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Gold Standard Evaluation of an Automatic HAIs Surveillance System
dc.contributor.author | Villamarin Bello , María Beatriz | |
dc.contributor.author | URIEL LATORRE, BERTA MARIA | |
dc.contributor.author | Fdez-Riverola, F. | |
dc.contributor.author | SANDE MEIJIDE, MARIA | |
dc.contributor.author | Glez-Pena, D. | |
dc.date.accessioned | 2022-01-27T10:40:39Z | |
dc.date.available | 2022-01-27T10:40:39Z | |
dc.date.issued | 2019 | |
dc.identifier.issn | 2314-6133 | |
dc.identifier.other | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6778878/pdf/BMRI2019-1049575.pdf | es |
dc.identifier.uri | http://hdl.handle.net/20.500.11940/15965 | |
dc.description.abstract | 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%). | en |
dc.language.iso | eng | es |
dc.rights | Atribución 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject.mesh | Population Surveillance | * |
dc.subject.mesh | Health Information Systems | * |
dc.subject.mesh | Humans | * |
dc.subject.mesh | Data Collection | * |
dc.subject.mesh | Reference Standards | * |
dc.subject.mesh | Sensitivity and Specificity | * |
dc.subject.mesh | Cross Infection | * |
dc.subject.mesh | Electronic Health Records | * |
dc.title | Gold Standard Evaluation of an Automatic HAIs Surveillance System | en |
dc.type | Artigo | es |
dc.identifier.doi | 10.1155/2019/1049575 | |
dc.identifier.pmid | 31662963 | |
dc.identifier.sophos | 32706 | |
dc.issue.number | - | es |
dc.journal.title | BioMed research international | es |
dc.organization | Servizo Galego de Saúde::Estrutura de Xestión Integrada (EOXI)::EOXI de Ourense, Verín e O Barco de Valdeorras - Complexo Hospitalario Universitario de Ourense | es |
dc.page.initial | 1049575 | es |
dc.rights.accessRights | openAccess | es |
dc.subject.decs | sistemas de información sanitaria | * |
dc.subject.decs | estándares de referencia | * |
dc.subject.decs | infección hospitalaria | * |
dc.subject.decs | sensibilidad y especificidad | * |
dc.subject.decs | historias clínicas electrónicas | * |
dc.subject.decs | humanos | * |
dc.subject.decs | recopilación de datos | * |
dc.subject.decs | vigilancia de la población | * |
dc.subject.keyword | CHUO | es |
dc.typefides | Artículo Original | es |
dc.typesophos | Artículo Original | es |
dc.volume.number | 2019 | es |
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