Using Surveillance Data to Direct Infection Control Efforts to Reduce Surgical-Site Infections Following Clean Abdominal Operations in Japan

2002 ◽  
Vol 23 (7) ◽  
pp. 404-406 ◽  
Author(s):  
Keita Morikane ◽  
Midori Nishioka ◽  
Hisami Tanimura ◽  
Hiroe Noguchi ◽  
Toshiro Konishi ◽  
...  
Keyword(s):  
Infection Control ◽  
Disease Control ◽  
Nosocomial Infections ◽  
Surgical Site Infections ◽  
Surveillance Data ◽  
Control And Prevention ◽  
Abdominal Operations ◽  
Centers For Disease Control ◽  
Clean Contaminated

AbstractWe initiated surveillance for surgical-site infections (SSIs) in a Japanese hospital using Centers for Disease Control and Prevention definitions and the approach of the National Nosocomial Infections Surveillance (NNIS) System. Patients were observed following clean and clean-contaminated abdominal operations. SSI rates were higher than those of the NNIS System, but there was a trend toward decreased SSI rates in the latter half of the study period.

scholarly journals Surveying the Surveillance: Surgical Site Infections Excluded by the January 2013 Updated Surveillance Definitions

2014 ◽  
Vol 35 (5) ◽  
pp. 570-573 ◽  
Author(s):  
Kristen V. Dicks ◽  
Sarah S. Lewis ◽  
Michael J. Durkin ◽  
Arthur W. Baker ◽  
Rebekah W. Moehring ◽  
...  
Keyword(s):  
Disease Control ◽  
Surgical Site Infections ◽  
National Healthcare ◽  
National Healthcare Safety Network ◽  
Control And Prevention ◽  
Centers For Disease Control

The updated 2013 Centers for Disease Control and Prevention/National Healthcare Safety Network definitions for surgical site infections (SSIs) reduced the duration of prolonged surveillance from 1 year to 90 days and defined which procedure types require prolonged surveillance. Applying the updated 2013 SSI definitions to cases analyzed using the pre-2013 surveillance definitions excluded 10% of previously identified SSIs.

scholarly journals Improving Risk Adjustment Above Current Centers for Disease Control and Prevention Methodology Using Electronically Available Comorbid Conditions

2016 ◽  
Vol 37 (10) ◽  
pp. 1173-1178 ◽  
Author(s):  
Sarah S. Jackson ◽  
Surbhi Leekha ◽  
Lisa Pineles ◽  
Laurence S. Magder ◽  
Kerri A. Thom ◽  
...  
Keyword(s):  
Renal Transplantation ◽  
Disease Control ◽  
Risk Adjustment ◽  
Surgical Site Infections ◽  
Bivariate Analysis ◽  
Data Repository ◽  
Comorbid Conditions ◽  
C Statistic ◽  
Control And Prevention ◽  
Centers For Disease Control

OBJECTIVETo identify comorbid conditions associated with surgical site infection (SSI) among patients undergoing renal transplantation and improve existing risk adjustment methodology used by the Centers for Disease Control and Prevention National Healthcare Safety Network (NHSN).PATIENTSPatients (≥18 years) who underwent renal transplantation at University of Maryland Medical Center January 1, 2010-December 31, 2011.METHODSTrained infection preventionists reviewed medical records to identify surgical site infections that developed within 30 days after transplantation, using NHSN criteria. Patient demographic characteristics and risk factors for surgical site infections were identified through a central data repository. International Statistical Classification of Disease, Ninth Revision, Clinical Modification codes were used to analyze individual component comorbid conditions and calculate the Charlson and Elixhauser comorbidity indices. These indices were compared with the current NHSN risk adjustment methodology.RESULTSA total of 441 patients were included in the final cohort. In bivariate analysis, the Charlson components of cerebrovascular disease, peripheral vascular disease, and rheumatologic disorders and Elixhauser components of obesity, rheumatoid arthritis, and weight loss were significantly associated with the outcome. A model utilizing the variables from the NHSN methodology had a c-statistic of 0.56 (95% CI, 0.48–0.63), whereas a model that also included comorbidities from the Charlson and Elixhauser indices had a c-statistic of 0.65 (95% CI, 0.58–0.73). The model with all 3 risk adjustment scores performed best and was statistically different from the NHSN model alone, demonstrated by improvement in the c statistic (0.65 vs 0.56).CONCLUSIONRisk adjustment models should incorporate electronically available comorbid conditions.Infect Control Hosp Epidemiol 2016;1–6

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