Using a large, geographically diverse, hospital-based database in the United States (Premier PINC AI Healthcare Database), we aimed to describe the proportion and characteristics of patients receiving phenotype-desirable antimicrobial therapy (PDAT) among those hospitalized with Enterobacterales bloodstream infections.

Adult patients with an admission between January 1, 2017 and June 30, 2022 with ≥1 blood culture positive for Escherichia coli, Klebsiella oxytoca, Klebsiella pneumoniae, or Proteus mirabilis and receiving an empiric antibiotic therapy on blood culture collection (BCC) Days 0 or 1 were included. Receiving PDAT (defined as receipt of any antimicrobial categorized as “desirable” for the respective phenotype) on BCC Days 0−2 was defined as receiving early PDAT.

Among 35,880 eligible patients, the proportion of patients receiving PDAT increased (from 6.8% to 22.8%) from BCC Day 0−4. Patients who received PDAT (8,193, 22.8%) were more likely to visit large (500 + beds, 36% vs 31%), teaching (45% vs 39%), and urban (85% vs 82%) hospitals in the Northeast (22% vs 13%) compared to patients not receiving PDAT (all P <. 01). Among patients receiving PDAT, 61.4% (n = 5,033) received it early; they had a lower mean comorbidity score (3.2 vs 3.6), were less likely to have severe or extreme severity of illness (71% vs 79%), and were less likely to have a pathogen susceptible to narrow-spectrum β-lactams (31% vs 71%) compared to patients in the delayed PDAT group (all P < .01).

The proportion of patients receiving desirable therapy increased between BCC Day 0 and 4. Receipts of PDAT and early PDAT were associated with hospital, clinical, and pathogen characteristics.

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.