1302-B - Utilizing Predictive Analytics to Decrease Catheter Associated Infections

Session Description: Implementation of device bundles and protocols has successfully decreased the incidence of healthcare-associated infections (HAI) in the past. The National Healthcare Safety Network data indicates the incidence of these infections has increased over the last two years compared to prepandemic periods. A multidisciplinary team comprising of infection preventionists, data scientists, nursing quality specialists, clinical educators, nursing informatics, and bedside nurses created and implemented a catheter associated urinary tract infection (CAUTI) risk score decision support tool to identify the specific risk factors and level of risk which can augment existing prevention protocols and strategies to decrease catheter associated infections.

During this presentation we will discuss the retrospective analysis derived from patients who had catheters placed, the risk factors found to have the most significant association with CAUTI diagnosis, the level of risk on a rolling timeframe of catheter device days and the diagnosis of a CAUTI with the outcome tied into the day the lab resulted. This predictive model was then incorporated into the electronic medical record to inform the healthcare providers with a daily level of risk. We will also demonstrate how we incorporated the risk score into our professional practices to decrease the incidence of infections.

The target audience is any infection preventionist working in a facility that has indwelling urinary catheters.