Ashleigh J. Goris

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OBJECTIVE To develop and evaluate computer algorithms with high negative predictive values that augment traditional surveillance for central line-associated bloodstream infection (CLABSI). SETTING Barnes-Jewish Hospital, a 1,250-bed tertiary care academic hospital in Saint Louis, Missouri. METHODS We evaluated all adult patients in intensive care units(More)
BACKGROUND Manual surveillance for central line-associated bloodstream infections (CLABSIs) by infection prevention practitioners is time-consuming and often limited to intensive care units (ICUs). An automated surveillance system using existing databases with patient-level variables and microbiology data was investigated. METHODS Patients with a positive(More)
Background: More than 18 million healthcare workers (HCW) in the United States work in hospitals and other healthcare settings. Precise national data are not available on the annual number of needlestick injuries (NSI) among HCW; however, recent estimates indicate that over 440,000 NSI occur annually. Active safety engineered devices (ASED) are the most(More)
OBJECTIVE To increase reliability of the algorithm used in our fully automated electronic surveillance system by adding rules to better identify bloodstream infections secondary to other hospital-acquired infections. METHODS Intensive care unit (ICU) patients with positive blood cultures were reviewed. Central line-associated bloodstream infection(More)
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