A Pilot Study Evaluating the Impact of an Algorithm-Driven Protocol on Guideline-Concordant Antibiotic Prescribing in a Rural Primary Care Setting

Antimicrobial resistance (AMR) causes 2.8 million infections and over 35,000 deaths annually in the U.S., driven largely by inappropriate antibiotic prescribing, especially in rural and underserved clinics. Antibiotic Stewardship Programs (ASPs) improve prescribing practices, but many rural clinics lack fully functional ASPs. This pilot study evaluated the impact of an algorithm-driven protocol on antibiotic prescribing in a rural primary care setting. We conducted a 3.5-month, quasi-experimental study at a Federally Qualified Health Center (FQHC), focusing on upper respiratory infections, urinary tract infections, and sexually transmitted infections. Eligible patients were identified by a pharmacy resident. The primary outcome was the frequency of guideline-concordant treatment, analyzed using descriptive statistics and Chi-square tests. Among 201 patients (101 pre-intervention, 100 post-intervention), the pre-intervention group had 77% females and 47% African Americans, while the post-intervention group had 72% females and 46% African Americans. The intervention was associated with a 12.6% decrease in inappropriate antibiotic prescriptions (37.6% to 25%) from pre- to post-intervention periods. This corresponded to an odds ratio (OR) of 0.55 (95% CI: 0.30–1.01, p=0.054). Although not statistically significant at α=0.05, the trend suggests potential benefits of algorithm-driven protocols in improving antibiotic stewardship in resource-limited settings. Longer study periods may further elucidate these benefits.