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Novel antibiotic stewardship metrics and the quality of antibiotic prescribing for lower respiratory and urinary tract infection across 24 VA hospitals.

Oct 2026 · Infection control and hospital epidemiology · pp. 1-7 · 0 citations · 25 references
Medicine

Abstract

INTRODUCTION Some inpatient antibiotic use metrics have important limitations, including the absence of patient-level risk adjustment. To address this limitation, we previously developed two risk-standardized ratios (RSRs), one based on days of therapy (RSR-DOT) and the other on days of antibiotic spectrum coverage (RSR-DASC). Here, we evaluated the construct validity of these metrics by examining whether hospital performance was associated with the quality of antibiotic selection and duration in patients with either lower respiratory tract infections (LRIs) or urinary tract infections (UTIs).

Methods

Using Veterans Health Administration data from October 2020 through September 2021, we calculated RSR-DOT and RSR-DASC for 121 acute-care hospitals and selected 24 hospitals with relatively low or high values. At each hospital, a blinded infectious diseases physician reviewed 10 admissions each for LRI and UTI. Antibiotic selection at day 3 and total antibiotic duration were adjudicated and summarized as a 6-category ordinal composite outcome. Associations between RSR metrics and antibiotic-prescribing quality were evaluated using ordinal logistic regression; model-fit and bootstrap analyses compared RSR-DOT and RSR-DASC.

Results

We reviewed 479 admissions (239 LRI and 240 UTI). In LRI, lower RSR-DASC tended to be associated with a higher quality of antibiotic use (coefficient, 2.906 [P = .053]), whereas RSR-DOT was not (1.418 [P = .374]). In UTI, neither metric was associated with the quality of antibiotic therapy. Model-fit and bootstrap analyses consistently favor RSR-DASC over RSR-DOT for LRI.

Conclusions

RSR-DASC may capture antibiotic-prescribing quality more closely than RSR-DOT for LRI, but not for UTI, potentially supporting the value of spectrum-informed benchmarking metrics.

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