A new study using Independence Blue Cross (IBX) claims data published in JAMA Network Open found that 2011 national guidelines for treating uncomplicated urinary tract infections (UTI) are still optimal. IBX Director of Data Science and Health Care Aaron Smith-McLallen co-authored the research study, which included researchers from MIT and Harvard.
Using a novel machine learning approach to evaluate the efficacy of first, second, and third-line antibiotic treatments for UTIs, the study found strong support for existing treatment guidelines. It also demonstrates how large healthcare datasets, when combined with machine learning techniques, can be used to assess treatment effectiveness, and potentially improve care for a variety of conditions.
The study looked at nearly 60,000 episodes of UTI among more than 49,000 women with an average age of nearly 52. Up to half of women will experience a UTI in their lifetime, making it the third most common indication for antibiotic treatment in the United States after respiratory tract infection and skin and soft-tissue infections.
