J Korean Med Sci.  2022 Jun;37(24):e191. 10.3346/jkms.2022.37.e191.

Development of the Korean Standardized Antimicrobial Administration Ratio as a Tool for Benchmarking Antimicrobial Use in Each Hospital

Affiliations
  • 1Department of Internal Medicine, Hanyang University College of Medicine, Seoul, Korea
  • 2Department of Health Convergence, Ewha Womans University, Seoul, Korea
  • 3Department of Research, Health Insurance Review & Assessment Service, Wonju, Korea
  • 4Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea
  • 5Department of Laboratory Medicine, Yonsei University Wonju College of Medicine, Wonju, Korea
  • 6Division of Infectious Diseases, Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
  • 7Department of Pharmacy, Seoul National University Bundang Hospital, Seongnam, Korea
  • 8Korean Society of Health-System Pharmacist, Seoul, Korea
  • 9Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea

Abstract

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.

Keyword

SAAR; KONAS; Antimicrobial Stewardship; Benchmarking; Korea

Cited by  2 articles

Applicability of New Indicators for Healthcare-associated Infections Surveillance in Korea
Sun Hee Park, Sun Young Cho, Soo-Han Choi, Ji Youn Choi, Hee-Jung Son, Hong Bin Kim, Mi Suk Lee
Korean J Healthc Assoc Infect Control Prev. 2022;27(2):104-117.    doi: 10.14192/kjicp.2022.27.2.104.

Applicability of New Indicators for Healthcare-associated Infections Surveillance in Korea
Sang-Oh Lee
Korean J Healthc Assoc Infect Control Prev. 2022;27(2):93-95.    doi: 10.14192/kjicp.2022.27.2.93.


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