Objective: To evaluate different strategies for detecting surgical site infections (SSIs) using different sources (notification by the surgeon, bacteriological results, antibiotic prescription, and discharge diagnosis codes).
Background: Surveillance plays a role in reducing the risks of SSIs but the performance of case reports by surgeons is insufficient. Indirect methods of SSI detection are an alternative to increase the quality of surveillance.
Methods: A retrospective cohort study of 446 patients operated consecutively during the first half of 2007 was set up in a 56-bed general surgery unit in Lyon University Hospital, France. Patients were followed up 30 days after intervention. Different methods of detection were established by combining different data sources. The sensitivity and specificity of these methods were calculated by using, as reference method, the manual review of the medical records.
Results: The sensitivity and specificity of SSI detection were, respectively, 18.4% (95% confidence interval [CI]: 7.9–31.6) and 100% for surgeon notification; 63.2% (95% CI: 47.3–78.9) and 95.1% (95% CI: 92.9–97.1) for detection based on positive cultures; 68.4% (95% CI: 52.6–81.6) and 87.5% (95% CI: 84.3–90.7) using antibiotic prescription; 26.3% (95% CI: 13.2–42.1) and 99.5% (95% CI: 98.8–100) using discharge diagnosis codes. By combining the latter 3 sources, the sensitivity increased at 86.8% (95% CI: 76.3 – 97.4) and the specificity was lowered at 85.5% (95% CI: 82.1 – 89.0).
Conclusions: SSI detection based on the combination of data extracted automatically from the hospital information system performed well. This strategy has been implemented gradually in Lyon University Hospital.