Guest Post: A "Hybrid" Surveillance approach for SSI

Dr. Connie Savor Price has been co-project director and PI on a 2009 AHRQ ACTION contract charged with improving the measurement of surgical site infection risk stratification and outcome detection. The final report has just been published online and she was kind enough to stop by our humble blog to briefly describe the project.

With pressure on infection control programs to expand surveillance for public reporting and pay-for -performance, increasing surveillance efficiency without sacrificing data validity creates a conundrum. Purely automated systems for surgical site infection (SSI) surveillance have been developed and utilized, but are not validated or generalizable for these purposes.

In this report, we describe development of "hybrid" surveillance approach using highly sensitive electronic algorithms for detection of SSI targeted for subsequent human-adjudication. Electronic algorithms to detect deep and organ-space SSI after coronary artery bypass grafting, total hip and knee arthroplasties, and herniorrhaphies were created using a sample of nationwide Veterans Affairs Surgical Quality Improvement Program data (VASQIP). The algorithms were tested against VASQIP data, and then assessed for generalization using data from hospitals from three different, external (non-VA) healthcare systems.

Although all algorithms performed reasonably well at identifying deep and organ-space SSI among the VASQIP test data set, performance was variable when tested against data from the outside systems. As one would expect, the observed variation was primarily due to differences in the data collected and stored electronically in each system. While not surprising, perhaps some are disappointed that this research did not produce a universally applicable surveillance tool for "out-of-the-box" utility for all infection control programs. But just wait. As meaningful use incentives help us move toward interoperable electronic health records throughout the United States, this surveillance strategy will hold promise as a reliable tool for detecting potential surgical site infection.