A decision algorithm to promote outpatient antimicrobial stewardship for uncomplicated urinary tract infection
Antibiotic resistance is a major cause of treatment failure and leads to increased use of broad-spectrum agents, which begets further resistance. This vicious cycle is epitomized by uncomplicated urinary tract infection (UTI), which affects one in two women during their life and is associated with increasing antibiotic resistance and high rates of prescription for broad-spectrum second-line agents. To address this, we developed machine learning models to predict antibiotic susceptibility using electronic health record data and built a decision algorithm for recommending the narrowest possible antibiotic to which a specimen is susceptible.
Global Ambassador Network
Welcome at the AMR Insights Ambassador Network!
The AMR Insights Ambassador Network is a growing, distinctive group of professionals who stand out for their commitment, willingness to cooperate and open attitude to combat Antimicrobial resistance (AMR).