Home > Available Issues
Original Articles
Surveillance of Antimicrobial Use and Antimicrobial Resistance
Young Kyung Yoon, M.D., Min Ja Kim, M.D., Jang Wook Sohn, M.D., Dae Won Park, M.D., Jeong-Yeon Kim, M.D. and Byung Chul Chun, M.D.
Division of Infectious Diseases, Department of Internal Medicine, Korea University College of Medicine, Department of Preventive Medicine, Korea University College of Medicine, Seoul, Korea
Vol.40 Num.2 (p93~101)
Background:The purpose of this study was to investigate the relationship between antimicrobial consumption and antimicrobial resistance and to predict for the level of antimicrobial resistance by a time series analysis.
Materials and Methods:In a 750-bed medical center, antimicrobial consumption data of 12 classes of antimicrobials and surveillance of resistant profiles from all microbial isolates were collected from 1/2004 through 3/2007 by database from the hospital's computerized order system. World Health Organization 2004 definition of defined daily doses per 1,000 patient days were used to express the antimicrobial use density (AUD). The monthly proportion of resistant isolates (PR) of selected pathogens and monthly AUD were analyzed by time series analysis with transfer function model by using the SAS/ETS software.
Results:The microbial surveillance data covered 15,522 isolates. PR of ciprofloxacin-resistant E.coli (EC-CFX), imipenem-resistant P. aureginosa, and methicillin-resistant S. aureus (MRSA) were 32.5%14.0, 11.4%8.1, and 78.6%6.9. The two highest monthly AUD of 12 class antimicrobials were 156.26.5 AUD for aminoglycosides and 145.76.0 AUD for 3rd-generation cephalosporins. By using time series analysis, we verified a significant correlation between the monthly CFX use and the PR of EC-CFX, and between the monthly penicillin use and the PR of MRSA.
Conclusion:Antibiotic consumption and PR of antimicrobial resistant pathogens remained stable over the period of study. Furthermore, we could confirm the usefulness of a time series analysis to demonstrate a temporal relationship between antimicrobial use and resistance, to predict the effect of antibiotics use on antimicrobial resistance.
Keywords : Antimicrobial utilization, Antibiotic resistance, Surveillance