Two comprehensive studies have demonstrated the effectiveness of algorithm-driven alerts in optimizing antibiotic selection for hospitalized patients with pneumonia or urinary tract infections (UTIs). The findings, published in the Journal of the American Medical Association (JAMA), suggest a potential solution to reducing antibiotic resistance.
The INSPIRE Pneumonia and UTI Trials, led by Harvard Pilgrim Health Care Institute, HCA Healthcare, and the University of California, Irvine, involved over 220,000 patients at 59 HCA Healthcare hospitals. Half of these hospitals implemented computerized alerts that provided clinicians with real-time information on the optimal antibiotic choice for each patient.
The alerts were based on patient characteristics and hospital-specific data that assessed the risk of antibiotic-resistant infection. Physicians treating patients with a low risk were guided towards standard-spectrum antibiotics, which preserve beneficial bacteria and minimize the development of resistance.
The results showed a significant improvement in antibiotic selection: 28% of pneumonia patients and 17% of UTI patients received a better antibiotic match in hospitals with alerts compared to those without. This precise targeting of antibiotics reduces the overuse of broad-spectrum antibiotics, which can contribute to resistance.
Dr. Sujan Reddy, a Medical Officer at the CDC, emphasizes the value of these alerts in promoting best practices. “Pneumonia and UTIs are common hospital infections and a major driver of antibiotic misuse. The INSPIRE trials provide a practical strategy for physicians to optimize antibiotic selection for each patient,” he says.
The study findings highlight the potential of data-driven tools to improve healthcare outcomes. By providing clinicians with real-time guidance on antibiotic selection, algorithm-driven alerts can contribute to more appropriate use of antibiotics, reduce resistance, and improve patient care.
Jon Napitupulu is Director of Media Relations at The Clinical Trial Vanguard. Jon, a computer data scientist, focuses on the latest clinical trial industry news and trends.
