The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) provides more accurate data for driving improvements in surgical quality than two other sources of administrative data, according to two new studies.
ACS NSQIP data proved more accurate than either administrative claims data used for billing purposes or National Inpatient Sample (NIS) data, according to studies conducted at hospitals in Northern Virginia, southern California and Boston. Researchers presented the results last week at an American College of Surgeons conference, according to a study announcement.
For the analysis involving National Inpatient Sample data, researchers examined data for 300,00 patients that underwent 11 major surgical procedures during 2010 at the University of California San Diego, University of California Davis and Massachusetts General Hospital.
They found that unadjusted rates for surgical complications were higher for hospitals that used the NIS, while unadjusted mortality rates were lower in hospitals that used ACS NSQIP.
"We are actually improving our own outcomes by studying them," lead study author Anna Weiss, M.D., a surgical resident at UC San Diego, said in presenting the findings, according to the article.
In the second study, researchers at Virginia's Inova Health System found that ACS NSQIP data provided more accurate predictions of hospital readmissions within 30 days of general, endovascular and colorectal surgical procedures than administrative claims data, according to the article.
They also determined the clinical data could potentially prevent roughly 60 percent of readmissions. That finding echoed one from another study published earlier this year in JAMA Surgery, in which researchers from the University of Rochester Medical Center found that using the ACS NSQIP can help doctors predict which patients will experience post-surgical complications and therefore reduce unplanned readmissions.
In the case of the Inova study, researchers suspect the difference in outcomes can be attributed to the precise diagnostic coding information in the ACS NSQIP data, said lead study author Amber Trickey, Ph.D., a surgery epidemiologist and biostatistician at Inova Fairfax Hospital.
Hospitals are increasingly turning to predictive analytics to help reduce post-surgical complications. Using such tools, the University of Iowa Hospitals and Clinics, for example, cut its infection rates for colon surgery patients 58 percent over two years.