fairly complicated patients, was one advance. In addition, such things as antibiotic management and tracking were important, because, say, we might find out three days into an antibiotic administration regimen that a patient needs a different antibiotic, or maybe the timing might need to change. Or in another area, questions might come up as to how to handle ICU patients—where is the best place to take them from the ICU? Even if your processes work well nine out of ten times, it’s important to examine what’s going on and to address the issues that emerge.

In other words, a lot of the success in the program seems to have come about through efforts to systematize and standardize care through the use of data analysis?

Isgett:  Absolutely. We had used some data prior to QUEST, but we had looked at the data one disease at a time, but not across diseases. And at first, it almost seemed insurmountable that you would find the common denominators across diseases. And actually, the physicians who had made up that mortality committee in our organization were past chairs of disease-specific quality improvement groups.

Irvin: One of the challenges is moving forward to look at populations. One of the things a doctor is trained to do is to look at the individual patient. When I’m with Mrs. Smith, I’m worried about what’s going on with her. When we’re looking at this kind of data and doing analysis, we’re looking at an entire population, and that’s not something that physicians are trained to do. So to get them to look at that population and take that information, and put that into use, and see it as part of a treatment plan, is where we as physicians really need to get to the next level.

You’ve explained to me that you’re upgrading your electronic health record [EHR] right now, and that right now, your evidence-based order sets are still primarily paper-based, correct?

Irvin: Yes. And the beauty, once we transition to our new EHR, is that we’ll be able to see how and when the doctors have used the evidence-based order sets.  And once everyone is on CPOE [computerized order entry], we’ll find things we need to fix and fix fast, so we’re building into the system mechanisms to help us figure out what’s going on and how to fix it.