Objective The National Healthcare Safety Network classifies breast operations as clean procedures with an expected 1–2% surgical site infection (SSI) incidence. We assessed differences in SSI incidence following mastectomy with and without immediate reconstruction in a large, geographically diverse population. Design Retrospective cohort study. Patients Commercially-insured women aged 18–64 years with ICD-9-CM procedure or CPT-4 codes for mastectomy from 1/1/2004–12/31/2011. Methods Incident SSIs within 180 days after surgery were identified by ICD-9-CM diagnosis codes. The incidence of SSI after mastectomy +/− immediate reconstruction was compared by the chi-square test. Results From 2004–2011, 18,696 mastectomy procedures among 18,085 women were identified, with immediate reconstruction in 10,836 (58%) procedures. The 180-day incidence of SSI following mastectomy with or without reconstruction was 8.1% (1,520/18,696). Forty-nine percent of SSIs were identified within 30 days post-mastectomy, 24.5% between 31–60 days, 10.5% between 61–90 days, and 15.7% between 91–180 days. The incidence of SSI was 5.0% (395/7,860) after mastectomy-only, 10.3% (848/8,217) after mastectomy plus implant, 10.7% (207/1,942) after mastectomy plus flap, and 10.3% (70/677) after mastectomy plus flap and implant (p<0.001). The SSI risk was higher after bilateral compared with unilateral mastectomy with (11.4% vs. 9.4%, p=0.001) and without (6.1% vs. 4.7%, p=0.021) immediate reconstruction. Conclusions SSI incidence was two-fold higher after mastectomy with immediate reconstruction than after mastectomy alone. Only 49% of SSIs were coded within 30 days after operation. Our results suggest stratification by procedure type will facilitate comparison of SSI rates after breast operations between facilities.

Background Little data are available regarding individual patients’ risk of surgical site infection (SSI) following mastectomy with or without immediate reconstruction. Our objective was to develop a risk prediction model for mastectomy-related SSI. Methods We established a cohort of women < 65 years of age with mastectomy from 1/1/2004–12/31/2011 using commercial claims data. ICD-9-CM diagnosis codes were used to identify SSI within 180 days after surgery. SSI risk factors were determined with multivariable logistic regression using derivation data from 2004-2008 and validated with 2009–2011 data using discrimination and calibration measures. Results In the derivation cohort 595 SSIs were identified in 7,607 (7.8%) women, and 396 SSIs were coded in 4,366 (9.1%) women in the validation cohort. Independent risk factors for SSIs included rural residence, rheumatologic disease, depression, diabetes, hypertension, liver disease, obesity, preexisting pneumonia or urinary tract infection, tobacco use disorder, smoking-related diseases, bilateral mastectomy, and immediate reconstruction. Receipt of home health care was associated with lower risk. The model performed equally in the validation cohort per discrimination (C statistics 0.657 and 0.649) and calibration (Hosmer-Lemeshow P=0.091 and 0.462 for derivation and validation, respectively). Three risk strata were created based on predicted SSI risk, which demonstrated good correlation with the proportion of observed infections in the strata. Conclusions We developed and internally validated an SSI risk prediction model that can be used to counsel women concerning their individual risk of SSI post-mastectomy. Immediate reconstruction, diabetes, and smoking-related diseases were important risk factors for SSI in this nonelderly population of women undergoing mastectomy.

Objective To evaluate a central line care maintenance bundle to reduce central line-associated bloodstream infection (CLABSI) in non-ICU settings. Design Before-after trial with 12 month follow-up period. Setting 1250-bed teaching hospital. Participants Patients with central lines on eight general medicine wards. Four wards received the intervention and four served as controls. Intervention A multifaceted catheter care maintenance bundle consisting of educational programs for nurses, update of hospital policies, visual aids, a competency assessment, process monitoring, regular progress reports, and consolidation of supplies necessary for catheter maintenance. Results Data were collected for 25,542 catheter-days including 43 CLABSI (rate = 1.68 per 1,000 CL-days) and 4,012 catheter dressing observations. Following the intervention, a 2.5% monthly decrease in the CLABSI incidence density was observed on intervention floors, but this was not statistically significant (95% confidence interval (CI); −5.3 – 0.4). On control floors, there was a smaller, but marginally significant decrease in CLABSI incidence during the study (change in monthly rate = −1.1%; 95% CI, −2.1 - −0.1). Implementation of the bundle was associated with improvement in catheter dressing compliance on intervention wards (78.8% compliance pre-intervention vs. 87.9% during intervention/follow-up; p<0.001) but improvement was also observed on control wards (84.9% compliance pre-intervention vs. 90.9% during intervention/follow-up; P = .001). Conclusions A multi-faceted program to improve catheter care was associated with improvement in catheter dressing care, but no change in CLABSI rates. Additional study is needed to determine strategies to prevent CLABSI in non-ICU patients.

BackgroundAccurate 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.MethodsIn 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.ResultsCompared 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 %).ConclusionsModifications 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12913-016-1636-7) contains supplementary material, which is available to authorized users.

Background Few studies have validated ICD-9-CM diagnosis codes for surgical site infection (SSI), and none have validated coding for noninfectious wound complications after mastectomy. Objectives To determine the accuracy of ICD-9-CM diagnosis codes in administrative health insurer claims data to identify SSI and noninfectious wound complications, including hematoma, seroma, fat and tissue necrosis, and dehiscence, after mastectomy. Methods We reviewed medical records for 275 randomly selected women who were coded for mastectomy with or without immediate breast reconstruction and were coded with an ICD-9-CM diagnosis code for a wound complication within 180 days after surgery. We calculated the positive predictive value (PPV) to evaluate the accuracy of diagnosis codes to identify specific wound complications and the PPV to determine the accuracy of coding for the breast surgical procedure. Results The PPV for SSI was 57.5%, or 68.9% if cellulitis-alone was considered an SSI, while the PPV for coding of cellulitis was 82.2%. The PPVs of individual noninfectious wound complications ranged from 47.8% for fat necrosis to 94.9% for seroma and 96.6% for hematoma. The PPVs for mastectomy, implant, and autologous flap reconstruction were uniformly high (97.5%–99.2%). Conclusions Our results suggest that claims data can be used to compare rates of infectious and noninfectious wound complications after mastectomy across facilities, although the PPV varies by specific type of postoperative complication. The accuracy of coding was highest for cellulitis, hematoma, and seroma, and a composite group of noninfectious complications (fat necrosis, tissue necrosis, or dehiscence).