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1821. Understanding the Components and Calculation of the SAAR, Illustrative Data
BACKGROUND: The standardized antimicrobial administration ratio (SAAR) compares each hospital’s observed to predicted days of antimicrobial therapy. However, confusion exists about how hospital-level, seasonal, and hospital-peer-based variations in antibiotic use might impact an institution’s SAAR....
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6254700/ http://dx.doi.org/10.1093/ofid/ofy210.1477 |
Sumario: | BACKGROUND: The standardized antimicrobial administration ratio (SAAR) compares each hospital’s observed to predicted days of antimicrobial therapy. However, confusion exists about how hospital-level, seasonal, and hospital-peer-based variations in antibiotic use might impact an institution’s SAAR. We characterized the impact of each of these three types of variation on predicted SAARs utilizing local NHSN data. METHODS: Analysis of antibiotic consumption data from an academic medical center in Chicago, IL was conducted. SAAR and antimicrobial days per 1,000 days present (AD/1,000DP) were compiled in monthly increments from 2014 to 2016.Antimicrobial consumption was aggregated and classified into agent categories according to NHSN criteria. Month-to-month changes in both the SAAR and AD/1,000DP were evaluated. Azithromycin AD/1,000DP from 2012 through 2017 were explored for seasonal variation as defined as >20% increase in AD/1,000DP from each quarter to the overall mean AD/1,000DP for all months. A simulation was performed to explore the potential effect of seasonality on the SAAR. Demographic covariates within the SAAR model were altered while holding constant observed antibiotic use; thus we were able to observe the potential impact of demographics. Finally, a simulation explored the effect of altered consumption at other hospitals on a local institution’s SAAR. RESULTS: Across all antibiotic agent categories for both ICU (n = 4) and general wards (n = 4), the average matched-month percent change in AD/1,000DP was highly predicted and correlated with the corresponding change in SAAR (Figure 1, Pearson’s r = 0.99). The monthly mean ± SD AD/1,000DP was 235.0 (range 47.2–661.5), and the mean ± SD SAAR was 1.09 ± 0.26 (range 0.79–1.09) across the NHSN antibiotic agent categories. Five quarters were found to have seasonal variation in AD/1000DP for azithromycin (Figure 2). Simulations demonstrated that changing antimicrobial usage at comparator hospitals does not impact the local SAAR, and seasonal variation may cause fluctuating SAARs. CONCLUSION: Month-to-month changes in the SAAR mirror monthly changes in an institution’s AD/1,000DP. Seasonal variation can impact the SAAR, and the effect changing peer hospital antibiotic consumption is not currently captured by the SAAR methodology. [Image: see text] [Image: see text] DISCLOSURES: J. Liu, Merck: Grant fund from Merck, Research grant. D. Martin, Syneos Health: Employee, Salary. GlaxoSmithKline: Independent Contractor, Salary. M. H. Scheetz, Merck & Co., Inc.: Grant Investigator, Grant recipient. Bayer: Consultant, Consulting fee. |
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