Establishing the prevalence of healthcare-associated infections in Australian hospitals

protocol for the Comprehensive Healthcare Associated Infection National Surveillance (CHAINS) study

Philip L. Russo, Andrew Stewardson, Allen C. Cheng, Tracey Bucknall, Kalisvar Marimuthu, Brett G. Mitchell

Research output: Contribution to journalArticleOtherpeer-review

Abstract

INTRODUCTION: A healthcare-associated infection (HAI) data point prevalence study (PPS) conducted in 1984 in Australian hospitals estimated the prevalence of HAI to be 6.3%. Since this time, there have been no further national estimates undertaken. In the absence of a coordinated national surveillance programme or regular PPS, there is a dearth of national HAI data to inform policy and practice priorities. METHODS AND ANALYSIS: A national HAI PPS study will be undertaken based on the European Centres for Disease Control method. Nineteen public acute hospitals will participate. A standardised algorithm will be used to detect HAIs in a two-stage cluster design, random sample of adult inpatients in acute wards and all intensive care unit patients. Data from each hospital will be collected by two trained members of the research team. We will estimate the prevalence of HAIs, invasive device use, single room placement and deployment of transmission-based precautions. ETHICS AND DISSEMINATION: Ethics approval was obtained from the Alfred Health Human Research Ethics Committee (HREC/17/Alfred/203) via the National Mutual Assessment. A separate approval was obtained from the Tasmanian Health and Medical Human Research Committee (H0016978) for participating Tasmanian hospitals. Findings will be disseminated in individualised participating hospital reports, peer-reviewed publications and conference presentations.

Original languageEnglish
Article numbere024924
Number of pages7
JournalBMJ Open
Volume8
Issue number11
DOIs
Publication statusPublished - 8 Nov 2018

Keywords

  • healthcare associated infection
  • infection control
  • infection prevention
  • point prevalence surveillance

Cite this

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title = "Establishing the prevalence of healthcare-associated infections in Australian hospitals: protocol for the Comprehensive Healthcare Associated Infection National Surveillance (CHAINS) study",
abstract = "INTRODUCTION: A healthcare-associated infection (HAI) data point prevalence study (PPS) conducted in 1984 in Australian hospitals estimated the prevalence of HAI to be 6.3{\%}. Since this time, there have been no further national estimates undertaken. In the absence of a coordinated national surveillance programme or regular PPS, there is a dearth of national HAI data to inform policy and practice priorities. METHODS AND ANALYSIS: A national HAI PPS study will be undertaken based on the European Centres for Disease Control method. Nineteen public acute hospitals will participate. A standardised algorithm will be used to detect HAIs in a two-stage cluster design, random sample of adult inpatients in acute wards and all intensive care unit patients. Data from each hospital will be collected by two trained members of the research team. We will estimate the prevalence of HAIs, invasive device use, single room placement and deployment of transmission-based precautions. ETHICS AND DISSEMINATION: Ethics approval was obtained from the Alfred Health Human Research Ethics Committee (HREC/17/Alfred/203) via the National Mutual Assessment. A separate approval was obtained from the Tasmanian Health and Medical Human Research Committee (H0016978) for participating Tasmanian hospitals. Findings will be disseminated in individualised participating hospital reports, peer-reviewed publications and conference presentations.",
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Establishing the prevalence of healthcare-associated infections in Australian hospitals : protocol for the Comprehensive Healthcare Associated Infection National Surveillance (CHAINS) study. / Russo, Philip L.; Stewardson, Andrew; Cheng, Allen C.; Bucknall, Tracey; Marimuthu, Kalisvar; Mitchell, Brett G.

In: BMJ Open, Vol. 8, No. 11, e024924, 08.11.2018.

Research output: Contribution to journalArticleOtherpeer-review

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