Hostname: page-component-586b7cd67f-gb8f7 Total loading time: 0 Render date: 2024-12-01T01:29:25.120Z Has data issue: false hasContentIssue false
  • English
  • Français

Association Between High-Risk Medication Usage and Healthcare Facility-Onset C. difficile Infection

Published online by Cambridge University Press:  21 April 2016

Julie A. Patterson ,
Michael B. Edmond ,
Samuel F. Hohmann  and
Amy L. Pakyz
Julie A. Patterson
Affiliation:
Department of Pharmacotherapy and Outcomes Science, School of Pharmacy, Virginia Commonwealth University Richmond, Virginia
Michael B. Edmond
Affiliation:
Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa
Samuel F. Hohmann
Affiliation:
University Health System Consortium, Chicago, Illinois
Amy L. Pakyz*
Affiliation:
Department of Pharmacotherapy and Outcomes Science, School of Pharmacy, Virginia Commonwealth University Richmond, Virginia
*
Address correspondence to Amy L. Pakyz, PharmD, MS, PhD, Department of Pharmacotherapy and Outcomes Science, Virginia Commonwealth University School of Pharmacy, 410 North 12th Street, Box 980533 ([email protected]).
Get access Rights & Permissions [Opens in a new window]

Abstract

OBJECTIVE

National hospital performance measures for C. difficile infection (CD) are available; comparing antibacterial use among performance levels can aid in identifying effective antimicrobial stewardship strategies to reduce CDI rates.

DESIGN

Hospital-level, cross-sectional analysis.

METHODS

Hospital characteristics (ie, demographics, medications, patient mix) were obtained for 77 hospitals for 2013. Hospitals were assigned 1 of 3 levels of a CDI standardized infection ratio (SIR): ‘Worse than,’ ‘Better than,’ or ‘No different than’ a national benchmark. Analyses compared medication use (total and broad-spectrum antibacterials) for 3 metrics: days of therapy per 1,000 patient days; length of therapy; and proportion of patients receiving a medication across SIR levels. A multivariate, ordered-probit regression identified characteristics associated with SIR categories.

RESULTS

Regarding total average antimicrobial use per patient, there was a significant difference detected in mean length of therapy: ‘No different’ hospitals having the longest (4.93 days) versus ‘Worse’ (4.78 days) and ‘Better’ (4.43 days) (P<.01). ‘Better’ hospitals used fewer total antibacterials (693 days of therapy per 1,000 patient days) versus ‘No different’ (776 days) versus ‘Worse’ (777 days) (P<.05). The ‘Better’ hospitals used broad-spectrum antibacterials for a shorter average length of therapy (4.03 days) versus ‘No different’ (4.51 days) versus ‘Worse’ (4.38 days) (P<.05). ‘Better’ hospitals used fewer broad-spectrum antibacterials (310 days of therapy per 1,000 patient days) versus ‘No different’ (364 days) versus ‘Worse’ (349 days) (P<.05). Multivariate analysis revealed that the proportion of elderly patients and chemotherapy days of therapy per 1,000 patient days was significantly negatively associated with the SIR.

CONCLUSIONS

These findings have potential implications regarding the need to fully account for hospital patient mix when carrying out inter-hospital comparisons of CDI rates.

Infect Control Hosp Epidemiol 2016;37:909–915

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 37 , Issue 8 , August 2016 , pp. 909 - 915
Copyright
© 2016 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.)

References

REFERENCES

1. Magill, SS, Edwards, JR, Fridkin, SK, Emerging Infections Program Healthcare-Associated Infections and Antimicrobial Use Prevalence Survey Team. Survey of health care-associated infections. N Engl J Med 2014;370:2542–2543.Google Scholar
2. Zerey, M, Paton, BL, Lincourt, AE, Gersin, KS, Kercher, KW, Heniford, BT. The burden of Clostridium difficile in surgical patients in the United States. Surg Infect 2007;8:557–566.Google Scholar
3. Lessa, FC, Mu, Y, Bamberg, WM, et al. Burden of Clostridium difficile infection in the United States. N Engl J Med 2015;372:825–834.Google Scholar
4. Loo, VG, Bourgault, AM, Poirier, L, et al. Host and pathogen factors for Clostridium difficile infection and colonization. N Engl J Med 2011;365:1693–1703.Google Scholar
5. Kyne, L, Sougioultzis, S, McFarland, LV, Kelly, CP. Underlying disease severity as a major risk factor for nosocomial Clostridium difficile diarrhea. Infect Control Hosp Epidemiol 2002;23:653–659.Google Scholar
6. Baxter, R, Ray, GT, Fireman, BH. Case-control study of antibiotic use and subsequent Clostridium difficile-associated diarrhea in hospitalized patients. Infect Control Hosp Epidemiol 2008;29:44–50.Google Scholar
7. Kwok, CS, Arthur, AK, Anibueze, CI, Singh, S, Cavallazzi, R, Loke, YK. Risk of Clostridium difficile infection with acid suppressing drugs and antibiotics: Meta-analysis. Am J Gastroenterol 2012;107:1011–1019.Google Scholar
8. Deshpande, A, Pant, C, Pasupuleti, V, et al. Association between proton pump inhibitor therapy and Clostridium difficile infection in a meta-analysis. Clin Gastroenterol Hepatol 2012;10:225–233.Google Scholar
9. Stevens, V, Dumyati, G, Fine, LS, Fisher, SG, van Wijngaarden, E. Cumulative antibiotic exposures over time and the risk of Clostridium difficile infection. Clin Infect Dis 2011;53:42–48.Google Scholar
10. Gilca, R, Hubert, B, Fortin, E, Gaulin, C, Dionne, M. Epidemiological patterns and hospital characteristics associated with increased incidence of Clostridium difficile infection in Quebec, Canada, 1998–2006. Infect Control Hosp Epidemiol 2010;31:939–947.Google Scholar
11. Chandler, RE, Hedberg, K, Cieslak, PR. Clostridium difficile-associated disease in Oregon: Increasing incidence and hospital-level risk factors. Infect Control Hosp Epidemiol 2007;28:116–122.Google Scholar
12. Pakyz, AL, Jawahar, R, Wang, Q, Harpe, SE. Medication risk factors associated with healthcare-associated Clostridium difficile infection: a multilevel model case-control study among 64 US academic medical centres. J Antimicrobial Chemother 2014;69:1127–1131.Google Scholar
13. Ricciardi, R, Harriman, K, Baxter, NN, Hartman, LK, Town, RJ, Virnig, BA. Predictors of Clostridium difficile colitis infections in hospitals. Epidemiol Infect 2008;136:913–921.CrossRefGoogle ScholarPubMed
14. Jou, J, Ebrahim, J, Shofer, FS, Hamilton, KW, Stern, J, Han, JH. Environmental transmission of Clostridium difficile: association between hospital room size and C. difficile infection. Infect Control Hosp Epidemiol 2015;36:564–568.Google Scholar
15. Datta, R, Kazerouni, NN, Rosenberg, J, et al. Substantial variation in hospital rankings after adjusting for hospital-level predictors of publicly-reported hospital-associated Clostridium difficile infection rates. Infect Control Hosp Epidemiol 2015;36:464–466.Google Scholar
16. Ahyow, LC, Lambert, PC, Jenkins, DR, Neal, KR, Tobin, M. Bed occupancy rates and hospital-acquired Clostridium difficile infection: A cohort study. Infect Control Hosp Epidemiol 2013;34:1062–1069.CrossRefGoogle ScholarPubMed
17. CMS to improve quality of care during hospital inpatient stays. Centers for Medicare and Medicaid Services website. https://www.cms.gov/Newsroom/MediaReleaseDatabase/Fact-sheets/2014-Fact-sheets-items/2014-08-04-2.html. Accessed November 4, 2015.Google Scholar
18. 3M APR DRG Software. 3M Health Information Systems website. http://solutions.3m.com/wps/portal/3M/en_US/Health-Information-Systems/HIS/Products-and-Services/Products-List-A-Z/APR-DRG-Software. Accessed November 4, 2015.Google Scholar
19. Multidrug-resistant organism and Clostridium difficile infection (MDRO/CDI) module. Centers for Disease Control and Prevention website. http://www.cdc.gov/nhsn/PDFs/pscManual/12pscMDRO_CDADcurrent.pdf. Published 2016. Accessed March 31, 2016.Google Scholar
20. Pakyz, AL, Gurgle, HE, Ibrahim, OM, Oinonen, MJ, Polk, RE. Trends in antibacterial use in hospitalized pediatric patients in United States academic health centers. Infect Control Hosp Epidemiol 2009;30:600–603.Google Scholar
21. Lessa, FC, Gould, CV, McDonald, LC. Current status of Clostridium difficile infection epidemiology. Clin Infect Dis 2012;55:S65–S70.Google Scholar
22. Feazel, LM, Malhotra, A, Perencevich, EN, Kaboli, P, Diekema, DJ, Schweizer, ML. Effect of antibiotic stewardship programmes on Clostridium difficile incidence: a systematic review and meta-analysis. J Antimicrob Chemother 2014;69:1748–1754.Google Scholar
23. Slimings, C, Riley, TV. Antibiotics and hospital-acquired Clostridium difficile infection: Update of systematic review and meta-analysis. J Antimicrob Chemother 2014;69:881–891.Google Scholar
24. Jenkins, TC, Knepper, BC, Shihadeh, K, et al. Long-term outcomes of an antimicrobial stewardship program implemented in a hospital with low baseline antibiotic use. Infect Control Hosp Epidemiol 2015;36:664–672.CrossRefGoogle Scholar
25. Davey, P, Brown, E, Charani, E, et al. Interventions to improve antibiotic prescribing practices for hospital inpatients. Cochrane Database Syst Rev 2013;4:CD003543.Google Scholar
26. Talpaert, MJ, Gopal Rao, G, Cooper, BS, Wade, P. Impact of guidelines and enhanced antibiotic stewardship on reducing broad-spectrum antibiotic usage and its effect on incidence of Clostridium difficile infection. J Antimicrobial Chemother 2011;66:2168–2174.Google Scholar
27. Kanerva, M, Ollgren, J, Voipio, T, Mentula, S, Lyytikainen, O. Regional differences in Clostridium difficile infections in relation to fluoroquinolone and proton pump inhibitor use, Finland, 2008-2011. Infect Dis (Lond) 2015;47:530–535.Google Scholar
28. Brown, K, Valenta, K, Fisman, D, Simor, A, Daneman, N. Hospital ward antibiotic prescribing and the risks of Clostridium difficile infection. JAMA Intern Med 2015;175:626–633.Google Scholar
29. Mayfield, JL, Leet, T, Miller, J, Mundy, LM. Environmental control to reduce transmission of Clostridium difficile . Clin Infect Dis 2000;31:995–1000.Google Scholar
30. Lawrence, SJ, Puzniak, LA, Shadel, BN, Gillespie, KN, Kollef, MH, Mundy, LM. Clostridium difficile in the intensive care unit: epidemiology, costs, and colonization pressure. Infect Control Hosp Epidemiol 2007;28:123–130.Google Scholar
31. Schaier, M, Wendt, C, Zeier, M, Ritz, E. Clostridium difficile diarrhoea in the immunosuppressed patient—update on prevention and management. Nephrol Dial Transplant 2004;19:2432–2436.Google Scholar
32. Anand, A, Glatt, AE. Clostridium difficile infection associated with antineoplastic chemotherapy: a review. Clin Infect Dis 1993;17:109–113.Google Scholar
33. Thompson, ND, Edwards, JR, Dudeck, MA, Fridkin, SK, Magill, SS. Evaluating the use of the case mix index for risk adjustment of healthcare-associated infection data: an illustration using Clostridium difficile infection data from the National Healthcare Safety Network. Infect Control Hosp Epidemiol 2016;37:19–25.Google Scholar