US outpatient antibiotic prescribing variation according to geography, patient population, and provider specialty in 2011

Abstract

Background: Appropriate antibiotic prescribing is an essential strategy to reduce the spread of antibiotic resistance. US prescribing practices have not been thoroughly characterized. We analyzed outpatient antibiotic prescribing data to identify where appropriate antibiotic prescribing interventions could have the most impact.

Methods: Oral antibiotic prescriptions dispensed during 2011 were extracted from the IMS Health Xponent database. The number of prescriptions and census denominators were used to calculate prescribing rates. Prescription totals were calculated for each provider specialty. Regression modeling was used to examine the association between socioeconomic and population health factors and prescribing rates.

Results: Healthcare providers prescribed 262.5 million courses of antibiotics in 2011(842 prescriptions per 1000 persons). Penicillins and macrolides were the most common antibiotic categories prescribed. The most commonly prescribed individual antibiotic agent was azithromycin. Family practitioners prescribed the most antibiotic courses (24%). The prescribing rate was higher in the South census region (931 prescriptions per 1000 persons) than in the West (647 prescriptions per 1000 persons; P < .001); this pattern was observed among all age groups, including children ≤ 2 and persons ≥ 65 years of age. Counties with a high proportion of obese persons, infants and children ≤ 2 years of age, prescribers per capita, and females were more likely to be high prescribing by multivariable analysis (adjusted odds ratio, >1.0).

Conclusions: Efforts to characterize antibiotic prescribing practices should focus on the South census region and family practitioners. Further understanding of the factors leading to high prescribing among key target populations will inform appropriate prescribing interventions.

Keywords: anti-bacterial agents; antibiotic; inappropriate prescribing.