RT Journal Article
T1 Gold standard evaluation of an automatic HAIs surveillance system
A1 Villamarín Bello, Beatriz
A1 Uriel Latorre, Berta
A1 Fernández Riverola, Florentino
A1 Sande Meijide, María
A1 González Peña, Daniel
K1 3201.03 Microbiología Clínica
K1 1203.20 Sistemas de Control Medico
K1 3205.05 Enfermedades Infecciosas
AB Hospital-acquired Infections (HAIs) surveillance, defined as the systematic collection of data related to a certain health event, is considered an essential dimension for a prevention HAI program to be effective. In recent years, new automated HAI surveillance methods have emerged with the wide adoption of electronic health records (EHR). Here we present the validation results against the gold standard of HAIs diagnosis of the InNoCBR system deployed in the Ourense University Hospital Complex (Spain). Acting as a totally autonomous system, InNoCBR achieves a HAI sensitivity of 70.83% and a specificity of 97.76%, with a positive predictive value of 77.24%. The kappa index for infection type classification is 0.67. Sensitivity varies depending on infection type, where bloodstream infection attains the best value (93.33%), whereas the respiratory infection could be improved the most (53.33%). Working as a semi-automatic system, InNoCBR reaches a high level of sensitivity (81.73%), specificity (99.47%), and a meritorious positive predictive value (94.33%).
PB BioMed Research International
SN 23146133
YR 2019
FD 2019-09-23
LK http://hdl.handle.net/11093/4244
UL http://hdl.handle.net/11093/4244
LA eng
NO BioMed Research International, 2019, 1049575 (2019)
NO Xunta de Galicia | Ref. ED431C2018/55-GRC
DS Investigo
RD 08-sep-2024