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Burden of Bloodstream Infection Caused by Extended-Spectrum β-Lactamase–Producing Enterobacteriaceae Determined Using Multistate Modeling at a Swiss University Hospital and a Nationwide Predictive Model

Published online by Cambridge University Press:  02 January 2015

Andrew Stewardson ,
Carolina Fankhauser ,
Giulia De Augelis ,
Peter Rohner ,
Edith Safran ,
Jacques Schrenzel ,
Didier Pittet  and
Stephan Harbarth
Andrew Stewardson*
Affiliation:
Infection Control Program, University of Geneva Hospitals and Faculty of Medicine, Geneva, Switzerland
Carolina Fankhauser
Affiliation:
Infection Control Program, University of Geneva Hospitals and Faculty of Medicine, Geneva, Switzerland
Giulia De Augelis
Affiliation:
Division of Infectious Diseases, Università Cattolica Sacro Cuore, Rome, Italy
Peter Rohner
Affiliation:
Health-Economic Unit, University of Geneva Hospitals and Faculty of Medicine, Geneva, Switzerland
Edith Safran
Affiliation:
Health-Economic Unit, University of Geneva Hospitals and Faculty of Medicine, Geneva, Switzerland
Jacques Schrenzel
Affiliation:
Clinical Microbiology Laboratory, Service of Infectious Diseases, University of Geneva Hospitals, Geneva, Switzerland
Didier Pittet
Affiliation:
Infection Control Program, University of Geneva Hospitals and Faculty of Medicine, Geneva, Switzerland
Stephan Harbarth
Affiliation:
Infection Control Program, University of Geneva Hospitals and Faculty of Medicine, Geneva, Switzerland
*
Service de Prévention et Contrôle de l'Infection, Hôpitaux Universitaires de Genève, Rue Gabrielle-Perret-Gentil 4, CH-1211 Genève 14, Switzerland (stephan.harbarth@hcuge.ch)
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Abstract

Objective.

To obtain an unbiased estimate of the excess hospital length of stay (LOS) and cost attributable to extended-spectrum β-lactamase (ESBL) positivity in bloodstream infections (BSIs) due to Enterobacteriaceae.

Design.

Retrospective cohort study.

Setting.

A 2,200-bed academic medical center in Geneva, Switzerland.

Patients.

Patients admitted during 2009.

Methods.

We used multistate modeling and Cox proportional hazards models to determine the excess LOS and adjusted end-of-LOS hazard ratio (HR) for ESBL-positive and ESBL-negative BSI. We estimated economic burden as the product of excess LOS and average bed-day cost. Patient-level accounting data provided a complementary analysis of economic burden. A predictive model was fitted to national surveillance data.

Results.

Thirty ESBL-positive and 96 ESBL-negative BSI cases were included. The excess LOS attributable to ESBL-positive and ESBL-negative BSI was 9.4 (95% confidence interval [CI], 0.4–18.4) and 2.6 (95% CI, 0.7–5.9) days, respectively. ESBL positivity was therefore associated with 6.8 excess days and CHF 9,473 per BSI. The adjusted end-of-LOS HRs for ESBL-positive and ESBL-negative BSI were 0.62 (95% CI, 0.43–0.89) and 0.90 (95% CI, 0.74–1.10), respectively. After reimbursement, the average financial loss per acute care episode in ESBL-positive BSI, ESBL-negative BSI, and control cohorts was CHF 48,674, 48,131, and 13,532, respectively. Our predictive model estimated that the nationwide cost of third-generation cephalosporin resistance would increase from CHF 2,084,000 in 2010 to CHF 3,526,000 in 2015.

Conclusions.

This is the first hospital-wide analysis of excess LOS attributable to ESBL positivity determined using multistate modeling to avoid time-dependent bias. These results may inform health-economic evaluations of interventions targeting ESBL control.

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 34 , Issue 2 , February 2013 , pp. 133 - 143
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2013 

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References

1. Livermore, DM, Canton, R, Gniadkowski, M, et al. CTX-M: changing the face of ESBLs in Europe. J Antimicrob Chemother 2007;59:165–174.Google Scholar
2. Hawkey, PM, Jones, AM. The changing epidemiology of resistance. J Antimicrob Chemother 2009;64(suppl 1):i3–i10.Google Scholar
3. Schwaber, MJ, Navon-Venezia, S, Kaye, KS, Ben-Ami, R, Schwartz, D, Carmeli, Y. Clinical and economic impact of bacteremia with extended-spectrum-β-lactamase-producing Enterobacteriaceae . Antimicrob Agents Chemother 2006;50:1257–1262.Google Scholar
4. Schwaber, MJ, Carmeli, Y. Mortality and delay in effective therapy associated with extended-spectrum β-lactamase production in Enterobacteriaceae bacteraemia: a systematic review and metaanalysis. J Antimicrob Chemother 2007;60:913–920.Google Scholar
5. Melzer, M, Petersen, I. Mortality following bacteraemic infection caused by extended spectrum beta-lactamase (ESBL) producing E. coli compared to non-ESBL producing E. coli . J Infect 2007;55:254–259.Google Scholar
6. Hyle, EP, Lipworth, AD, Zaoutis, TE, Nachamkin, I, Bilker, WB, Lautenbach, E. Impact of inadequate initial antimicrobial therapy on mortality in infections due to extended-spectrum β-lacta-mase-producing Enterobacteriaceae: variability by site of infection. Arch Intern Med 2005;165:1375–1380.Google Scholar
7. Graves, N, Harbarth, S, Beyersmann, J, Barnett, A, Halton, K, Cooper, B. Estimating the cost of health care-associated infections: mind your p's and q's. Clin Infect Dis 2010;50:1017–1021.Google Scholar
8. Graves, N. Economics and preventing hospital-acquired infection. Emerg Infect Dis 2004;10:561–566.Google Scholar
9. Brun-Buisson, C, Roudot-Thoraval, F, Girou, E, Grenier-Sennelier, C, Durand-Zaleski, I. The costs of septic syndromes in the intensive care unit and influence of hospital-acquired sepsis. Intensive Care Med 2003;29:1464–1471.Google Scholar
10. Maragakis, LL, Perencevich, EN, Cosgrove, SE. Clinical and economic burden of antimicrobial resistance. Expert Rev Anti Infect Ther 2008;6:751–763.Google Scholar
11. Beyersmann, J, Wolkewitz, M, Allignol, A, Grambauer, N, Schumacher, M. Application of multistate models in hospital epidemiology: advances and challenges. Biom J 2011;53:332–350.Google Scholar
12. Beyersmann, J, Kneib, T, Schumacher, M, Gastmeier, P. Nosocomial infection, length of stay, and time-dependent bias. Infect Control Hosp Epidemiol 2009;30:273–276.Google Scholar
13. Mauldin, PD, Salgado, CD, Hansen, IS, Durup, DT, Bosso, JA. Attributable hospital cost and length of stay associated with health care-associated infections caused by antibiotic-resistant gram-negative bacteria. Antimicrob Agents Chemother 2010;54:109–115.Google Scholar
14. Barnett, AG, Beyersmann, J, Allignol, A, Rosenthal, VD, Graves, N, Wolkewitz, M. The time-dependent bias and its effect on extra length of stay due to nosocomial infection. Value Health 2011;14:381–386.Google Scholar
15. De Angelis, G, Allignol, A, Murthy, A, et al. Multistate modelling to estimate the excess length of stay associated with meticillin-resistant Staphylococcus aureus colonisation and infection in surgical patients. J Hosp Infect 2011;78:86–91.Google Scholar
16. Lambert, ML, Suetens, C, Savey, A, et al. Clinical outcomes of health-care-associated infections and antimicrobial resistance in patients admitted to European intensive-care units: a cohort study. Lancet Infect Dis 2011;11:30–38.Google Scholar
17. Eggimann, P, Harbarth, S, Constantin, MN, Touveneau, S, Chevrolet, JC, Pittet, D. Impact of a prevention strategy targeted at vascular-access care on incidence of infections acquired in intensive care. Lancet 2000;355:1864–1868.Google Scholar
18. Harbarth, S, Rohner, P, Auckenthaler, R, Safran, E, Sudre, P, Pittet, D. Impact and pattern of gram-negative bacteraemia during 6 y at a large university hospital. Scand J Infect Dis 1999;31:163–168.Google Scholar
19. Horan, TC, Andrus, M, Dudeck, MA. CDC/NHSN surveillance definition of health care-associated infection and criteria for specific types of infections in the acute care setting. Am J Infect Control 2008;36:309–332.Google Scholar
20. Friedman, ND, Kaye, KS, Stout, JE, et al. Health care-associated bloodstream infections in adults: a reason to change the accepted definition of community-acquired infections. Ann Intern Med 2002;137:791–797.Google Scholar
21. Clinical and Laboratory Standards Institute (CLSI). Performance Standards for Antimicrobial Susceptibility Testing: Approved Standard M7-A7. Wayne, PA: CLSI, 2006.Google Scholar
22. Aalen, O, Johansen, S. An empirical transition matrix for non-homogeneous Markov chains based on censored observations. Scand J Stat 1978;5:141–150.Google Scholar
23. Andersen, PK, Borgan, O, Gill, RD, Keiding, N. Statistical models based on counting processes. New York: Springer, 1993.Google Scholar
24. Hôpitaux universitaires de Genève. Guide pratique de comptabilité analytique pour les hôpitaux latins compatible avec REKOLE®. http://comptabilite-analytique.hug-ge.ch/_library/pdf/GUIDE_PRATIQUE_CAE.pdf. Published 2009. Accessed July 19, 2012.Google Scholar
25. Hugonnet, S, Eggimann, P, Borst, F, Maricot, P, Chevrolet, JC, Pittet, D. Impact of ventilator-associated pneumonia on resource utilization and patient outcome. Infect Control Hosp Epidemiol 2004;25:1090–1096.Google Scholar
26. World Health Organization (WHO). International Statistical Classification of Diseases and Related Health Problems, 10th Revision. Geneva: WHO, 2007.Google Scholar
27. Swiss Federal Office of Statistics. Classification Suisse des Interventions Chirurgicales (CHOP) version 11. http://www.bfs.admin.ch/bfs/portal/fr/index/infothek/nomenklaturen/blank/blank/chop/02.html#parsys_50214. Published 2008. Accessed July 19, 2012.Google Scholar
28. Club d'utilisateurs APDRG Suisse. APDRG Suisse website. http://www.apdrgsuisse.ch. Published 2004. Accessed July 14, 2012.Google Scholar
29. Kronenberg, A, Hilty, M, Mühlemann, K. Temporal trends of Enterobacteriaceae with resistance to higher generation cepha-losporines in Switzerland, 2004 to 2010. In: Program and Abstracts of the 21st European Congress of Clinical Microbiology and Infectious Diseases. May 7-10, 2011; Milan, Italy. Abstract P657.Google Scholar
30. Swiss Federal Office of Statistics. Statistique des hôpitaux 2010—tableaux standard, http://www.bfs.admin.ch/bfs/portal/fr/index/themen/14/03/01/data/01.html. Published 2012. Accessed April 26, 2012.Google Scholar
31. Department of Regional Affairs, Economy, and Health, State Council (Geneva). Suivi des prestations de santé à Genève, Décembre 2011, N°10. http://ge.ch/dares/les-couts-de-la-sante-a-geneve/couts_sante_aujourd_hui_geneve-899.html. Published 2011. Accessed April 26, 2012.Google Scholar
32. Cosgrove, SE. The relationship between antimicrobial resistance and patient outcomes: mortality, length of hospital stay, and health care costs. Clin Infect Dis 2006;42(suppl 2):S82–S89.Google Scholar
33. da Silva, GJ, Mendonça, N. Association between antimicrobial resistance and virulence in Escherichia coli . Virulence 2012;3:18–28.Google Scholar
34. Harbarth, S, Ferriere, K, Hugonnet, S, Ricou, B, Suter, P, Pittet, D. Epidemiology and prognostic determinants of bloodstream infections in surgical intensive care. Arch Surg 2002;137:1353–1359.Google Scholar
35. Tumbarello, M, Spanu, T, Di Bidino, R, et al. Costs of bloodstream infections caused by Escherichia coli and influence of extended-spectrum-β-lactamase production and inadequate initial antibiotic therapy. Antimicrob Agents Chemother 2010;54:4085–4091.Google Scholar
36. de Kraker, ME, Wolkewitz, M, Davey, PG, et al. Burden of an timicrobial resistance in European hospitals: excess mortality and length of hospital stay associated with bloodstream infections due to Escherichia coli resistant to third-generation cephalosporins. J Antimicrob Chemother 2011;66:398–407.Google Scholar
37. de Kraker, ME, Davey, PG, Grundmann, H. Mortality and hospital stay associated with resistant Staphylococcus aureus and Escherichia coli bacteremia: estimating the burden of antibiotic resistance in Europe. PLoS Med 2011;8:e1001104.Google Scholar
38. Lautenbach, E, Patel, JB, Bilker, WB, Edelstein, PH, Fishman, NO. Extended-spectrum β-lactamase-producing Escherichia coli and Klebsiella pneumoniae, risk factors for infection and impact of resistance on outcomes. Clin Infect Dis 2001;32:1162–1171.Google Scholar
39. Blot, S, Vandewoude, K, De Bacquer, D, Colardyn, F. Nosocomial bacteremia caused by antibiotic-resistant gram-negative bacteria in critically ill patients: clinical outcome and length of hospitalization. Clin Infect Dis 2002;34:1600–1606.Google Scholar
40. Yang, YS, Ku, CH, Lin, JC, et al. Impact of extended-spectrum β-lactamase-producing Escherichia coli and Klebsiella pneumoniae on the outcome of community-onset bacteremic urinary tract infections. J Microbiol Immunol Infect 2010;43:194–199.Google Scholar