Early prediction of central line associated bloodstream infection using machine learning

Central line-associated bloodstream infections (CLABSIs) are associated with significant morbidity, mortality, and increased healthcare costs. Despite the high prevalence of CLABSIs in the U.S., there are currently no tools to stratify a patient ' s risk of developing an infection as the result of central line placement. To this end, we have developed and validated a machine learning algorithm (MLA) that can predict a patient ' s likelihood of developing CLABSI using only electronic health record data in order to provide clinical decision support.
Source: Current Awareness Service for Health (CASH) - Category: Consumer Health News Source Type: news