2006 HSR&D National Meeting Abstract
3001 — Antimicrobial Use Control Measures to Prevent and Control Antimicrobial Resistance in US Hospitals
Zillich AJ (Purdue University College of Pharmacy and HSR&D Center on Implementing Evidence-based Practice, Roudebush VA Medical Center)
Sutherland JM (Indiana University School of Medicine and HSR&D Center on Implementing Evidence-based Practice, Roudebush VA Medical Center)
Wilson SJ (Indiana University School of Medicine)
Diekema DJ (Iowa City Veterans Affairs Medical Center, University of Iowa College of Medicine)
Ernst EJ (University of Iowa College of Pharmacy)
Vaugh TE (University of Iowa College of Public Health)
Doebbeling BN (HSR&D Center on Implementing Evidence-based Practice, Roudebush VA Medical Center, Regenstrief Institute, Inc, and IU School of Medicine)
Inappropriate use of antibiotics and control of antimicrobial resistance (AMR) are major public health issues. Clinical practice guidelines (CPGs) and practices to control use of antibiotics have been published, however little is known regarding the effect of these practices on AMR rates in hospitals. The objective of this study is to identify relationships between antimicrobial use control strategies and AMR in a national sample of U.S. hospitals.
Cross-sectional, stratified, national survey of 670 US hospitals. The outcome reflected four dependent variables considered concurrently: prevalence of AMR for 1) methicillin-resistant Staphylococcus aureus (MRSA), 2) vancomycin-resistant enterococci (VRE), 3) ceftazidime-resistant Klebsiella species (K-ESBL), and 4) quinolone (ciprofloxacin)-resistant E. coli (QREC). The independent variables included the extent to which hospitals: 1) implement and disseminate CPGs for antimicrobial use, 2) ensure practices for appropriate use of antimicrobials, 3) use antimicrobial-related information technology, 4) use decision support tools, and 5) communicate to prescribers about antimicrobial usage. Control variables included hospital bed size, teaching status, Veteran’s Affairs (VA) status, geographic region, number of long-term care beds, and presence of an intensive care unit (ICU), a burn unit, or transplant services. A generalized estimating equation modeled all resistance rates simultaneously to identify predictors of AMR.
A total of 448 hospitals (67%) responded. Four antimicrobial control measures predicted (or were associated with) AMR. Implementation of antimicrobial use CPGs (p<0.01) and best practice for duration of empiric antibiotic prophylaxis (p<0.01) was associated with lower prevalence of AMR. Use of restrictive formularies (p=0.05) and dissemination of CPGs (p<0.01) were associated with higher prevalence of AMR. Hospital bed size and VA status were also associated with overall AMR levels. However, an interaction showed larger VA hospitals had lower AMR rates in the final model.
Implementation of guidelines and best practices for duration of empiric therapy was associated with decreased AMR. More innovative strategies are needed to combine and implement measures in accordance with national guidelines.
These data suggest certain strategies promulgated in national guidelines can decrease AMR.