A framework to develop semiautomated surveillance of surgical site infections: An international multicenter study.

OBJECTIVE: Automated surveillance of healthcare-associated infections reduces workload and improves standardization, but it has not yet been adopted widely. In this study, we assessed the performance and feasibility of an easy implementable framework to develop algorithms for semiautomated surveillance of deep incisional and organ-space surgical site infections (SSIs) after orthopedic, cardiac, and colon surgeries. DESIGN: Retrospective cohort study in multiple countries. METHODS: European hospitals were recruited and selected based on the availability of manual SSI surveillance data from 2012 onward (reference standard) and on the ability to extract relevant data from electronic health records. A questionnaire on local manual surveillance and clinical practices was administered to participating hospitals, and the information collected was used to pre-emptively design semiautomated surveillance algorithms standardized for multiple hospitals and for center-specific application. Algorithm sensitivity, positive predictive value, and reduction of manual charts requiring review were calculated. Reasons for misclassification were explored using discrepancy analyses. RESULTS: The study included 3 hospitals, in the Netherlands, France, and Spain. Classification algorithms were developed to indicate procedures with a high probability of SSI. Components concerned microbiology, prolonged length of stay or readmission, and reinterventions. Antibiotics and radiology ordering were optional. In total, 4,770 orthopedic procedures, 5,047 cardiac procedures, and 3,906 colon procedures were analyzed. Across hospitals, standardized algorithm sensitivity ranged between 82% and 100% for orthopedic surgery, between 67% and 100% for cardiac surgery, and between 84% and 100% for colon surgery, with 72%-98% workload reduction. Center-specific algorithms had lower sensitivity. CONCLUSIONS: Using this framework, algorithms for semiautomated surveillance of SSI can be successfully developed. The high performance of standardized algorithms holds promise for large-scale standardization.

[Cluster outbreak of MRSA in the community; recognition and approach]. / Clusteruitbraak MRSA buiten het ziekenhuis; herkennen en aanpakken.

BACKGROUND: Community-acquired infection with methicillin-resistant Staphylococcus aureus (CA-MRSA) mainly affects healthy young people, without health-care related risk factors for MRSA. Patients often present with skin and soft-tissue infections. CASE DESCRIPTION: An 18-year-old woman presented at the casualty department with recurrent purulent skin infections. She proved to be MRSA-positive. Within 6 months, 2 people around her also developed an MRSA infection. Culture showed CA-MRSA, with an identical strain (spa type: t008). Additional screening within her immediate circle identified 4 carriers, 2 of whom had corresponding skin infections. CONCLUSION: Cluster outbreaks of CA-MRSA require a coordinated approach from both the treating physician and the public health services. The choice of additional investigation among the circle of contacts was the determining factor in breaking the cycle of transmission and reinfection within this cluster.