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Background. There are limited data on risk factors for surgical site infection (SSI) after open or laparoscopic cholecystectomy. Methods. A retrospective cohort of commercially insured persons aged 18-64 years was assembled using International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) procedure or Current Procedural Terminology, 4th edition codes for cholecystectomy from December 31, 2004 to December 31, 2010. Complex procedures and patients (eg, cancer, end-stage renal disease) and procedures with pre-existing infection were excluded. Surgical site infections within 90 days after cholecystectomy were identified by ICD-9-CM diagnosis codes. A Cox proportional hazards model was used to identify independent risk factors for SSI. Results. Surgical site infections were identified after 472 of 66 566 (0.71%) cholecystectomies; incidence was higher after open (n = 51, 4.93%) versus laparoscopic procedures (n = 421, 0.64%; P < .001). Independent risk factors for SSI included male gender, preoperative chronic anemia, diabetes, drug abuse, malnutrition/weight loss, obesity, smoking-related diseases, previous Staphylococcus aureus infection, laparoscopic approach with acute cholecystitis/obstruction (hazards ratio [HR], 1.58; 95% confidence interval [CI], 1.27-1.96), open approach with (HR, 4.29; 95% CI, 2.45-7.52) or without acute cholecystitis/obstruction (HR, 4.04; 95% CI, 1.96-8.34), conversion to open approach with (HR, 4.71; 95% CI, 2.74-8.10) or without acute cholecystitis/obstruction (HR, 7.11; 95% CI, 3.87-13.08), bile duct exploration, postoperative chronic anemia, and postoperative pneumonia or urinary tract infection. Conclusions. Acute cholecystitis or obstruction was associated with significantly increased risk of SSI with laparoscopic but not open cholecystectomy. The risk of SSI was similar for planned open and converted procedures. These findings suggest that stratification by operative factors is important when comparing SSI rates between facilities. [ABSTRACT FROM AUTHOR]

Background: Accurate identification of underlying health conditions is important to fully adjust for confounders in studies using insurer claims data. Our objective was to evaluate the ability of four modifications to a standard claims-based measure to estimate the prevalence of select comorbid conditions compared with national prevalence estimates.Methods: In a cohort of 11,973 privately insured women aged 18-64 years with mastectomy from 1/04-12/11 in the HealthCore Integrated Research Database, we identified diabetes, hypertension, deficiency anemia, smoking, and obesity from inpatient and outpatient claims for the year prior to surgery using four different algorithms. The standard comorbidity measure was compared to revised algorithms which included outpatient medications for diabetes, hypertension and smoking; an expanded timeframe encompassing the mastectomy admission; and an adjusted time interval and number of required outpatient claims. A χ2 test of proportions was used to compare prevalence estimates for 5 conditions in the mastectomy population to national health survey datasets (Behavioral Risk Factor Surveillance System and the National Health and Nutrition Examination Survey). Medical record review was conducted for a sample of women to validate the identification of smoking and obesity.Results: Compared to the standard claims algorithm, use of the modified algorithms increased prevalence from 4.79 to 6.79 % for diabetes, 14.75 to 24.87 % for hypertension, 4.23 to 6.65 % for deficiency anemia, 1.78 to 12.87 % for smoking, and 1.14 to 6.31 % for obesity. The revised estimates were more similar, but not statistically equivalent, to nationally reported prevalence estimates. Medical record review revealed low sensitivity (17.86 %) to capture obesity in the claims, moderate negative predictive value (NPV, 71.78 %) and high specificity (99.15 %) and positive predictive value (PPV, 90.91 %); the claims algorithm for current smoking had relatively low sensitivity (62.50 %) and PPV (50.00 %), but high specificity (92.19 %) and NPV (95.16 %).Conclusions: Modifications to a standard comorbidity measure resulted in prevalence estimates that were closer to expected estimates for non-elderly women than the standard measure. Adjustment of the standard claims algorithm to identify underlying comorbid conditions should be considered depending on the specific conditions and the patient population studied. [ABSTRACT FROM AUTHOR]