Dataset Information

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

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.

SUBMITTER: Kim B

PROVIDER: S-EPMC9247727 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectivesEvaluation of the extent and appropriateness of antimicrobial use is a cornerstone of antibiotic stewardship programs, but it is time-consuming. Documentation of the indication at the moment of prescription might be more time-efficient. We investigated the real-life feasibility of mandatory documentation of the indication for all hospital antibiotic prescriptions for quality evaluation purposes.MethodsA mandatory prescription-indication format was implemented in the Electronic Medical Record (EMR) of three hospitals using EPIC or ChipSoft HIX software. We evaluated the retrieved data of all antibiotics (J01) prescribed as empiric therapy in adult patients with respiratory tract infections (RTI) or urinary tract infections (UTI), from January through December 2017 in Hospital A, June through October 2019 in Hospital B and May 2019 through June 2020 in Hospital C. Endpoints were the accuracy of the data, defined as agreement between selected indication for the prescription and the documented indication in the EMR, as assessed by manually screening a representative sample of eligible patient records in the EMR of the three hospitals, and appropriateness of the prescriptions, defined as the prescriptions being in accordance with the national guidelines.ResultsThe datasets of hospitals A, B and C contained 9588, 338 and 5816 empiric antibiotic prescriptions indicated for RTI or UTI, respectively. The selected indication was in accordance with the documented indication in 96.7% (error rate: 10/300), 78.2% (error rate: 53/243), and 86.9% (error rate: 39/298), respectively. A considerable variation in guideline adherence was seen between the hospitals for severe community acquired pneumonia (adherence rate ranged from 35.4 to 53.0%), complicated UTI (40.0-67.1%) and cystitis (5.6-45.3%).ConclusionsAfter local validation of the datasets to verify and optimize accuracy of the data, mandatory documentation of the indication for antibiotics enables a reliable and time-efficient method for systematic registration of the extent and appropriateness of empiric antimicrobial use, which might enable benchmarking both in-hospital and between hospitals.