Intensity of Vascular Catheter Use in Critical Care: Impact on Catheter-Associated Bloodstream Infection Rates and Association with Severity of Illness

2012 ◽  
Vol 33 (12) ◽  
pp. 1268-1270 ◽  
Author(s):  
Kimberlee S. Fong ◽  
Mary Banks ◽  
Rebekah Benish ◽  
Cynthia Fatica ◽  
Melissa Triche ◽  
...  
1987 ◽  
Vol 8 (3) ◽  
pp. 108-112 ◽  
Author(s):  
Richard I. Stillman ◽  
Richard P. Wenzel ◽  
Leigh C. Donowitz

AbstractOver an eight year period, 1975 to 1982, 1,843 nosocomial bloodstream infections were identified by routine prospective surveillance at the University of Virginia Hospital (106/10,000 admissions). Despite a decline in overall bloodstream infection rates during the study period (P =.085), bloodstream infections due to gram positive organisms increased from 29 (1975-1978) to 43/10,000 (1979-1982), (P<0.001). Notably, rates for coagulase negative staphylococci increased from 5.2 (1975-1978) to 12.4/10,000 (1979-1982), (P<0.001). In 1982, coagulase negative staphylococci accounted for 17% of all bloodstream infections and were the most frequently isolated pathogens. Sixty-four percent of patients with coagulase negative staphylococci were in critical care units versus 41% with other bloodstream infections (P<.05). The recognition of coagulase negative staphylococci as significant bloodstream pathogens markedly alters the clinician's approach to nosocomial septicemia.


2016 ◽  
Vol 52 (3) ◽  
pp. 1079-1098 ◽  
Author(s):  
Hangsheng Liu ◽  
Carolyn T. A. Herzig ◽  
Andrew W. Dick ◽  
E. Yoko Furuya ◽  
Elaine Larson ◽  
...  

2015 ◽  
Vol 36 (6) ◽  
pp. 649-655 ◽  
Author(s):  
Louise Elaine Vaz ◽  
Kenneth P. Kleinman ◽  
Alison Tse Kawai ◽  
Robert Jin ◽  
William J. Kassler ◽  
...  

BACKGROUNDPolicymakers may wish to align healthcare payment and quality of care while minimizing unintended consequences, particularly for safety net hospitals.OBJECTIVETo determine whether the 2008 Centers for Medicare and Medicaid Services Hospital-Acquired Conditions policy had a differential impact on targeted healthcare-associated infection rates in safety net compared with non–safety net hospitals.DESIGNInterrupted time-series design.SETTING AND PARTICIPANTSNonfederal acute care hospitals that reported central line–associated bloodstream infection and ventilator-associated pneumonia rates to the Centers for Disease Control and Prevention’s National Health Safety Network from July 1, 2007, through December 31, 2013.RESULTSWe did not observe changes in the slope of targeted infection rates in the postpolicy period compared with the prepolicy period for either safety net (postpolicy vs prepolicy ratio, 0.96 [95% CI, 0.84–1.09]) or non–safety net (0.99 [0.90–1.10]) hospitals. Controlling for prepolicy secular trends, we did not detect differences in an immediate change at the time of the policy between safety net and non–safety net hospitals (P for 2-way interaction, .87).CONCLUSIONSThe Centers for Medicare and Medicaid Services Hospital-Acquired Conditions policy did not have an impact, either positive or negative, on already declining rates of central line–associated bloodstream infection in safety net or non–safety net hospitals. Continued evaluations of the broad impact of payment policies on safety net hospitals will remain important as the use of financial incentives and penalties continues to expand in the United States.Infect Control Hosp Epidemiol 2015;00(0): 1–7


2012 ◽  
Vol 6 (2) ◽  
pp. 126-130 ◽  
Author(s):  
Jill S. Sweney ◽  
W. Bradley Poss ◽  
Colin K. Grissom ◽  
Heather T. Keenan

ABSTRACTObjective: A pediatric triage tool is needed during times of resource scarcity to optimize critical care utilization. This study compares the modified sequential organ failure assessment score (M-SOFA), the Pediatric Early Warning System (PEWS) score, the Pediatric Risk of Admission Score II (PRISA-II), and physician judgment to predict the need for pediatric intensive care unit (PICU) interventions.Methods: This retrospective cohort study evaluates three illness severity scores for all non-neonatal pediatric patients transported and admitted to a single center in 2006. The outcome of interest was receipt of a PICU intervention (mechanical ventilation, acute dialysis, depressed consciousness, or persistent hypotension). Predictive ability was assessed using receiver operating curves (ROCs).Results: Of 752 patients admitted to the hospital, 287 received a PICU intervention. Median scores for all tools were significantly higher for children receiving an intervention than for those who did not. ROCs showed PEWS had the least discriminatory ability, followed by PRISA-II and pediatric M-SOFA. No value of the pediatric M-SOFA produced both positive and negative predictive values better than clinician judgment.Conclusions: No score had a clinically acceptable discriminate ability to predict patients who required a PICU intervention from those who did not. Physician judgment outperformed all three triage scores.(Disaster Med Public Health Preparedness. 2012;6:126–130)


2015 ◽  
Author(s):  
Mark T. Keegan

Critical care consumes about 4% of national health expenditure and 0.65% of United States gross domestic product. There are approximately 94,000 critical care beds in the United States, and provision of critical care services costs approximately $80 billion per year. The enormous costs and the heterogeneity of critical care have led to scrutiny of patient outcomes and cost-effectiveness by a variety of governmental and nongovernmental organizations; furthermore, individual critical care practitioners and their hospitals should evaluate the care delivered. This review discusses scoring systems in medicine, critical care systems, development, validation, performance, and customization of the models, adult intensive care unit (ICU) prognostic models, model use, limitations, prognostic models in trauma care, perioperative scoring systems, assessment of organ failure, severity of illness and organ dysfunction scoring in children, and future directions. Figures show the distribution of predicted risk of death using two different prediction models among a population of patients who ultimately are observed to either live or die, a comparison of  “expected” deaths (based on the expectation that the predicted probability from the model is correct) to observed deaths within each of the 10 deciles of predicted risk, the importance of disease in the risk of death equation,  and the revised Rapaport-Teres graph for ICUs in the Project IMPACT validation set. Tables list three main ICU prognostic models, study characteristics and performance of the fourth-generation prognostic models, variables included in the fourth-generation prognostic models, potential uses of adult ICU prognostic models, variables included in the calculation of the organ failure scores, and sequential organ failure assessment. This review contains 4 highly rendered figures, 6 tables, and 293 references


JAMA ◽  
2020 ◽  
Vol 323 (2) ◽  
pp. 183 ◽  
Author(s):  
David Scheinker ◽  
Andrew Ward ◽  
Andrew Y. Shin ◽  
Grace M. Lee ◽  
Roshni Mathew ◽  
...  

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