Data drives improvement in cardiac surgery
Some people's eyes glaze over when they look at graphs. Donald Likosky's light up. Likosky, a Ph.D. who's a statistician and epidemiologist in Dartmouth's surgery department, points to a graph with a zigzag blue line that peaks at a red dot. A red dot "indicates to the viewer something is different," explains Likosky. "Different can be good. Different can be bad.
A good dot is cause for celebration, while a bad one means "you ought to tweak something," he says. The dot he's pointing at shows a rise in the percentage of patients given aspirin within seven days of a coronary artery bypass graft (CABG). That's good, so no tweaking is needed in this case.
The graph is on a large poster featuring 21 similar graphs, each displaying data on DHMC CABG patients from 2002 through 2006. The graphs chart details such as patients' median age, rates of post-operative bleeding, and average hospital stays. And this poster is just one of five, each of them focused on a different type of cardiothoracic procedure. Likosky's team produces them all.
OR: The data provides information both to DHMC's cardiothoracic surgery section and to the public. The system draws daily from two patient databases: a clinical registry (with information about patients and procedures) and the hospital's administrative records (with information like the OR schedule). The clinical registry is in a database that's compatible with independent graphing software, so Likosky and the department's database manager, John H. Higgins, can design the graphs quickly. That enables them to present current data at monthly meetings of the section's clinical staff. The latest graphs are then posted prominently on a wall that staff walk by regularly.
News: "We need to provide information that is relevant and contemporaneous," says Likosky, "We can't tell them how they did six months ago, because that's old news."
"The nice thing about this kind of data wall," agrees section chief William Nugent, M.D., is that "when you decide there is a problem . . . you are in a great place to change that."
In many of the graphs, DHMC's rates are plotted against regional rates from the Northern New England Cardiovascular Disease Study Group (NNE). The NNE is a voluntary consortium based at DHMC of eight institutions throughout New Hampshire, Maine, and Vermont. Likosky's team recently published a paper based on NNE data in the journal Annals of Thoracic Surgery and expects to soon publish details of the DHMC data project.
The team at DHMC focuses on factors they have the most control over—factors "we can change tomorrow," says Likosky—and those that have a direct effect on patient care. These include use of aspirin after surgery, intra- and post-operative transfusions, or whether the graft vessel for a CABG is taken from the internal mammary artery (IMA) or from a vein in the leg. The graphs chart mortality associated with various factors; both DHMC's and NNE's mortality rates compare favorably to national norms.
And even though DHMC's patients are older and sicker than they used to be, "I'm happy to say that we have not seen a bump in mortality," notes Nugent.
In addition to being shared with the section, the data is also used for DHMC's quality reports website, where mortality rates, infection rates, patient satisfaction, and other such measures are reported to the public (to see these reports, visit the DHMC "Quality Reports" website).
Public: Why the need to generate all this data and make it public? One reason, says Likosky, is that insurance companies, accreditation organizations, and other stakeholders want to know a hospital's clinical outcomes. And it "holds us . . . accountable to our patients."
In addition, he says, "I think it holds us accountable internally [when] we don't measure up the way we want to."
Staff do take the data seriously. The information Likosky marshals has shown, for example, that IMA grafts have lower mortality than leg vein grafts. "Less guesswork. Less art," says Nugent of how he now decides which kind of graft to use.
"It doesn't mean you can't impart your own stamp," he explains. It just means doing so based on the data.
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