Understanding the role of antibiotic-associated adverse events in influencing antibiotic decision-making.

Objective: To (1) understand the role of antibiotic-associated adverse events (ABX-AEs) on antibiotic decision-making, (2) understand clinician preferences for ABX-AE feedback, and (3) identify ABX-AEs of greatest clinical concern. Design: Focus groups. Setting: Academic medical center. Participants: Medical and surgical house staff, attending physicians, and advanced practice practitioners. Methods: Focus groups were conducted from May 2022 to December 2022. Participants discussed the role of ABX-AEs in antibiotic decision-making and feedback preferences and evaluated the prespecified categorization of ABX-AEs based on degree of clinical concern. Thematic analysis was conducted using inductive coding. Results: Four focus groups were conducted (n = 15). Six themes were identified. (1) ABX-AE risks during initial prescribing influence the antibiotic prescribed rather than the decision of whether to prescribe. (2) The occurrence of an ABX-AE leads to reassessment of the clinical indication for antibiotic therapy. (3) The impact of an ABX-AE on other management decisions is as important as the direct harm of the ABX-AE. (4) ABX-AEs may be overlooked because of limited feedback regarding the occurrence of ABX-AEs. (5) Clinicians are receptive to feedback regarding ABX-AEs but are concerned about it being punitive. (6) Feedback must be curated to prevent clinicians from being overwhelmed with data. Clinicians generally agreed with the prespecified categorizations of ABX-AEs by degree of clinical concern. Conclusions: The themes identified and assessment of ABX-AEs of greatest clinical concern may inform antibiotic stewardship initiatives that incorporate reporting of ABX-AEs as a strategy to reduce unnecessary antibiotic use.

An Electronic Algorithm to Identify Vancomycin-Associated Acute Kidney Injury.

Background: The burden of vancomycin-associated acute kidney injury (V-AKI) is unclear because it is not systematically monitored. The objective of this study was to develop and validate an electronic algorithm to identify cases of V-AKI and to determine its incidence. Methods: Adults and children admitted to 1 of 5 health system hospitals from January 2018 to December 2019 who received at least 1 dose of intravenous (IV) vancomycin were included. A subset of charts was reviewed using a V-AKI assessment framework to classify cases as unlikely, possible, or probable events. Based on review, an electronic algorithm was developed and then validated using another subset of charts. Percentage agreement and kappa coefficients were calculated. Sensitivity and specificity were determined at various cutoffs, using chart review as the reference standard. For courses ≥48 hours, the incidence of possible or probable V-AKI events was assessed. Results: The algorithm was developed using 494 cases and validated using 200 cases. The percentage agreement between the electronic algorithm and chart review was 92.5% and the weighted kappa was 0.95. The electronic algorithm was 89.7% sensitive and 98.2% specific in detecting possible or probable V-AKI events. For the 11 073 courses of ≥48 hours of vancomycin among 8963 patients, the incidence of possible or probable V-AKI events was 14.0%; the V-AKI incidence rate was 22.8 per 1000 days of IV vancomycin therapy. Conclusions: An electronic algorithm demonstrated substantial agreement with chart review and had excellent sensitivity and specificity in detecting possible or probable V-AKI events. The electronic algorithm may be useful for informing future interventions to reduce V-AKI.

Risk-factor analysis for extended-spectrum beta-lactamase-producing Enterobacterales colonization or infection: Evaluation of a novel approach to assess local prevalence as a risk factor.

OBJECTIVE: To explore an approach to identify the risk of local prevalence of extended-spectrum ß-lactamase-producing Enterobacterales (ESBL-E) on ESBL-E colonization or infection and to reassess known risk factors. DESIGN: Case-control study. SETTING: Johns Hopkins Health System emergency departments (EDs) in the Baltimore-Washington, DC, region. PATIENTS: Patients aged ≥18 years with a culture growing Enterobacterales between April 2019 and December 2021. Cases had a culture growing an ESBL-E. METHODS: Addresses were linked to Census Block Groups and placed into communities using a clustering algorithm. Prevalence in each community was estimated using the proportion of ESBL-E among Enterobacterales isolates. Logistic regression was used to determine risk factors for ESBL-E colonization or infection. RESULTS: ESBL-E were detected in 1,167 of 11,224 patients (10.4%). Risk factors included a history of ESBL-E in the prior 6 months (aOR, 20.67; 95% CI, 13.71-31.18), exposure to a skilled nursing or long-term care facility (aOR, 1.64; 95% CI, 1.37-1.96), exposure to a third-generation cephalosporin (aOR, 1.79; 95% CI, 1.46-2.19), exposure to a carbapenem (aOR, 2.31; 95% CI, 1.68-3.18), or exposure to a trimethoprim-sulfamethoxazole (aOR, 1.54; 95% CI, 1.06-2.25) within the prior 6 months. Patients were at lower risk if their community had a prevalence <25th percentile in the prior 3 months (aOR, 0.83; 95% CI, 0.71-0.98), 6 months (aOR, 0.83; 95% CI, 0.71-0.98), or 12 months (aOR, 0.81; 95% CI, 0.68-0.95). There was no association between being in a community in the >75th percentile and the outcome. CONCLUSIONS: This method of defining the local prevalence of ESBL-E may partially capture differences in the likelihood of a patient having an ESBL-E.