scholarly journals Surgical site infections in outpatient surgeries: Less invasive procedures contribute substantially to the overall burden

2019 ◽  
Vol 40 (10) ◽  
pp. 1191-1193
Author(s):  
Katherine Linsenmeyer ◽  
Westyn Branch-Elliman ◽  
Emily Kalver ◽  
Hillary J. Mull

AbstractMore than 50% of outpatient surgeries predicted to have an increased likelihood of an adverse event were excluded from surgical site infection (SSI) surveillance based on Veterans Affairs Surgical Quality Improvement Program (VASQIP) eligibility criteria, defined by clinician determination of invasiveness. Burden of SSI for eligible versus ineligible surgeries was similar; thus, surveillance activities in the outpatient setting need to be re-evaluated.

Author(s):  
Alaia M. M. Christensen ◽  
Karen Dowler ◽  
Shira Doron

Abstract Surgical site infections (SSIs) are associated with readmissions, reoperations, increased cost of care, and overall morbidity and mortality risk. The National Healthcare Safety Network (NHSN) and the National Surgical Quality Improvement Program (NSQIP) have developed an array of metrics to monitor hospital-acquired complications. The only metric collected by both is SSI, but performance as benchmarked against peer hospitals is often discordant between the 2 systems. In this commentary, we outline the differences between these 2 surveillance systems as they relate to this potential for discordance.


2018 ◽  
Vol 84 (6) ◽  
pp. 1039-1042 ◽  
Author(s):  
Jonathan B. Imran ◽  
Oswaldo Renteria ◽  
Maria Ruiz ◽  
Thai H. Pham ◽  
Ali A. Mokdad ◽  
...  

The Veterans Affairs Surgical Quality Improvement Program (VASQIP) risk calculator has been validated for several operations but has not been assessed specifically for cholecystectomy. Our aim was to externally validate the VASQIP calculator's accuracy in predicting 30-day morbidity and mortality (M&M) for patients undergoing cholecystectomy. A retrospective review of patients undergoing cholecystectomy at the North Texas Veterans Affairs hospital was performed. The VASQIP risk calculator was used to determine predicted 30-day M&M, which was compared with actual M&M. The predictive accuracy of the Veterans Affairs risk calculator was assessed using the C-statistic and a graphical assessment of a locally weighted least squares regression smoother. Overall, 848 patients were included in the study. Actual M&M were 6.3 and 0.94 per cent, respectively, whereas predicted M&M were 6.0 and 0.54 per cent. The C-statistic was 0.75 for morbidity and 0.78 for mortality. In our analysis, the VASQIP risk calculator reasonably predicted 30-day M&M.


2018 ◽  
Vol 24 (8) ◽  
pp. 1833-1839 ◽  
Author(s):  
Bharati Kochar ◽  
Edward L Barnes ◽  
Anne F Peery ◽  
Katherine S Cools ◽  
Joseph Galanko ◽  
...  

Abstract Background Ulcerative colitis (UC) patients requiring colectomy often have a staged ileal pouch anal anastomosis (IPAA). There are no prospective data comparing timing of pouch creation. We aimed to compare 30-day adverse event rates for pouch creation at the time of colectomy (PTC) with delayed pouch creation (DPC). Methods Using prospectively collected data from 2011–2015 through the National Surgical Quality Improvement Program, we conducted a cohort study including subjects aged ≥18 years with a postoperative diagnosis of UC. We assessed 30-day postoperative rates of unplanned readmissions, reoperations, and major and minor adverse events (AEs), comparing the stage of the surgery where the pouch creation took place. Using a modified Poisson regression model, we estimated risk ratios (RRs) with 95% confidence intervals (CIs) adjusting for age, sex, race, body mass index, smoking status, diabetes, albumin, and comorbidities. Results Of 2390 IPAA procedures, 1571 were PTC and 819 were DPC. In the PTC group, 51% were on chronic immunosuppression preoperatively, compared with 15% in the DPC group (P < 0.01). After controlling for confounders, patients who had DPC were significantly less likely to have unplanned reoperations (RR, 0.42; 95% CI, 0.24–0.75), major AEs (RR, 0.72; 95% CI, 0.52–0.99), and minor AEs (RR, 0.48; 95% CI, 0.32–0.73) than PTC. Conclusions Patients undergoing delayed pouch creation were at lower risk for unplanned reoperations and major and minor adverse events compared with patients undergoing pouch creation at the time of colectomy.


Author(s):  
Claudia Berrondo ◽  
Brendan Bettinger ◽  
Cindy B Katz ◽  
Jennifer Bauer ◽  
Margarett Shnorhavorian ◽  
...  

Abstract 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.


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