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Healthcare-associated bloodstream infection trends under a provincial surveillance program

Published online by Cambridge University Press:  19 March 2019

Iman Fakih
Affiliation:
Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, Canada
Élise Fortin
Affiliation:
Direction des risques biologiques et de la santé au travail, Institut national de santé publique du Québec, Québec, Canada Department of Microbiology, Infectious Diseases and Immunology, Faculty of Medicine, University of Montreal, Montreal, Québec, Canada
Marc-André Smith
Affiliation:
CIUSSS du Nord-de-l’Île-de-Montréal, Montreal, Québec, Canada
Alex Carignan
Affiliation:
Department of Microbiology and Infectious Diseases, Sherbrooke University, Sherbrooke, Québec, Canada
Claude Tremblay
Affiliation:
CHU de Québec, Québec City, Québec, Canada
Jasmin Villeneuve
Affiliation:
Direction des risques biologiques et de la santé au travail, Institut national de santé publique du Québec, Québec, Canada
Danielle Moisan
Affiliation:
CISSS du Bas-Saint-Laurent, Québec, Canada
Charles Frenette
Affiliation:
Department of Medical Microbiology, McGill University Health Centre, Montreal, Québec, Canada
Caroline Quach
Affiliation:
Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, Canada Direction des risques biologiques et de la santé au travail, Institut national de santé publique du Québec, Québec, Canada Department of Microbiology, Infectious Diseases and Immunology, Faculty of Medicine, University of Montreal, Montreal, Québec, Canada Division of Pediatric Infectious Diseases and Medical Microbiology, CHU Sainte-Justine, Montreal, Québec, Canada
Alexandra M. Schmidt*
Affiliation:
Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, Canada
for SPIN-BACTOT
Affiliation:
Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, Canada Direction des risques biologiques et de la santé au travail, Institut national de santé publique du Québec, Québec, Canada Department of Microbiology, Infectious Diseases and Immunology, Faculty of Medicine, University of Montreal, Montreal, Québec, Canada CIUSSS du Nord-de-l’Île-de-Montréal, Montreal, Québec, Canada Department of Microbiology and Infectious Diseases, Sherbrooke University, Sherbrooke, Québec, Canada CHU de Québec, Québec City, Québec, Canada CISSS du Bas-Saint-Laurent, Québec, Canada Department of Medical Microbiology, McGill University Health Centre, Montreal, Québec, Canada Division of Pediatric Infectious Diseases and Medical Microbiology, CHU Sainte-Justine, Montreal, Québec, Canada
*
Author for correspondence: Alexandra M. Schmidt, Email: alexandra.schmidt@mcgill.ca

Abstract

Objective:

BACTOT, Quebec’s healthcare-associated bloodstream infection (HABSI) surveillance program has been operating since 2007. In this study, we evaluated the changes in HABSI rates across 10 years of BACTOT surveillance under a Bayesian framework.

Design:

A retrospective, cohort study of eligible hospitals having participated in BACTOT for at least 3 years, regardless of their entry date. Multilevel Poisson regressions were fitted independently for cases of HABSI, catheter-associated bloodstream infections (CA-BSIs), non–catheter-associated primary BSIs (NCA-BSIs), and BSIs secondary to urinary tract infections (BSI-UTIs) as the outcome and log of patient days as the offset. The log of the mean Poisson rate was decomposed as the sum of a surveillance year effect, period effect, and hospital effect. The main estimate of interest was the cohort-level rate in years 2–10 of surveillance relative to year 1.

Results:

Overall, 17,479 cases and 33,029,870 patient days were recorded for the cohort of 77 hospitals. The pooled 10-year HABSI rate was 5.20 per 10,000 patient days (95% CI, 5.12–5.28). For HABSI, CA-BSI, and BSI-UTI, there was no difference between the estimated posterior rates of years 2–10 compared to year 1. The posterior means of the NCA-BSI rate ratios increased from the seventh year until the tenth year, when the rate was 29% (95% confidence interval, 1%–89%) higher than the first year rate.

Conclusions:

HABSI rates and those of the most frequent subtypes remained stable over the surveillance period. To achieve reductions in incidence, we recommend that more effort be expended in active interventions against HABSI alongside surveillance.

Type
Original Article
Copyright
© 2019 by The Society for Healthcare Epidemiology of America. All rights reserved. 

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References

Gastmeier, P, Geffers, C, Brandt, C, et al. Effectiveness of a nationwide nosocomial infection surveillance system for reducing nosocomial infections. J Hosp Infect 2006;64:1622.CrossRefGoogle ScholarPubMed
Schwab, F, Gastmeier, P, Piening, B, Geffers, C. The step from a voluntary to a mandatory national nosocomial infection surveillance system: the influence on infection rates and surveillence effect. Antimicrob Resist Infect Control 2012;1:24.CrossRefGoogle Scholar
Haley, RW, Culver, DH, White, JW, et al. The efficacy of infection surveillance and control programs in preventing nosocomial infections in US hospitals. Am J Epidemiol 1985;121:182205.CrossRefGoogle ScholarPubMed
Zuschneid, I, Schwab, F, Geffers, C, Ruden, H, Gastmeier, P. Reducing central venous catheter-associated primary bloodstream infections in intensive care units is possible: data from the German nosocomial infection surveillance system. Infect Control Hosp Epidemiol 2003;24:501505.CrossRefGoogle ScholarPubMed
Zuschneid, I, Schwab, F, Geffers, C, Behnke, M, Ruden, H, Gastmeier, P. Trends in ventilator-associated pneumonia rates within the German nosocomial infection surveillance system (KISS). Infect Control Hosp Epidemiol 2007;28:314318.CrossRefGoogle Scholar
Gastmeier, P, Schwab, F, Sohr, D, Behnke, M, Geffers, C. Reproducibility of the surveillance effect to decrease nosocomial infection rates. Infect Control Hosp Epidemiol 2009;30:993999.CrossRefGoogle ScholarPubMed
Kanamori, H, Weber, DJ, DiBiase, LM, et al. Longitudinal trends in all healthcare-associated infections through comprehensive hospital-wide surveillance and infection control measures over the past 12 years: substantial burden of healthcare-associated infections outside of intensive care units and “other” types of infection. Infect Control Hosp Epidemiol 2015;36:11391147.CrossRefGoogle Scholar
Meyer, E, Schroder, C, Gastmeier, P, Geffers, C. The reduction of nosocomial MRSA infection in Germany: an analysis of data from the hospital infection surveillance system (KISS) between 2007 and 2012. Dtsch Arztebl Int 2014;111:331336.Google ScholarPubMed
Blanchard, AC, Fortin, E, Rocher, I, et al. Central line-associated bloodstream infection in neonatal intensive care units. Infect Control Hosp Epidemiol 2013;34:11671173.CrossRefGoogle ScholarPubMed
Gastmeier, P, Sohr, D, Schwab, F, et al. Ten years of KISS: the most important requirements for success. J Hosp Infect 2008;70:1116.CrossRefGoogle Scholar
Zingg, W, Sax, H, Inan, C, et al. Hospital-wide surveillance of catheter-related bloodstream infection: from the expected to the unexpected. J Hosp Infect 2009;73:4146.CrossRefGoogle ScholarPubMed
Schwab, F, Geffers, C, Barwolff, S, Ruden, H, Gastmeier, P. Reducing neonatal nosocomial bloodstream infections through participation in a national surveillance system. J Hosp Infect 2007;65:319325.CrossRefGoogle Scholar
Civitarese, AM, Ruggieri, E, Walz, JM, et al. A 10-year review of total hospital-onset ICU bloodstream infections at an academic medical center. Chest 2017;151:10111017.CrossRefGoogle ScholarPubMed
Valles, J, Calbo, E, Anoro, E, et al. Bloodstream infections in adults: importance of healthcare-associated infections. J Infect 2008;56:2734.CrossRefGoogle ScholarPubMed
Suljagic, V, Cobeljic, M, Jankovic, S, et al. Nosocomial bloodstream infections in ICU and non-ICU patients. Am J Infect Control 2005;33:333340.CrossRefGoogle ScholarPubMed
SPIN-BACTOT. Résultats de surveillance 2016–2017. Québec: Institut national de santé publique du Québec (INSPQ); 2017.Google Scholar
Vrijens, F, Hulstaert, F, Van de Sande, S, Devriese, S, Morales, I, Parmentier, Y. Hospital-acquired, laboratory-confirmed bloodstream infections: linking national surveillance data to clinical and financial hospital data to estimate increased length of stay and healthcare costs. J Hosp Infect 2010;75:158162.CrossRefGoogle ScholarPubMed
Ronveaux, O, Jans, B, Suetens, C, Carsauw, H. Epidemiology of nosocomial bloodstream infections in Belgium, 1992–1996. Eur J Clin Microbiol Infect Dis 1998;17:695700.CrossRefGoogle Scholar
Lyytikainen, O, Lumio, J, Sarkkinen, H, Kolho, E, Kostiala, A, Ruutu, P. Nosocomial bloodstream infections in Finnish hospitals during 1999–2000. Clin Infect Dis 2002;35:e14e19.CrossRefGoogle ScholarPubMed
Kontula, KSK, Skogberg, K, Ollgren, J, Jarvinen, A, Lyytikainen, O. The outcome and timing of death of 17, 767 nosocomial bloodstream infections in acute care hospitals in Finland during 1999–2014. Eur J Clin Microbiol Infect Dis 2018;37:945952.CrossRefGoogle ScholarPubMed
Si, D, Runnegar, N, Marquess, J, Rajmokan, M, Playford, EG. Characterising health care-associated bloodstream infections in public hospitals in Queensland, 2008–2012. Med J Austral 2016;204:276.CrossRefGoogle Scholar
Cope, C, Wilkinson, I, Infection Control Service, Communicable Disease Control Branch, SA Department for Health and Ageing. South Australian healthcare-associated infection surveillance program: bloodstream infection annual report, 2016. Adelaide: Department for Health and Ageing, Government of South Australia; 2017.Google Scholar
Fortin, E, Rocher, I, Frenette, C, Tremblay, C, Quach, C. Healthcare-associated bloodstream infections secondary to a urinary focus: the Quebec provincial surveillance results. Infect Control Hosp Epidemiol 2012;33:456462.CrossRefGoogle ScholarPubMed
Fakih, I, Fortin, E, Smith, MA, et al. A ten-year review of healthcare-associated bloodstream infections from forty hospitals in Quebec, Canada. Infect Control Hosp Epidemiol 2018;39:12021209.CrossRefGoogle ScholarPubMed
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;36:309332.CrossRefGoogle ScholarPubMed
Gamerman, D, Lopes, HF. Markov Chain Monte Carlo: Stochastic simulation for Bayesian Inference. New York: Chapman & Hall; 2006.Google Scholar
Depaoli, S, Clifton, JP, Cobb, PR. Just another Gibbs sampler (JAGS). J Educ Behav Stat 2016;41:628649.CrossRefGoogle Scholar
Plummer, M. rjags: Bayesian Graphical Models using MCMC. R package version 4–6. 2016. https://CRAN.R-project.org/package=rjags.Google Scholar
Gelman, A, Rubin, DB. Inference from iterative simulation using multiple sequences. Stat Sci 1992;7:457511.CrossRefGoogle Scholar
Al-Hasan, MN, Lahr, BD, Eckel-Passow, JE, Baddour, LM. Seasonal variation in Escherichia coli bloodstream infection: a population-based study. Clin Microbiol Infect 2009;15:947950.CrossRefGoogle ScholarPubMed
Chazan, B, Colodner, R, Edelstein, H, Raz, R. Seasonal variation in Escherichia coli bloodstream infections in northern Israel. Clin Microbiol Infect 2011;17:851854.CrossRefGoogle ScholarPubMed
Freeman, JT, Anderson, DJ, Sexton, DJ. Seasonal peaks in Escherichia coli infections: possible explanations and implications. Clin Microbiol Infect 2009;15:951953.CrossRefGoogle ScholarPubMed
Spiegelhalter, DJ, Best, NG, Carlin, BJ, van der Linde, A. Bayesian measures of model complexity and fit. J Roy Stat Soc B 2002;64:583639.CrossRefGoogle Scholar
Australian Institute of Health and Welfare. Admitted patient care 2016–2017: Australian hospital statistics. Health Services Series. Canberra: AIHW; 2017.Google Scholar
Li, L, Fortin, E, Tremblay, C, Ngenda-Muadi, M, Quach, C. Central-line-associated bloodstream infections in Quebec intensive care units: results from the provincial healthcare-associated infections surveillance program (SPIN). Infect Control Hosp Epidemiol 2016;37:11861194.CrossRefGoogle Scholar
SPIN-HD. Résultats de surveillance 2016–2017. Québec: Institut national de santé publique du Québec (INSPQ); 2017.Google Scholar
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