Feasibility of Licensed Vocational Nurses Using a CDS App to Communicate Signs and Symptoms of a UTI.

Abstract

Urinary tract infections (UTIs) occurring in nursing home (NH) residents are poorly assessed and challenging to treat. The emergence of clinical decision support (CDS) technology provides an opportunity for improved diagnosis and treatment of UTIs in the NH. The purpose of this study was to report findings examining the feasibility of licensed vocational nurses (LVNs) using a CDS algorithm designed to directly guide assessment of a standardized NH resident experiencing symptoms of a potential UTI in a simulation setting at a university in the Southern United States. A structured observational design was used. A sample of ten practicing nurses used an algorithm developed by the authors from published UTI assessment and practice-driven criteria. Data collection was framed using (a) UTI-guided assessment tool, (b) analysis of LVN behavior and verbal interaction with the algorithm, and (c) postsimulation interviews about the algorithm and nurse-resident interactions. Results showed LVNs found the algorithm easy or very easy to use, their behaviors demonstrated high levels of engagement with the simulation while using the algorithm, and interviews supported the positive value LVNs placed on using an algorithmic approach for UTI assessment. The algorithm we developed fills a gap in the current approaches to diagnosing a UTI in the NH by focusing on the role of the LVN in data collection in relation to assessment of the resident.