Changing the way we interpret SCIP measures
Briefings on Infection Control, September 1, 2010
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In 2006, a number of national organizations—including The Joint Commission, the CDC, and CMS—collaborated with one goal in mind: to improve surgical care by significantly reducing surgical complications.
As a result, in July 2006, the Surgical Care Improvement Project (SCIP) was born, and hospitals began publicly reporting on compliance with the following infection prevention measures:
- SCIP INF 1: Prophylactic antibiotic received within one hour prior to surgical incision
- SCIP INF 2: Prophylactic antibiotic selection for surgical patients
- SCIP INF 3: Prophylactic antibiotics discontinued within 24 hours after surgery end time (48 hours for cardiac patients)
- SCIP INF 4: Cardiac surgery patients with controlled 6 a.m. postoperative serum glucose
- SCIP INF 6: Surgery patients with appropriate hair removal
- SCIP INF 7: Colorectal surgery patients with immediate postoperative normothermia
Compliance with these six measures translated to better-quality care, and patients could access the information in order to choose the hospital with the lowest infection rates. The initiative aimed to reduce surgical complications by 25% by 2010.
But a new study published in the July 23 Journal of the American Medical Association indicates that compliance with individual SCIP measures did not translate to a decreased risk of developing a postoperative infection. Rather, reporting aggregate data (compliance with two or more measures) showed a decreased risk of infection.
“We didn’t feel that individual measures or the individual measures that were reported would necessarily be associated, but we felt that the underlying practices through these randomized control trials and other studies are probably associated,” says Jonah J. Stulberg, MD, PhD, MPH, a recent graduate of Case Western Reserve University School of Medicine and the lead author of the study. “So we felt there might be more benefit to aggregating those measures to get better power out of our estimation that we truly wanted to be able to publicly report quality data that was associated with improved outcomes.”
The study also sought to determine whether compliance with individual measures was a fair indicator of quality, especially since these measures are publicly reported.
“I think there is an underlying assumption that some hospitals are better than others,” Stulberg says. “Some hospitals provide better quality of care than others, right? If all of the hospitals are collecting this data, and there is variation in quality, why can’t we see it in the individual methods? That’s kind of the question that is out there that my study tried to answer.”
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