OBJECTIVE: Clinical practice guidelines and recommended practices to control use of antibiotics have been published, but the effect of these practices on antimicrobial resistance (AMR) rates in hospitals is unknown. The objective of this study was to examine relationships between antimicrobial use control strategies and AMR rates in a national sample of US hospitals. DESIGN: Cross-sectional, stratified study of a nationally representative sample of US hospitals. METHODS: A survey instrument was sent to the person responsible for infection control at a sample of 670 US hospitals. The outcome was current prevalences of 4 epidemiologically important, drug-resistant pathogens, considered concurrently: methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococci, ceftazidime-resistant Klebsiella species, and quinolone (ciprofloxacin)-resistant Escherichia coli. Five independent variables regarding hospital practices were selected from the survey: the extent to which hospitals (1) implement practices recommended in clinical practice guidelines and ensure best practices for antimicrobial use, (2) disseminate information on clinical practice guidelines for antimicrobial use, (3) use antimicrobial-related information technology, (4) use decision support tools, and (5) communicate to prescribers about antimicrobial use. Control variables included the hospitals' number of beds, teaching status, Veterans Affairs status, geographic region, and number of long-term care beds; and the presence of an intensive care unit, a burn unit, or transplant services. A generalized estimating equation modeled all resistance rates simultaneously to identify overall predictors of AMR levels at the facility. RESULTS: Completed survey instruments were returned by 448 hospitals (67%). Four antimicrobial control measures were associated with higher prevalence of AMR. Implementation of recommended practices for antimicrobial use (P < .01) and optimization of the duration of empirical antibiotic prophylaxis (P < .01) were associated with a lower prevalence of AMR. Use of restrictive formularies (P = .05) and dissemination of clinical practice guideline information (P < .01) were associated with higher prevalence of AMR. Number of beds and Veterans Affairs status were also associated with higher AMR rates overall. CONCLUSIONS: Implementation of guideline-recommended practices to control antimicrobial use and optimize the duration of empirical therapy appears to help control AMR rates in US hospitals. A longitudinal study would confirm the results of this cross-sectional study. These results highlight the need for systems interventions and reengineering to ensure more-consistent application of guideline-recommended measures for antimicrobial use.
OBJECTIVE: Clinical practice guidelines and recommended practices to control use of antibiotics have been published, but the effect of these practices on antimicrobial resistance (AMR) rates in hospitals is unknown. The objective of this study was to examine relationships between antimicrobial use control strategies and AMR rates in a national sample of US hospitals. DESIGN: Cross-sectional, stratified study of a nationally representative sample of US hospitals. METHODS: A survey instrument was sent to the person responsible for infection control at a sample of 670 US hospitals. The outcome was current prevalences of 4 epidemiologically important, drug-resistant pathogens, considered concurrently: methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococci, ceftazidime-resistant Klebsiella species, and quinolone (ciprofloxacin)-resistant Escherichia coli. Five independent variables regarding hospital practices were selected from the survey: the extent to which hospitals (1) implement practices recommended in clinical practice guidelines and ensure best practices for antimicrobial use, (2) disseminate information on clinical practice guidelines for antimicrobial use, (3) use antimicrobial-related information technology, (4) use decision support tools, and (5) communicate to prescribers about antimicrobial use. Control variables included the hospitals' number of beds, teaching status, Veterans Affairs status, geographic region, and number of long-term care beds; and the presence of an intensive care unit, a burn unit, or transplant services. A generalized estimating equation modeled all resistance rates simultaneously to identify overall predictors of AMR levels at the facility. RESULTS: Completed survey instruments were returned by 448 hospitals (67%). Four antimicrobial control measures were associated with higher prevalence of AMR. Implementation of recommended practices for antimicrobial use (P < .01) and optimization of the duration of empirical antibiotic prophylaxis (P < .01) were associated with a lower prevalence of AMR. Use of restrictive formularies (P = .05) and dissemination of clinical practice guideline information (P < .01) were associated with higher prevalence of AMR. Number of beds and Veterans Affairs status were also associated with higher AMR rates overall. CONCLUSIONS: Implementation of guideline-recommended practices to control antimicrobial use and optimize the duration of empirical therapy appears to help control AMR rates in US hospitals. A longitudinal study would confirm the results of this cross-sectional study. These results highlight the need for systems interventions and reengineering to ensure more-consistent application of guideline-recommended measures for antimicrobial use.
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