To determine the usefulness of adjusting antibiotic use (AU) by prevalence of bacterial isolates as an alternative method for risk adjustment beyond hospital characteristics.

Retrospective, observational, cross-sectional study.

Hospitals in the southeastern United States.

AU in days of therapy per 1,000 patient days and microbiologic data from 2015 and 2016 were collected from 26 hospitals. The prevalences of Pseudomonas aeruginosa, extended-spectrum β-lactamase (ESBL)–producing bacteria, methicillin-resistant Staphylococcus aureus (MRSA), and vancomycin-resistant enterococci (VRE) were calculated and compared to the average prevalence of all hospitals in the network. This proportion was used to calculate the adjusted AU (a-AU) for various categories of antimicrobials. For example, a-AU of antipseudomonal β-lactams (APBL) was the AU of APBL divided by (prevalence of P. aeruginosa at that hospital divided by the average prevalence of P. aeruginosa). Hospitals were categorized by bed size and ranked by AU and a-AU, and the rankings were compared.

Most hospitals in 2015 and 2016, respectively, moved ≥2 positions in the ranking using a-AU of APBL (15 of 24, 63%; 22 of 26, 85%), carbapenems (14 of 23, 61%; 22 of 25; 88%), anti-MRSA agents (13 of 23, 57%; 18 of 26, 69%), and anti-VRE agents (18 of 24, 75%; 15 of 26, 58%). Use of a-AU resulted in a shift in quartile of hospital ranking for 50% of APBL agents, 57% of carbapenems, 35% of anti-MRSA agents, and 75% of anti-VRE agents in 2015 and 50% of APBL agents, 28% of carbapenems, 50% of anti-MRSA agents, and 58% of anti-VRE agents in 2016.

The a-AU considerably changes how hospitals compare among each other within a network. Adjusting AU by microbiological burden allows for a more balanced comparison among hospitals with variable baseline rates of resistant bacteria.

To examine the temporal trends in ambulatory antibiotic prescription fill rates and to determine the influences of age, gender, and location.

Population-based cohort study.

Ambulatory setting in South Carolina.

Patients ≤64 years of age from January 2012 to December 2017.

Aggregated pharmacy claims data for oral antibiotic prescriptions were utilized to estimate community antibiotic prescription rates. Poisson regression or Student t tests were used to examine overall temporal trend in antibiotic prescription rates, seasonal variation, and the trends across age group, gender, and rural versus urban location.

Overall antibiotic prescription rates decrease from 1,127 to 897 per 1,000 person years (P < .001). The decrease was more noticeable in persons aged <18 years (26%) and 18–39 years (20%) than in those aged 40–64 years (5%; P < .001 for all). Prescription rates were higher among females than males in all age groups, although this finding was the most pronounced in group aged 18–39 years (1,232 vs 585 per 1,000 person years; P < .0001). Annualized antibiotic prescription rates were higher during the winter months (December–March) than the rest of the year (1,145 vs 885 per 1,000 person years; P < .0001), and rates were higher in rural areas than in urban areas (1,032 vs 941 per 1,000 person years; P < .0001).

The decline in ambulatory antibiotic prescription rates is encouraging. Ongoing ambulatory antibiotic stewardship efforts across South Carolina should focus on older adults, rural areas, and during the winter season when antibiotic prescriptions peak.