Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-26T09:48:03.365Z Has data issue: false hasContentIssue false
  • English
  • Français

Antimicrobial Use Control Measures to Prevent and Control Antimicrobial Resistance in US Hospitals

Published online by Cambridge University Press:  21 June 2016

Alan J. Zillich ,
Jason M. Sutherland ,
Stephen J. Wilson ,
Daniel J. Diekema ,
Erika J. Ernst ,
Thomas E. Vaughn  and
Bradley N. Doebbeling
Alan J. Zillich*
Affiliation:
Department of Pharmacy Practice, Purdue University College of Pharmacy, West Lafayette, Indiana University School of Medicine, Indianapolis, Indiana, Iowa City, Iowa Veterans Affairs Health Services Research and Development Center on Implementing Evidence-Based Practice, Roudebush Veterans Affairs Medical Center, Indiana University School of Medicine, Indianapolis, Indiana, Iowa City, Iowa Indiana University Center for Outcomes Research, Regenstrief Institute, Indiana University School of Medicine, Indianapolis, Indiana, Iowa City, Iowa
Jason M. Sutherland
Affiliation:
Veterans Affairs Health Services Research and Development Center on Implementing Evidence-Based Practice, Roudebush Veterans Affairs Medical Center, Indiana University School of Medicine, Indianapolis, Indiana, Iowa City, Iowa Indiana University Center for Outcomes Research, Regenstrief Institute, Indiana University School of Medicine, Indianapolis, Indiana, Iowa City, Iowa Division of Biostatistics, Indiana University School of Medicine, Indianapolis, Indiana, Iowa City, Iowa
Stephen J. Wilson
Affiliation:
Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, Iowa City, Iowa
Daniel J. Diekema
Affiliation:
Departments of Internal Medicine and Pathology, Iowa City Veterans Affairs Medical Center andUniversity of Iowa Roy A. and Lucille J. Carver College of Medicine, Iowa City, Iowa
Erika J. Ernst
Affiliation:
Division of Clinical and Administrative Pharmacy, University of Iowa College of Pharmacy, Iowa City, Iowa
Thomas E. Vaughn
Affiliation:
Department of Health Management and Policy, University of Iowa College of Public Health, Iowa City, Iowa
Bradley N. Doebbeling
Affiliation:
Veterans Affairs Health Services Research and Development Center on Implementing Evidence-Based Practice, Roudebush Veterans Affairs Medical Center, Indiana University School of Medicine, Indianapolis, Indiana, Iowa City, Iowa Indiana University Center for Outcomes Research, Regenstrief Institute, Indiana University School of Medicine, Indianapolis, Indiana, Iowa City, Iowa Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, Iowa City, Iowa
*
Purdue University, Pharmacy Programs—Indianapolis, W7555, Myers Building, 1001 West 10th Street, Indianapolis, IN 46202, ([email protected])
Get access Rights & Permissions [Opens in a new window]

Extract

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.

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 27 , Issue 10 , October 2006 , pp. 1088 - 1095
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2006

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Carmeli, Y, Troillet, N, Karchmer, AW, Samore, MH. Health and economic outcomes of antibiotic resistance in Pseudomonas aeruginosa . Arch Intern Med 1999; 159:1127–1132.CrossRefGoogle ScholarPubMed
2. Institute of Medicine (IOM). To Err Is Human: Building a Safer Health System. Kohn, LT, Corrigan, JM, Donaldson, M, eds. Washington, DC: Committee on Quality of Health Care in America, IOM, 2000.Google Scholar
3. Centers for Disease Control and Prevention. Campaign to prevent antimicrobial resistance in healthcare settings: why a campaign? Available at: http://www.cdc.gov/drugresistance/healthcare/problem.htm.Accessed July 11, 2005.Google Scholar
4. Center for Disease Control and Prevention. National Nosocomial Infections Surveillance (NNIS) System report, data summary from January 1992-June 2001, issued August 2001. Am J Infect Control 2001; 29:404–421.CrossRefGoogle Scholar
5. Diekema, DJ, Pfaller, MA, Schmitz, FJ, et al. Survey of infections due to Staphylococcus species: frequency of occurrence and antimicrobial susceptibility of isolates collected in the United States, Canada, Latin America, Europe, and the Western Pacific region for the SENTRY Antimicrobial Surveillance Program, 1997-1999. Clin Infect Dis 2001; 32(Suppl 2):S114–S132.CrossRefGoogle ScholarPubMed
6. Fridkin, SK, Steward, CD, Edwards, JR, et al. Surveillance of antimicrobial use and antimicrobial resistance in United States hospitals: project ICARE phase 2. Project Intensive Care Antimicrobial Resistance Epidemiology (ICARE) hospitals. Clin Infect Dis 1999; 29:245–252.CrossRefGoogle ScholarPubMed
7. John, JF Jr, Fishman, NO. Programmatic role of the infectious diseases physician in controlling antimicrobial costs in the hospital. Clin Infect Dis 1997;24:471–485.CrossRefGoogle ScholarPubMed
8. Healthy People 2010 Immunizations and Infectious Diseases. Washington, DC: US Department of Health and Human Services, Office of Public Health and Science; 2000:14–1 to 14-59.Google Scholar
9. Goldmann, DA, Weinstein, RA, Wenzel, RP, et al. Strategies to prevent and control the emergence and spread of antimicrobial-resistant microorganisms in hospitals: a challenge to hospital leadership. JAMA 1996; 275:234–240.CrossRefGoogle ScholarPubMed
10. Shlaes, DM, Gerding, DN, John, JF Jr, et al. Society for Healthcare Epidemiology of America and Infectious Diseases Society of America Joint Committee on the Prevention of Antimicrobial Resistance: guidelines for the prevention of antimicrobial resistance in hospitals. Clin Infect Dis 1997; 25:584–599.CrossRefGoogle Scholar
11. Centers for Disease Control and Prevention. Campaign to prevent antimicrobial resistance in healthcare settings. 2002. Available at: http://www.cdc.gov/drugresistance/healthcare/default.htm. Accessed March 30, 2005.Google Scholar
12. Murthy, R. Implementation of strategies to control antimicrobial resistance. Chest 2001;119(Suppl 2):405S–411S.CrossRefGoogle ScholarPubMed
13. Gross, PA, Pujat, D. Implementing practice guidelines for appropriate antimicrobial usage: a systematic review. Med Care 2001; 39(Suppl 2):II-55–II-69.CrossRefGoogle ScholarPubMed
14. Gould, IM. A review of the role of antibiotic policies in the control of antibiotic resistance. J Antimicrob Chemother 1999; 43:459–465.CrossRefGoogle ScholarPubMed
15. Parrino, TA. Controlled trials to improve antibiotic utilization: a systematic review of experience, 1984-2004. Pharmacotherapy 2005; 25:289–298.CrossRefGoogle ScholarPubMed
16. Wilton, P, Smith, R, Coast, J, Millar, M. Strategies to contain the emergence of antimicrobial resistance: a systematic review of effectiveness and cost-effectiveness. J Health Serv Res Policy 2002; 7:111–117.CrossRefGoogle ScholarPubMed
17. Ward, MM, Diekema, DJ, Yankey, JW, et al. Implementation of strategies to prevent and control the emergence and spread of antimicrobial-resistant microorganisms in US hospitals. Infect Control Hosp Epidemiol 2005; 26:21–30.CrossRefGoogle Scholar
18. Flach, SD, Diekema, DJ, Yankey, JW, et al. Variation in the use of procedures to monitor antimicrobial resistance in US hospitals. Infect Control Hosp Epidemiol 2005; 26:31–38.CrossRefGoogle Scholar
19. Field, TS, Cadoret, CA, Brown, ML, et al. Surveying physicians: do components of the “total design approach” to optimizing survey response rates apply to physicians? Med Care 2002; 40:596–605.CrossRefGoogle ScholarPubMed
20. Diekema, DJ, Boots Miller, BJ, Vaughn, TE, et al. Antimicrobial resistance trends and outbreak frequency in United States hospitals. Clin Infect Dis 2004; 38:78–85.CrossRefGoogle ScholarPubMed
21. Harbin, JW, Hilbe, JM. Generalized Estimating Equations. Boca Raton, FL: Chapman and Hall/CRC; 2002.Google Scholar
22. Little, R, Rubin, D. Statistical Analysis with Missing Data. New York: Wiley; 1987.Google Scholar
23. Low, DE, Keller, N, Barth, A, Jones, RN. Clinical prevalence, antimicrobial susceptibility, and geographic resistance patterns of enterococci: results from the SENTRY Antimicrobial Surveillance Program, 1997-1999. Clin Infect Dis 2001; 32(Suppl 2)S133–S145.CrossRefGoogle ScholarPubMed
24. Diekema, DJ, Pfaller, MA, Jones, RN, et al. Survey of bloodstream infections due to gram-negative bacilli: frequency of occurrence and antimicrobial susceptibility of isolates collected in the United States, Canada, and Latin America for the SENTRY Antimicrobial Surveillance Program, 1997. Clin Infect Dis 1999; 29:595–607.Google ScholarPubMed
25. Jones, ME, Mayfield, DC, Thornsberry, C, Karlowsky, JA, Sahm, DF, Peterson, D. Prevalence of oxacillin resistance in Staphylococcus aureus among inpatients and outpatients in the United States during 2000. Antimicrob Agents Chemother 2002; 46:3104–3105.CrossRefGoogle ScholarPubMed
26. Karlowsky, JA, Kelly, LJ, Thornsberry, C, et al. Susceptibility to fluoroquinolones among commonly isolated gram-negative bacilli in 2000: TRUST and TSN data for the United States: tracking resistance in the united states today. The Surveillance Network. Int J Antimicrob Agents 2002; 19:21–31.CrossRefGoogle ScholarPubMed
27. Ward, MM, Doebbeling, BN, Vaughn, TE, et al. Effectiveness of a nationally implemented smoking cessation guideline on provider and patient practices. Prev Med 2003; 36:265–271.CrossRefGoogle ScholarPubMed
28. Ward, MM, Vaughn, TE, Uden-Holman, T, Doebbeling, BN, Clarke, WR, Woolson, RF. Physician knowledge, attitudes and practices regarding a widely implemented guideline. J Eval Clin Pract 2002; 8:155–162.CrossRefGoogle ScholarPubMed
29. Ward, MM, Yankey, JW, Vaughn, TE, et al. Physician process and patient outcome measures for diabetes care: relationships to organizational characteristics. Med Care 2004; 42:840–850.CrossRefGoogle ScholarPubMed
30. Bero, LA, Grilli, R, Grimshaw, JM, Harvey, E, Oxman, AD, Thomson, MA. Closing the gap between research and practice: an overview of systematic reviews of interventions to promote the implementation of research findings. The Cochrane Effective Practice and Organization of Care Review Group. BMJ 1998; 317:465–468.CrossRefGoogle Scholar
31. Wakefield, DS, Pfaller, M, Massanari, RM, Hammons, GT. Variation in methicillin-resistant Staphylococcus aureus occurrence by geographic location and hospital characteristics. Infect Control 1987; 8:151–157.CrossRefGoogle ScholarPubMed
32. Lawton, RM, Fridkin, SK, Gaynes, RP, McGowan, JE Jr. Practices to improve antimicrobial use at 47 US hospitals: the status of the 1997 SHEA/IDSA position paper recommendations. Society for Healthcare Epidemiology of America / Infectious Diseases Society of America. Infect Control Hosp Epidemiol 2000; 21:256–259.CrossRefGoogle ScholarPubMed
33. Kawamoto, K, Houlihan, CA, Balas, EA, Lobach, DF. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. BMJ 2005; 330:765.CrossRefGoogle ScholarPubMed
34. Garg, AX, Adhikari, NK, McDonald, H, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA 2005; 293:1223–1238.CrossRefGoogle ScholarPubMed
35. Fang, E, Mittman, BS, Weingarten, S. Use of clinical practice guidelines in managed care physician groups. Arch Earn Med 1996; 5:528–531.Google ScholarPubMed
36. Newton, J, Knight, D, Woolhead, G. General practitioners and clinical guidelines: a survey of knowledge, use and beliefs. Br J Gen Pract 1996; 46:513–517.Google ScholarPubMed
37. Wise, CG, Billi, JE. A model for practice guideline adaptation and implementation: empowerment of the physician. Jt Comm J Qual Improv 1995;21:465–476.Google Scholar
38. Davis, DA, Thomson, MA, Oxman, AD, Haynes, RB. Evidence for the effectiveness of CME: a review of 50 randomized controlled trials. JAMA 1992; 268:1111–1117.CrossRefGoogle ScholarPubMed
39. Lomas, J, Anderson, GM, Domnick-Pierre, K, Vayda, E, Enkin, MW, Hannah, WJ. Do practice guidelines guide practice? The effect of a consensus statement on the practice of physicians. N Engl J Med 1989; 321:1306–1311.CrossRefGoogle ScholarPubMed
40. Woolf, SH. Practice guidelines: a new reality in medicine. III. Impact on patient care. Arch Intern Med 1993; 153:2646–2655.CrossRefGoogle Scholar
41. Greco, PJ, Eisenberg, JM. Changing physicians' practices. N Engl J Med 1993;329:1271–1273.CrossRefGoogle ScholarPubMed
42. Teich, J, Osheroff, J, Pifer, E, Sittig, D, Jenders, R. Clinical decision support in electronic prescribing: recommendations and an action plan, report of the Joint Clinical Decision Support Workgroup. Washington, DC; Department of Health of Human Services; 2005.Google Scholar
43. Polk, RE. Antimicrobial formularies: can they minimize antimicrobial resistance? Am J Health Syst Pharm 2003; 60(Suppl 1):S16–S19.CrossRefGoogle ScholarPubMed
44. Bergstrom, CT, Lo, M, Lipsitch, M. Ecological theory suggests that antimicrobial cycling will not reduce antimicrobial resistance in hospitals. Proc Natl Acad Sci U S A 2004; 101:13285–13290.CrossRefGoogle Scholar
45. Landman, D, Chockalingam, M, Quale, JM. Reduction in the incidence of methicillin-resistant Staphylococcus aureus and ceftazidime-resistant Klebsiella pneumoniae following changes in a hospital antibiotic formulary. Clin Infect Dis 1999;28:1062–1066.CrossRefGoogle Scholar
46. Rahal, JJ, Urban, C, Horn, D, et al. Class restriction of cephalosporin use to control total cephalosporin resistance in nosocomial Klebsiella . JAMA 1998; 280:1233–1237.CrossRefGoogle ScholarPubMed
47. Regal, RE, DePestel, DD, VandenBussche, HL. The effect of an antimicrobial restriction program on Pseudomonas aeruginosa resistance to beta-lactams in a large teaching hospital. Pharmacotherapy 2003; 23:618–624.CrossRefGoogle Scholar
48. Bantar, C, Sartori, B, Vesco, E, et al. A hospitalwide intervention program to optimize the quality of antibiotic use: impact on prescribing practice, antibiotic consumption, cost savings, and bacterial resistance. Clin Infect Dis 2003; 37:180–186.CrossRefGoogle ScholarPubMed
49. Cook, PP, Catrou, PG, Christie, JD, Young, PD, Polk, RE. Reduction in broad-spectrum antimicrobial use associated with no improvement in hospital antibiogram. J Antimicrob Chemother 2004; 53:853–859.CrossRefGoogle ScholarPubMed
50. Bosso, JA. The impact of antibiotic management on resistance. Pharmacotherapy 2004; 24:224S–231S.CrossRefGoogle ScholarPubMed
51. Ernst, EJ, Diekema, DJ, BootsMiller, BJ, et al. Are United States hospitals following national guidelines for the analysis and presentation of cumulative antimicrobial susceptibility data? Diagn Microbiol Infect Dis 2004; 49:141–145.CrossRefGoogle ScholarPubMed