1348. Indirect Standardization to Improve Comparison of Children’s Hospitals’ Antimicrobial Use

Abstract

BackgroundAntimicrobial use (AU) measured by days of therapy per 1000 patient-days (DOT/1000pd), the most established metric, varies widely between children’s hospitals despite robust adoption of antimicrobial stewardship. Differences in diagnoses and procedures (case mix) between hospitals are a source of AU variation not included in adjustment methods such as the Standardized Antimicrobial Administration Ratio. In this study, we evaluated an indirect standardization method to adjust children’s hospital AU for case mix.MethodsThis multicenter retrospective cohort study included 51 children’s hospitals participating in the Pediatric Health Information System database from 2016-2018. All inpatient, observation, and neonatal admissions were included, with a total of 2,558,948 discharges. Hospitalizations were grouped into 83 strata defined based on All Patients Refined Diagnosis Related Groups (APR-DRGs). Observed to expected (O:E) ratios were calculated by indirect standardization of mean antibiotic DOT per case, with expected values from 2016-2018 and observed values from 2018, and compared to DOT/1000pd. Outlier hospitals were defined by O:E z-scores corresponding to below 10th percentile (low outlier) and above 90th percentile (high outlier).ResultsAntibacterial DOT/1000pd ranged from 345 to 776 (2.2-fold variation from lowest to highest), whereas O:E ratios ranged from 0.8 to 1.14 (1.4-fold variation from lowest to highest) (Figure 1). O:E ratios were moderately correlated with DOT/1000pd (correlation estimate 0.45; 95% CI 0.19-0.64; p=0.0008). Three high outlier hospitals and 6 low outlier hospitals were identified. Examining hospitals with comparably high DOT/1000pd but discordant O:E ratios, differences could be explained by variation in both case mix and condition-specific AU within strata defined by APR-DRGs.Figure 1. Individual hospitals labeled on the X-axis, ordered by level of antibacterial DOT/1000pd (left axis), represented by bars. Diamonds represent O:E ratios derived by indirect standardization (right axis). Outlier hospitals (low and high) are highlighted in yellow. Dashed horizontal lines represent 10th percentile (lower) and 90th percentile (upper) limits of the O:E ratio distribution. ConclusionThe observed variation in DOT/1000pd between hospitals is reduced when indirect standardization is applied to account for case mix differences. This approach can be adapted for more specific uses including clinical conditions, patient populations, or antimicrobial agents. Indirect standardization may enhance stewardship efforts by providing adjusted comparisons that incorporate case mix differences between hospitals.Disclosures All Authors: No reported disclosures