Variations in Identification of Healthcare-Associated Infections
Published Date:May 21 2013
Source:Infect Control Hosp Epidemiol. 2013; 34(7):678-686.
Pubmed Central ID:PMC3981741
Funding:K24 AI080942/AI/NIAID NIH HHS/United States
K24 AI080942/AI/NIAID NIH HHS/United States
KM1 400-4239-4-555854-XXXX-2446-2192/PHS HHS/United States
U54-CK000163/CK/NCEZID CDC HHS/United States
Little is known about whether those performing healthcare-associated infection (HAI) surveillance vary in their interpretations of HAI definitions developed by the Centers for Disease Control and Prevention’s National Healthcare Safety Network (NHSN). Our primary objective was to characterize variations in these interpretations using clinical vignettes. We also describe predictors of variation in responses.
A sample of US-based members of the Society for Healthcare Epidemiology of America (SHEA) Research Network.
Respondents assessed whether each of 6 clinical vignettes met criteria for an NHSN-defined HAI. Individual- and institutional-level data were also gathered.
Surveys were distributed to 143 SHEA Research Network members from 126 hospitals. In total, 113 responses were obtained, representing at least 61 unique hospitals (30 respondents did not identify a hospital); 79.2% (84 of 106 nonmissing responses) were infection preventionists, and 79.4% (81 of 102 nonmissing responses) worked at academic hospitals. Among the 6 vignettes, the proportion of respondents correctly characterizing the vignettes was as low as 27.3%. Combining all 6 vignettes, the mean percentage of correct responses was 61.1% (95% confidence interval, 57.7%–63.8%). Percentage of correct responses was associated with presence of a clinical background (ie, nursing or physician degrees) but not with hospital size or infection prevention and control department characteristics.
Substantial heterogeneity exists in the application of HAI definitions in this survey of infection preventionists and hospital epidemiologists. Our data suggest a need to better clarify these definitions, especially when comparing HAI rates across institutions.
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