A Novel Risk-Adjusted Metric to Compare Hospitals on Their Antibiotic Prescribing at Hospital Discharge

Abstract

Background: Antibiotic overuse at hospital discharge is common, but there is no metric to evaluate hospital performance at this transition of care. We built a risk-adjusted metric for comparing hospitals on their overall post-discharge antibiotic use.

Methods: This was a retrospective study across all acute-care admissions within the Veterans Health Administration during 2018-2021. For patients discharged to home, we collected data on antibiotics and relevant covariates. We built a zero-inflated, negative, binomial mixed model with 2 random intercepts for each hospital to predict post-discharge antibiotic exposure and length of therapy (LOT). Data were split into training and testing sets to evaluate model performance using absolute error. Hospital performance was determined by the predicted random intercepts.

Results: 1 804 300 patient-admissions across 129 hospitals were included. Antibiotics were prescribed to 41.5% while hospitalized and 19.5% at discharge. Median LOT among those prescribed post-discharge antibiotics was 7 (IQR, 4-10) days. The predictive model detected post-discharge antibiotic use with fidelity, including accurate identification of any exposure (area under the precision-recall curve = 0.97) and reliable prediction of post-discharge LOT (mean absolute error = 1.48). Based on this model, 39 (30.2%) hospitals prescribed antibiotics less often than expected at discharge and used shorter LOT than expected. Twenty-eight (21.7%) hospitals prescribed antibiotics more often at discharge and used longer LOT.

Conclusions: A model using electronically available data was able to predict antibiotic use prescribed at hospital discharge and showed that some hospitals were more successful in reducing antibiotic overuse at this transition of care. This metric may help hospitals identify opportunities for improved antibiotic stewardship at discharge.

Keywords: antibiotic stewardship; community-acquired; hospital discharge; metrics; pneumonia; risk-adjustment.

Figure 1.

Flowchart for how the study cohort was constructed. Abbreviation: VA, Veterans Affairs.

Figure 2.

A, Caterpillar plot of the conditional odds ratio for any antibiotic prescribing at discharge for 129 hospitals. The points on the horizontal axis represent the conditional odds ratio at each hospital for any antibiotic prescribing at discharge compared with a hospital with the expected frequency of antibiotic prescribing at discharge. The error bars represent a 95% confidence interval (CI) around that predicted value for each hospital. Hospitals with CIs that are entirely above or below 1 can be interpreted as having significantly more frequent or less frequent antibiotic prescribing, respectively, holding all fixed effects equal. B, Caterpillar plot of the rate ratio for post-discharge length of antibiotic therapy at 129 hospitals. The points on the horizontal axis represent the relative percentage difference in post-discharge antibiotic length of therapy (LOT) between each hospital and a hospital that prescribes the expected post-discharge LOT. The error bars represent the 95% CI around that predicted value for each hospital. Hospitals with CIs that are entirely above or below zero can be interpreted as having significantly longer or shorter LOT, respectively, holding all fixed effects equal.

Figure 3.

Risk-adjusted comparison of post-discharge antibiotic-prescribing frequency and duration across 129 hospitals. Group 1 hospitals had less frequent post-discharge antibiotic prescribing and used shorter post-discharge antibiotic duration. Group 2 hospitals had more frequent post-discharge antibiotic prescribing and used shorter post-discharge antibiotic durations. Group 3 had less frequent post-discharge antibiotic prescribing and used longer post-discharge antibiotic durations. Group 4 hospitals had more frequent post-discharge antibiotic prescribing and used longer post-discharge antibiotic durations.