Importance Patient-related factors contribute to unnecessary antibiotics for urinary tract infections (UTI). Objective The objective of this study was to determine the effectiveness of an algorithm-based texting platform for reducing the rate of unnecessary antibiotics in women with recurrent UTI. Study Design Adult women with recurrent UTI were randomized in a 1:1 ratio to a texting platform or usual care at an urban academic center (March 2024 to March 2025). Participants in the texting group received access to an automated bidirectional evidence-based platform for symptom triage, shared decision making, and educational videos. Participants in the usual care group received treatment of UTI from their usual clinicians. The primary outcome was the rate of unnecessary antibiotics at 3 months from randomization. Results Women with recurrent UTI were randomized to the texting platform (n=51) or usual care (n=51). The mean number of UTI episodes was significantly lower in the texting group than in the usual care group (0.47±0.92 vs. 0.82±1.10, P =0.041). The overall rate of unnecessary antibiotics (11.8%, 95% CI, 4.4–23.9 vs. 29.4%, 95% CI, 17.5–43.8, P =0.028) and rate of unnecessary antibiotics for asymptomatic bacteriuria (2.0%, 95% CI, 0–10.4 vs. 19.6%, 95% CI, 9.8–33.1, P =0.004) were lower in the texting group than in the usual care group. In-person visits and nonbillable messages for UTI were lower in the texting group. Quality-of-life scores did not differ between groups. Conclusion An automated algorithmic texting platform reduced the number of UTI episodes, unnecessary antibiotic prescriptions, and health care utilization in women with recurrent UTI.
Agrawal et al. (Mon,) studied this question.