ArticleInfection control and hospital epidemiology2017
The Effect of Adding Comorbidities to Current Centers for Disease Control and Prevention Central-Line-Associated Bloodstream Infection Risk-Adjustment Methodology.
Article in Infection control and hospital epidemiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Risk factors of catheter- associated bloodstream infection: Systematic review and meta-analysis.PloS one · 2023Pooled it
- Risk Factor Prediction Model for Catheter-Associated Bloodstream Infections (CABSIs) in Midline and Central Venous Catheters: A Cohort Follow-Up Study.Journal of clinical medicine · 2026Article
- New Kids on the Block: Estimating Use of Next-generation Gram-negative Antibiotics Across Greater Than 700 Hospitals in the United States.Open forum infectious diseases · 2025Article
- Article
- Clinical Impacts and Risk Factors for Central Line-Associated Bloodstream Infection: A Systematic Review.Cureus · 2023Review
- Patterns, Predictors, and Intercenter Variability in Empiric Gram-Negative Antibiotic Use Across 928 United States Hospitals.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Article
- Hospital-onset bacteremia and fungemia: An evaluation of predictors and feasibility of benchmarking comparing two risk-adjusted models among 267 hospitals.Infection control and hospital epidemiology · 2022Article
- Central line-associated bloodstream infections at the multidisciplinary intensive care unit of Universitas Academic Hospital, Bloemfontein, South Africa.African journal of thoracic and critical care medicine · 2022Article
- The Limited Utility of Ranking Hospitals Based on Their Colon Surgery Infection Rates.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2021Article
- Asymptomatic central line-associated bloodstream infections in children implanted with long term indwelling central venous catheters in a teaching hospital, Sri Lanka.BMC infectious diseases · 2020Article
- Comparison of Rates of Central Line-Associated Bloodstream Infections in Patients With 1 vs 2 Central Venous Catheters.JAMA network open · 2020Article
- Electronically Available Comorbid Conditions for Risk Prediction of Healthcare-Associated Clostridium difficile Infection.Infection control and hospital epidemiology · 2018Article
- Problematic Risk Adjustment in National Healthcare Safety Network Measures.American journal of medical quality : the official journal of the American College of Medical QualityArticle
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12 authors.
Funding
Abstract
BACKGROUND Risk adjustment is needed to fairly compare central-line-associated bloodstream infection (CLABSI) rates between hospitals. Until 2017, the Centers for Disease Control and Prevention (CDC) methodology adjusted CLABSI rates only by type of intensive care unit (ICU). The 2017 CDC models also adjust for hospital size and medical school affiliation. We hypothesized that risk adjustment would be improved by including patient demographics and comorbidities from electronically available hospital discharge codes. METHODS Using a cohort design across 22 hospitals, we analyzed data from ICU patients admitted between January 2012 and December 2013. Demographics and International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) discharge codes were obtained for each patient, and CLABSIs were identified by trained infection preventionists. Models adjusting only for ICU type and for ICU type plus patient case mix were built and compared using discrimination and standardized infection ratio (SIR). Hospitals were ranked by SIR for each model to examine and compare the changes in rank. RESULTS Overall, 85,849 ICU patients were analyzed and 162 (0.2%) developed CLABSI. The significant variables added to the ICU model were coagulopathy, paralysis, renal failure, malnutrition, and age. The C statistics were 0.55 (95% CI, 0.51-0.59) for the ICU-type model and 0.64 (95% CI, 0.60-0.69) for the ICU-type plus patient case-mix model. When the hospitals were ranked by adjusted SIRs, 10 hospitals (45%) changed rank when comorbidity was added to the ICU-type model. CONCLUSIONS Our risk-adjustment model for CLABSI using electronically available comorbidities demonstrated better discrimination than did the CDC model. The CDC should strongly consider comorbidity-based risk adjustment to more accurately compare CLABSI rates across hospitals. Infect Control Hosp Epidemiol 2017;38:1019-1024.
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