title: Differences in identifying healthcare associated infections using clinical vignettes and the influence of respondent characteristics: a cross-sectional survey of Australian infection prevention staff.
abstract: BACKGROUND
  Australia has commenced public reporting and benchmarking of healthcare associated infections (HAIs), despite not having a standardised national HAI surveillance program. Annual hospital Staphylococcus aureus bloodstream (SAB) infection rates are released online, with other HAIs likely to be reported in the future. Although there are known differences between hospitals in Australian HAI surveillance programs, the effect of these differences on reported HAI rates is not known.
  
  
  OBJECTIVE
  To measure the agreement in HAI identification, classification, and calculation of HAI rates, and investigate the influence of differences amongst those undertaking surveillance on these outcomes.
  
  
  METHODS
  A cross-sectional online survey exploring HAI surveillance practices was administered to infection prevention nurses who undertake HAI surveillance. Seven clinical vignettes describing HAI scenarios were included to measure agreement in HAI identification, classification, and calculation of HAI rates. Data on characteristics of respondents was also collected. Three of the vignettes were related to surgical site infection and four to bloodstream infection. Agreement levels for each of the vignettes were calculated. Using the Australian SAB definition, and the National Health and Safety Network definitions for other HAIs, we looked for an association between the proportion of correct answers and the respondents' characteristics.
  
  
  RESULTS
  Ninety-two infection prevention nurses responded to the vignettes. One vignette demonstrated 100 % agreement from responders, whilst agreement for the other vignettes varied from 53 to 75 %. Working in a hospital with more than 400 beds, working in a team, and State or Territory was associated with a correct response for two of the vignettes. Those trained in surveillance were more commonly associated with a correct response, whilst those working part-time were less likely to respond correctly.
  
  
  CONCLUSIONS
  These findings reveal the need for further HAI surveillance support for those working part-time and in smaller facilities. It also confirms the need to improve uniformity of HAI surveillance across Australian hospitals, and raises questions on the validity of the current comparing of national HAI SAB rates.
authors.affiliation: Institute of Health and Biomedical Innovation, School of Public Health and Welfare, Queensland University of Technology, 60 Musk Ave, Kelvin Grove, QLD 4059 Australia ; Griffith University, Brisbane, QLD Australia.
authors.forename: Philip L
authors.initials: PL
authors.lastname: Russo
authors.affiliation: Institute of Health and Biomedical Innovation, School of Public Health and Welfare, Queensland University of Technology, 60 Musk Ave, Kelvin Grove, QLD 4059 Australia.
authors.forename: Adrian G
authors.initials: AG
authors.lastname: Barnett
authors.affiliation: Infectious Diseases Epidemiology Unit, Department of Epidemiology and Preventive Medicine, Monash University, Prahran, 3181 VIC Australia ; Infection Prevention and Healthcare Epidemiology Unit, Alfred Health, Commercial Rd, Prahran, 3181 VIC Australia.
authors.forename: Allen C
authors.initials: AC
authors.lastname: Cheng
authors.affiliation: Faculty of Medicine, Dentistry and Health, University of Melbourne, Grattan St, Parkville, 3010 VIC Australia.
authors.forename: Michael
authors.initials: M
authors.lastname: Richards
authors.affiliation: Institute of Health and Biomedical Innovation, School of Public Health and Welfare, Queensland University of Technology, 60 Musk Ave, Kelvin Grove, QLD 4059 Australia.
authors.forename: Nicholas
authors.initials: N
authors.lastname: Graves
authors.affiliation: Institute of Health and Biomedical Innovation, School of Public Health and Welfare, Queensland University of Technology, 60 Musk Ave, Kelvin Grove, QLD 4059 Australia.
authors.forename: Lisa
authors.initials: L
authors.lastname: Hall
keywords: Clinical vignettes; Data accuracy; Healthcare associated infections; Surveillance