TY - JOUR
T1 - Development of the Korean Standardized Antimicrobial Administration Ratio as a Tool for Benchmarking Antimicrobial Use in Each Hospital
AU - Kim, Bongyoung
AU - Ahn, Song Vogue
AU - Kim, Dong Sook
AU - Chae, Jungmi
AU - Jeong, Su Jin
AU - Uh, Young
AU - Kim, Hong Bin
AU - Kim, Hyung Sook
AU - Park, Sun Hee
AU - Park, Yoon Soo
AU - Choi, Jun Yong
N1 - Funding Information:
This study was supported by the Research Program funded by the Korea Disease Control and Prevention Agency (2019-ER5408-00).
Publisher Copyright:
© 2022. The Korean Academy of Medical Sciences
PY - 2022
Y1 - 2022
N2 - Background: The Korea National Antimicrobial Use Analysis System (KONAS), a benchmarking system for antimicrobial use in hospitals, provides Korean Standardized Antimicrobial Administration Ratio (K-SAAR) for benchmarking. This article describes K-SAAR predictive models to enhance the understanding of K-SAAR, an important benchmarking strategy for antimicrobial usage in KONAS. Methods: We obtained medical insurance claims data for all hospitalized patients aged ≥ 28 days in all secondary and tertiary care hospitals in South Korea (n = 347) from January 2019 to December 2019 from the Health Insurance Review & Assessment Service. Modeling was performed to derive a prediction value for antimicrobial use in each institution, which corresponded to the denominator value for calculating K-SAAR. The prediction values of antimicrobial use were modeled separately for each category, for all inpatients and adult patients (aged ≥ 15 years), using stepwise negative binomial regression. Results: The final models for each antimicrobial category were adjusted for different significant risk factors. In the K-SAAR models of all aged patients as well as adult patients, most antimicrobial categories included the number of hospital beds and the number of operations as significant factors, while some antimicrobial categories included mean age for inpatients, hospital type, and the number of patients transferred from other hospitals as significant factors. Conclusion: We developed a model to predict antimicrobial use rates in Korean hospitals, and the model was used as the denominator of the K-SAAR.
AB - Background: The Korea National Antimicrobial Use Analysis System (KONAS), a benchmarking system for antimicrobial use in hospitals, provides Korean Standardized Antimicrobial Administration Ratio (K-SAAR) for benchmarking. This article describes K-SAAR predictive models to enhance the understanding of K-SAAR, an important benchmarking strategy for antimicrobial usage in KONAS. Methods: We obtained medical insurance claims data for all hospitalized patients aged ≥ 28 days in all secondary and tertiary care hospitals in South Korea (n = 347) from January 2019 to December 2019 from the Health Insurance Review & Assessment Service. Modeling was performed to derive a prediction value for antimicrobial use in each institution, which corresponded to the denominator value for calculating K-SAAR. The prediction values of antimicrobial use were modeled separately for each category, for all inpatients and adult patients (aged ≥ 15 years), using stepwise negative binomial regression. Results: The final models for each antimicrobial category were adjusted for different significant risk factors. In the K-SAAR models of all aged patients as well as adult patients, most antimicrobial categories included the number of hospital beds and the number of operations as significant factors, while some antimicrobial categories included mean age for inpatients, hospital type, and the number of patients transferred from other hospitals as significant factors. Conclusion: We developed a model to predict antimicrobial use rates in Korean hospitals, and the model was used as the denominator of the K-SAAR.
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U2 - 10.3346/jkms.2022.37.e191
DO - 10.3346/jkms.2022.37.e191
M3 - Article
C2 - 35726144
AN - SCOPUS:85132279164
SN - 1011-8934
VL - 37
JO - Journal of Korean Medical Science
JF - Journal of Korean Medical Science
IS - 24
M1 - e191
ER -