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Objective: To evaluate temporal trends in the prevalence of gram-negative bacteria (GNB) with difficult-to-treat resistance (DTR) in the southeastern United States. Secondary objective was to examine the use of novel β-lactams for GNB with DTR by both antimicrobial use (AU) and a novel metric of adjusted AU by microbiological burden (am-AU)., Design: Retrospective, multicenter, cohort., Setting: Ten hospitals in the southeastern United States., Methods: GNB with DTR including Enterobacterales, Pseudomonas aeruginosa , and Acinetobacter spp. from 2015 to 2020 were tracked at each institution. Cumulative AU of novel β-lactams including ceftolozane/tazobactam, ceftazidime/avibactam, meropenem/vaborbactam, imipenem/cilastatin/relebactam, and cefiderocol in days of therapy (DOT) per 1,000 patient-days was calculated. Linear regression was utilized to examine temporal trends in the prevalence of GNB with DTR and cumulative AU of novel β-lactams., Results: The overall prevalence of GNB with DTR was 0.85% (1,223/143,638) with numerical increase from 0.77% to 1.00% between 2015 and 2020 ( P = .06). There was a statistically significant increase in DTR Enterobacterales (0.11% to 0.28%, P = .023) and DTR Acinetobacter spp. (4.2% to 18.8%, P = .002). Cumulative AU of novel β-lactams was 1.91 ± 1.95 DOT per 1,000 patient-days. When comparing cumulative mean AU and am-AU, there was an increase from 1.91 to 2.36 DOT/1,000 patient-days, with more than half of the hospitals shifting in ranking after adjustment for microbiological burden., Conclusions: The overall prevalence of GNB with DTR and the use of novel β-lactams remain low. However, the uptrend in the use of novel β-lactams after adjusting for microbiological burden suggests a higher utilization relative to the prevalence of GNB with DTR., Competing Interests: Potential conflicts of interest. D.C. reports that he is pending a patent with Genus, group, species, and/or strain-specific 16s rdna sequences. B.J. reports that he is the member of the speaker’s bureau for Abbie, Paratek, Innoviva, and Ferring. M.A. reports that he serves on IDSA Antimicrobial Resistance Committee, International Working Group for Diabetic Foot Infection Guideline Panel, and WHO Antimicrobial Resistance Expert Group on Human Health Research. P.B. reports that she has two ongoing grants (CDC-RFA-CK22-2203 and University of South Carolina Center for Rural and Primary Healthcare). J.A.J. reports that she is on the advisory board for Entasis Therapeutics and Shionogi. Potential conflicts of interest. All other authors report no conflicts of interest relevant to this article., (© The Author(s) 2024.)

Objective: To determine the usefulness of adjusting antibiotic use (AU) by prevalence of bacterial isolates as an alternative method for risk adjustment beyond hospital characteristics., Design: Retrospective, observational, cross-sectional study., Setting: Hospitals in the southeastern United States., Methods: 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., Results: 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., Conclusions: 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.