Establishing Benchmarks for Antimicrobial Use in Canadian Children’s Hospitals

Abstract Background Antimicrobial 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. Methods This 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). Results Antibacterial 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. Conclusion The 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

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Identifying Targets for Antimicrobial Stewardship in Children's Hospitals

Infection Control and Hospital Epidemiology ◽

10.1086/673982 ◽

2013 ◽

Vol 34 (12) ◽

pp. 1252-1258 ◽

Cited By ~ 58

Author(s):

Jeffrey S. Gerber ◽

Matthew P. Kronman ◽

Rachael K. Ross ◽

Adam L. Hersh ◽

Jason G. Newland ◽

...

Keyword(s):

Antibiotic Therapy ◽

Antimicrobial Stewardship ◽

Severity Of Illness ◽

Antibiotic Use ◽

The United States ◽

High Impact ◽

Antimicrobial Use ◽

Children's Hospitals ◽

Children’S Hospitals ◽

Days Of Therapy

Objective.Antimicrobial stewardship programs (ASPs) are recommended to optimize antimicrobial use for hospitalized patients. Although mechanisms for the implementation of ASPs have been described, data-driven approaches to prioritize specific conditions and antimicrobials for intervention have not been established. We aimed to develop a strategy for identifying high-impact targets for antimicrobial stewardship efforts.Design.Retrospective cross-sectional study.Setting and Patients.Children admitted to 32 freestanding children's hospitals in the United States in 2010.Methods.We identified the conditions with the largest proportional contribution to the total days of antibiotic therapy prescribed to all hospitalized children. For the 4 highest-using conditions, we examined variability between hospitals in antibiotic selection patterns for use of either first- or second-line therapies depending on the condition. Antibiotic use was determined using standardized probability of exposure to selected agents and standardized days of therapy per 1,000 patient-days, adjusting for patient demographics and severity of illness.Results.In 2010, 524,364 children received 2,082,929 days of antibiotic therapy. Surgical patients received 43% of all antibiotics. The 4 highest-using conditions—pneumonia, appendicitis, cystic fibrosis, and skin and soft-tissue infection—represent 1% of all conditions yet accounted for more than 10% of all antibiotic use. Wide variability in antibiotic use occurred for 3 of these 4 conditions.Conclusions.Antibiotic use in children's hospitals varied broadly across institutions when examining diagnoses individually and adjusting for severity of illness. Identifying conditions with both frequent and variable antimicrobial use informs the prioritization of high-impact targets for future antimicrobial stewardship interventions.

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Indirect Standardization as a Case Mix Adjustment Method to Improve Comparison of Children’s Hospitals’ Antimicrobial Use

Clinical Infectious Diseases ◽

10.1093/cid/ciaa1854 ◽

2020 ◽

Author(s):

Rachel L Wattier ◽

Cary W Thurm ◽

Sarah K Parker ◽

Ritu Banerjee ◽

Adam L Hersh ◽

...

Keyword(s):

Health Information System ◽

Case Mix ◽

Antimicrobial Use ◽

Children's Hospitals ◽

Children’S Hospitals ◽

Days Of Therapy ◽

Z Scores ◽

Case Mix Adjustment ◽

Indirect Standardization ◽

Correlation Estimate

Abstract Antimicrobial use (AU) in days of therapy per 1000 patient-days (DOT/1000pd) varies widely among children’s hospitals. We evaluated indirect standardization to adjust AU for case mix, a source of variation inadequately addressed by current measurements. Hospitalizations from the Pediatric Health Information System were grouped into 85 clinical strata. Observed to expected (O:E) ratios were calculated by indirect standardization and compared to DOT/1000pd. Outliers were defined by O:E z-scores. Antibacterial DOT/1000pd ranged from 345 to 776 (2.2-fold variation; interquartile range [IQR] 552-679), whereas O:E ratios ranged from 0.8 to 1.14 (1.4-fold variation; IQR 0.93-1.05). O:E ratios were moderately correlated with DOT/1000pd (correlation estimate 0.44; 95% CI 0.19-0.64; p=0.0009). Using indirect standardization to adjust for case mix reduces apparent AU variation and may enhance stewardship efforts by providing adjusted comparisons to inform interventions.

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