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Gaudart J, Cloutman-Green E, Guillas S, et al. Healthcare environments and spatial variability of healthcare associated infection risk: cross-sectional surveys. PLoS One. 2013;8(9):e76249doi: 10.1371/journal.pone.0076249.
Gaudart, J., Cloutman-Green, E., Guillas, S., D'Arcy, N., Hartley, J. C., Gant, V., & Klein, N. (2013). Healthcare environments and spatial variability of healthcare associated infection risk: cross-sectional surveys. PloS one, 8(9), e76249. https://doi.org/10.1371/journal.pone.0076249
Gaudart, Jean, et al. "Healthcare environments and spatial variability of healthcare associated infection risk: cross-sectional surveys." PloS one vol. 8,9 (2013): e76249. doi: https://doi.org/10.1371/journal.pone.0076249
Gaudart J, Cloutman-Green E, Guillas S, D'Arcy N, Hartley JC, Gant V, Klein N. Healthcare environments and spatial variability of healthcare associated infection risk: cross-sectional surveys. PLoS One. 2013 Sep 19;8(9):e76249. doi: 10.1371/journal.pone.0076249. eCollection 2013. PMID: 24069459; PMCID: PMC3777895.
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PLoS One. 2013 Sep 19;8(9):e76249. doi: 10.1371/journal.pone.0076249. eCollection 2013.

Healthcare environments and spatial variability of healthcare associated infection risk: cross-sectional surveys.

PloS one

Jean Gaudart, Elaine Cloutman-Green, Serge Guillas, Nikki D'Arcy, John C Hartley, Vanya Gant, Nigel Klein

Affiliations

  1. Aix-Marseille Univ, UMR912 SESSTIM (AMU, INSERM, IRD), Marseille, France ; University College, London, Department of Statistical Science, London, United Kingdom.

PMID: 24069459 PMCID: PMC3777895 DOI: 10.1371/journal.pone.0076249

Abstract

Prevalence of healthcare associated infections remains high in patients in intensive care units (ICU), estimated at 23.4% in 2011. It is important to reduce the overall risk while minimizing the cost and disruption to service provision by targeted infection control interventions. The aim of this study was to develop a monitoring tool to analyze the spatial variability of bacteriological contamination within the healthcare environment to assist in the planning of interventions. Within three cross-sectional surveys, in two ICU wards, air and surface samples from different heights and locations were analyzed. Surface sampling was carried out with tryptic Soy Agar contact plates and Total Viable Counts (TVC) were calculated at 48 hrs (incubation at 37 °C). TVCs were analyzed using Poisson Generalized Additive Mixed Model for surface type analysis, and for spatial analysis. Through three cross-sectional survey, 370 samples were collected. Contamination varied from place-to-place, height-to-height, and by surface type. Hard-to-reach surfaces, such as bed wheels and floor area under beds, were generally more contaminated, but the height level at which maximal TVCs were found changed between cross-sectional surveys. Bedside locations and bed occupation were risk factors for contamination. Air sampling identified clusters of contamination around the nursing station and surface sampling identified contamination clusters at numerous bed locations. By investigating dynamic hospital wards, the methodology employed in this study will be useful to monitor contamination variability within the healthcare environment and should help to assist in the planning of interventions.

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