Using a Prediction Tool to Guide Antibiotic Use for Urinary Tract Infection in Women Visiting the Emergency Room

What this Trial Is About

Urinary tract infection UTI occurs when bacteria enter the urinary system causing symptoms like burning during urination, frequent urge to pee, and cloudy or strong-smelling urine. Severe UTIs can lead to fever, abdominal pain, or lower back pain. In emergency departments, diagnosis relies on symptoms, urine analysis, and urine culture. This study aims to reduce unnecessary antibiotic use, which contributes to antibiotic resistance, a growing global health concern. Participants presenting with UTI symptoms at an emergency room will be assessed using a decision aid prediction model. Physicians will input patient data into this model to estimate the likelihood of a positive urine culture. Those with a high likelihood will receive empiric antibiotics based on guidelines, while those with a low likelihood will be discharged without antibiotics. A culture call-back system involving clinical pharmacists will notify patients if their culture results indicate a need to adjust treatment. Participants will be followed for up to two weeks to monitor antibiotic use and healthcare visits. Researchers will review medical records to measure antibiotic-free days, antibiotic prescription rates, hospitalizations, emergency readmissions, and unscheduled primary care visits. They will also evaluate the accuracy of urine analysis compared to cultures and track non-UTI urologic diagnoses. The total participation duration is about two weeks, focusing on prevention and appropriate antibiotic use.

Application of a Prediction Model for Directing Antibiotic Use in the Treatment of Urinary Tract Infection in an Ambulatory Setting