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Updated: Jan 26, 2026

A Protocol to Set Up Needle-Free Connector with Positive Displacement on Central Venous Catheter in Intensive Care Unit
Published on: July 13, 2019
Analysis of central venous catheter utilization at a quaternary care hospital
Graham Aufricht1, Joseph Hoang1, Jose Iglesias1
1College of Medicine, Texas A&M UniversityDallasTexas.
Abstract:
Central line-associated bloodstream infections (CLABSIs) are one of the most dangerous and costly types of hospital-acquired infections. Incidence of CLABSI can be significantly reduced through proper aseptic techniques, surveillance, and active management strategies, including elimination of idle central line days. This quality improvement project examined two central venous catheter (CVC) cohorts. The institutional electronic health record (EHR) was utilized to generate a daily report indicating CVC utilization by patient care unit. The EHR was further scrutinized for documentation of appropriate indications for CVC use employing an appropriateness tool developed by the institutional vascular access team. Cohort 1 included 12 National Healthcare Safety Network-reportable units audited on a daily basis over a 4-week time period; cohort 2 included selected National Healthcare Safety Network-nonreportable units audited on a daily basis over a 2-week time period. Central venous catheters that did not meet defined indications as outlined by the institutional vascular access team's data collection checklist were escalated the same day to the unit clinical nurse manager for review and possible removal. The percentage of clinically nonindicated CVCs in cohort 1 fell by 65% over the 4-week period of daily audit and real-time feedback, with similar results noted for cohort 2. In conclusion, real-time audit and feedback regarding appropriate clinical indications for CVC use can result in decreased idle or nonindicated central line days, potentially contributing to decreased CLABSI rates.
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The mean is one such measure, calculated by totaling all values in a dataset and dividing by the number of values. For instance, the mean blood pressure reading (120, 130, 140, 150) would be 135. However, the mean can be affected by extreme values or outliers.
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