Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-12-02T19:46:38.000Z Has data issue: false hasContentIssue false
  • English
  • Français

Predictors of Antimicrobial Stewardship Program Recommendation Disagreement

Published online by Cambridge University Press:  30 April 2018

Laura L. Bio ,
Jenna F. Kruger ,
Betty P. Lee ,
Matthew S. Wood  and
Hayden T. Schwenk
Laura L. Bio
Affiliation:
Lucile Packard Children’s Hospital Stanford, Stanford, California
Jenna F. Kruger
Affiliation:
Lucile Packard Children’s Hospital Stanford, Stanford, California
Betty P. Lee
Affiliation:
Lucile Packard Children’s Hospital Stanford, Stanford, California
Matthew S. Wood
Affiliation:
Lucile Packard Children’s Hospital Stanford, Stanford, California
Hayden T. Schwenk*
Affiliation:
Lucile Packard Children’s Hospital Stanford, Stanford, California Department of Pediatrics, Stanford University School of Medicine, Stanford, California
*
Address correspondence to Hayden T. Schwenk, MD, MPH, Division of Infectious Diseases, Department of Pediatrics, 300 Pasteur Dr, Room G312, Stanford, CA, 94305 ([email protected]).
Get access Rights & Permissions [Opens in a new window]

Abstract

OBJECTIVE

To identify predictors of disagreement with antimicrobial stewardship prospective audit and feedback recommendations (PAFR) at a free-standing children’s hospital.

DESIGN

Retrospective cohort study of audits performed during the antimicrobial stewardship program (ASP) from March 30, 2015, to April 17, 2017.

METHODS

The ASP included audits of antimicrobial use and communicated PAFR to the care team, with follow-up on adherence to recommendations. The primary outcome was disagreement with PAFR. Potential predictors for disagreement, including patient-level, antimicrobial, programmatic, and provider-level factors, were assessed using bivariate and multivariate logistic regression models.

RESULTS

In total, 4,727 antimicrobial audits were performed during the study period; 1,323 PAFR (28%) and 187 recommendations (15%) were not followed due to disagreement. Providers were more likely to disagree with PAFR when the patient had a gastrointestinal infection (odds ratio [OR], 5.50; 95% confidence interval [CI], 1.99–15.21), febrile neutropenia (OR, 6.14; 95% CI, 2.08–18.12), skin or soft-tissue infections (OR, 6.16; 95% CI, 1.92–19.77), or had been admitted for 31–90 days at the time of the audit (OR, 2.08; 95% CI, 1.36–3.18). The longer the duration since the attending provider had been trained (ie, the more years of experience), the more likely they were to disagree with PAFR recommendations (OR, 1.02; 95% CI, 1.01–1.04).

CONCLUSIONS

Evaluation of our program confirmed patient-level predictors of PAFR disagreement and identified additional programmatic and provider-level factors, including years of attending experience. Stewardship interventions focused on specific diagnoses and antimicrobials are unlikely to result in programmatic success unless these factors are also addressed.

Infect Control Hosp Epidemiol 2018;806–813

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 39 , Issue 7 , July 2018 , pp. 806 - 813
Copyright
© 2018 by The Society for Healthcare Epidemiology of America. All rights reserved. 

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.)

Footnotes

PREVIOUS PRESENTATION: A previous iteration of this data was presented at the Eighth Annual International Pediatric Antimicrobial Stewardship Conference on June 2, 2017, in St Louis Missouri.

References

REFERENCES

1. CDC: Get Smart for Healthcare. Overview and evidence to support stewardship. Centers for Disease Control and Prevention website. http://www.cdc.gov/getsmart/healthcare/evidence.html. Published 2016. Accessed September 21, 2016.Google Scholar
2. Dellit, TH, Owens, RC, McGowan, JE Jr, et al. Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America guidelines for developing an institutional program to enhance antimicrobial stewardship. Clin Infect Dis 2007;44:159–177.CrossRefGoogle Scholar
3. Chung, GW, Wu, JE, Yeo, CL, Chan, D, Hsu, LY. Antimicrobial stewardship: a review of prospective audit and feedback systems and an objective evaluation of outcomes. Virulence 2013;4:151–157.CrossRefGoogle Scholar
4. Hersh, AL, De Lurgio, SA, Thurm, C, et al. Antimicrobial stewardship programs in freestanding children’s hospitals. Pediatrics 2015;135:33–39.Google Scholar
5. Newland, JG, Stach, LM, De Lurgio, SA, et al. Impact of a prospective-audit-with-feedback antimicrobial stewardship program at a children’s hospital. J Pediatric Infect Dis Soc 2012;1:179–186.CrossRefGoogle ScholarPubMed
6. Hurst, AL, Child, J, Pearce, K, Palmer, C, Todd, JK, Parker, SK. Handshake stewardship: a highly effective rounding-based antimicrobial optimization service. Pediatr Infect Dis J 2016;35:1104–1110.CrossRefGoogle ScholarPubMed
7. Willis, ZI, Gillon, J, Xu, M, Slaughter, JC, Di Pentima, MC. Reducing antimicrobial use in an academic pediatric institution: evaluation of the effectiveness of a prospective audit with real-time feedback. J Pediatric Infect Dis Soc 2017;6:339–345.Google Scholar
8. Di Pentima, MC, Chan, S, Hossain, J. Benefits of a pediatric antimicrobial stewardship program at a children’s hospital. Pediatrics 2011;128:1062–1070.Google Scholar
9. Goldman, JL, Lee, BR, Hersh, AL, et al. Clinical diagnoses and antimicrobials predictive of pediatric antimicrobial stewardship recommendations: a program evaluation. Infect Control Hosp Epidemiol 2015;36:673–680.CrossRefGoogle ScholarPubMed
10. Lee, BR, Goldman, JL, Yu, D, et al. Clinical impact of an antibiotic stewardship program at a children’s hospital. Infect Dis Ther 2017;6:103–113.Google Scholar
11. Solomkin, JS, Mazuski, JE, Bradley, JS, et al. Diagnosis and management of complicated intra-abdominal infection in adults and children: guidelines by the Surgical Infection Society and the Infectious Diseases Society of America. Clin Infect Dis 2010;50:133–164.Google Scholar
12. Lehrnbecher, T, Robinson, P, Fisher, B, et al. Guideline for the management of fever and neutropenia in children with cancer and hematopoietic stem-cell transplantation recipients: 2017 update. J Clin Oncol 2017;35:2082–2094.Google Scholar
13. Papoutsi, C, Mattick, K, Pearson, M, Brennan, N, Briscoe, S, Wong, G. Social and professional influences on antimicrobial prescribing for doctors-in-training: a realist review. J Antimicrob Chemother 2017;194:1–13.Google Scholar
14. Wong, G, Brennan, N, Mattick, K, Pearson, M, Briscoe, S, Papousi, C. Interventions to improve antimicrobial prescribing of doctors in training: the IMPACT (IMProving Antimicrobial presCribing of doctors in Training) realist review. BMJ Open 2015;5:1–8.CrossRefGoogle ScholarPubMed
15. De Waele, JJ, Schouten, J, Dimopoulos, G. Understanding antibiotic stewardship for the critically ill. Intensive Care Med 2016 Dec; 42:2063–2065.CrossRefGoogle ScholarPubMed
16. Kaki, R, Elligsen, M, Walker, S, Simor, A, Palmay, L, Daneman, N. Impact of antimicrobial stewardship in critical care: a systematic review. J Antimicrob Chemother 2011;66:1223–1230.CrossRefGoogle ScholarPubMed
17. Nzegwu, NI, Rychalsky, MR, Nallu, LA, et al. Implementation of an antimicrobial stewardship program in a neonatal intensive care unit. Infect Control Hosp Epidemiol 2017;38:1137–1143.CrossRefGoogle Scholar
18. Downes, KJ, Weiss, SL, Gerber, JS, et al. A pragmatic biomarker-driven algorithm to guide antibiotic use in the pediatric intensive care unit: the optimizing antibiotic strategies in sepsis (OASIS) study. J Pediatric Infect Dis Soc 2017;6:134–141.Google Scholar
19. Elligsen, M, Walker, SA, Pinto, R, et al. Audit and feedback to reduce broad-spectrum antibiotic use among intensive care unit patients: a controlled interrupted time series analysis. Infect Control Hosp Epidemiol 2012;33:354–361.Google Scholar
20. Ding, H, Yang, Y, Wei, J, et al. Influencing the use of antibiotics in a Chinese pediatric intensive care unit. Pharm World Sci 2008;30:787–793.CrossRefGoogle Scholar
21. de Araujo, OR, da Silva, DC, Diegues, AR, et al. Cefepime restriction improves gram-negative overall resistance patterns in neonatal intensive care unit. Braz J Infect Dis 2007;11:277–280.CrossRefGoogle ScholarPubMed
22. Araujo da Silva, AR, Albernaz de Almeida Dias, DC, Marques, AF, et al. Role of antimicrobial stewardship programmes in children: a systematic review. J Hosp Infect 2017; Epub.Google Scholar
23. Turner, RB, Valcarlos, E, Loeffler, AM, Gilbert, M, Chan, D. Impact of an antimicrobial stewardship program on antibiotic use at a nonfreestanding children’s hospital. J Pediatric Infect Dis Soc 2017;6:e36–e40.Google Scholar
24. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing website. http://www.R-project.org/. Published 2012. Accessed March 15, 2018.Google Scholar
Supplementary material: File

Bio et al. supplementary material

Appendices A-D

Download Bio et al. supplementary material(File)
File 33.6 KB