Abstract
Infusion pumps are medical devices that deliver medication, fluids, and nutrients in a precise and controlled manner that is critical to patient care. This study proposes using infusion pump informatics on all-infusion datasets to understand current impact of alerts and alarms on patient care and health practitioner workflow. All-infusion datasets contain infusion data for both normal and abnormal use, i.e., error states. Ten months of continuous data was collected from one health institution. Analysis of variance with log-transformation and logistic regressions were used to analysis contributing factors for alerts and alarms states. A total 64,511 minutes of alarm activation were observed, where alarms were active prior to being resolved. Mean resolution times for 83% of alarms were one minute or less; however, 3% or alarms required >4 minutes before getting resolved. Risk factors for infusions with alerts included nursing shift variables. Specifically, odds for alerts were 1.3 times higher for infusions that span across shifts than infusions in the day shift.