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Background Surgical site infections (SSIs) are common, but data related to these infections maybe difficult to capture. We developed an electronic surveillance algorithm to identify patients with SSIs. Our objective was to validate our algorithm by comparing it with our institutional National Surgical Quality Improvement Program Pediatric (NSQIP Peds) data. Methods We applied our algorithm to our institutional NSQIP Peds 2015–2017 cohort. The algorithm consisted of the presence of a diagnosis code for post-operative infection or the presence of 4 criteria: diagnosis code for infection, antibiotic administration, positive culture, and readmission/surgery related to infection. We compared the algorithm’s SSI rate to the NSQIP Peds identified SSI. Algorithm performance was assessed using sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and Cohen’s kappa. The charts of discordant patients were reviewed to understand limitations of the algorithm. Results Of 3879 patients included, 2.5% had SSIs by NSQIP Peds definition and 1.9% had SSIs by our algorithm. Our algorithm achieved a sensitivity of 44%, specificity of 99%, NPV of 99%, PPV of 59%, and Cohen’s kappa of 0.5. Of the 54 false negatives, 37% were diagnosed/treated as outpatients, 31% had tracheitis, and 17% developed SSIs during their post-operative admission. Of the 30 false positives, 33% had an infection at index surgery and 33% had SSIs related to other surgeries/procedures. Conclusions Our algorithm achieved high specificity and NPV compared with NSQIP Peds reported SSIs and may be useful when identifying SSIs in patient populations that are not actively monitored for SSIs.

Introduction Surgical site infections (SSIs) are common and carry a significant risk of morbidity and mortality and lead to increased healthcare costs. Perioperative antibiotic prophylaxis decreases the risk of SSIs. There are several guidelines on the use of perioperative antibiotic prophylaxis. The American College of Surgeons (ACS) recommends weight-based antibiotic administration within 60 minutes prior to (two hours for vancomycin/fluoroquinolones) incision and redosing by drug half-life. There are limited data regarding adherence to existing recommendations. Furthermore, there are scarce data on the relationship between adherence to recommendations and the risk of postoperative SSI. Objectives In this study, we aimed to assess the adherence to ACS guidelines for perioperative antimicrobial prophylaxis in the Seattle Children’s Hospital (SCH) National Surgical Quality Improvement Program (NSQIP) pediatric cohort and to determine whether adherence to ACS guidelines is associated with a decreased risk of SSI. the secondary objective was to identify risk factors associated with SSI in our patient population. Materials and methods We conducted a secondary analysis of an institutional NSQIP pediatric data cohort between Jan 1, 2012, and Dec 31, 2017. We calculated summary statistics to assess adherence to ACS recommendations and fit a logistic regression model to identify factors associated with the risk of SSI. Patients who did not receive antibiotic prophylaxis were excluded. Results A total of 6,072 surgeries among 5,532 patients met the inclusion criteria. Adherence was achieved for weight-based dosing in 35% of surgeries, administration prior to the incision in 91%, administration within 60 minutes (two hours for vancomycin/fluoroquinolones) in 86%, correct redosing in 97%, and to all recommendations in 29%. There were no significant associations between any adherence metrics and SSI, although confidence intervals were wide for some metrics. Factors associated with SSI when adherence was met included urgent case status, wound class 2 or 4, the American Society of Anesthesiologists (ASA) class 2-5, and surgery duration. Conclusion There was varying adherence to ACS recommendations on antibiotic prophylaxis in our cohort. More evidence is needed to better understand the effects of adherence to any or all components of the recommendations on SSI. We identified a group of pediatric patients at risk of SSI and a need for further research and targeted interventions.

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