A novel measure for characterizing ultrasound device use and wear

Point-of-care ultrasound (POCUS) equipment management is critical in optimizing daily clinical operations in emergency departments (EDs). Traditional consultative ultrasound laboratories are well practiced at operations management, but this is not the case for POCUS programs, because machine upgrade and replacement metrics have not been developed or tested. We present a data-driven method for assessment of POCUS equipment maintenance and replacement named the ULTrA (a data-driven approach to point-of-care ultrasound upgrade) score. This novel model of assessing each ultrasound machine by quantitative scoring in each of four mostly objective categories: use (U), likeability (L), trustworthiness (Tr), and age (A). We propose the ULTrA model as a method to identify underperforming devices which could be upgraded or eliminated, and to compare relative performance amongst a group of departmental ultrasound machines. This composite score may be a useful objective tool that could replace individual proxies for clinical effectiveness, such as age, use, or individual provider preference. Additional research in multiple centers would be needed to refine and validate the ULTrA score. Once fully developed, the ULTrA score could be deployed in EDs and other clinical settings where POCUS is used to help streamline resources to maintain a functional and state-of-the-art fleet of ultrasound machines over time.