Accuracy and generalizability of using automated methods for identifying adverse events from electronic health record data: a validation study protocol

BACKGROUND: Adverse events (AEs) in acute care hospitals are frequent and associated with significant morbidity, mortality, and costs. Measuring AEs is necessary for quality improvement and benchmarking purposes, but current detection methods lack in accuracy, efficiency, and generalizability. The g...

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Publicado en:BMC Health Serv Res
Autores principales: Rochefort, Christian M., Buckeridge, David L., Tanguay, Andréanne, Biron, Alain, D’Aragon, Frédérick, Wang, Shengrui, Gallix, Benoit, Valiquette, Louis, Audet, Li-Anne, Lee, Todd C., Jayaraman, Dev, Petrucci, Bruno, Lefebvre, Patricia
Formato: Artigo
Lenguaje:Inglês
Publicado: BioMed Central 2017
Materias:
Study Protocol
Acceso en línea:https://ncbi.nlm.nih.gov/pmc/articles/PMC5314632/
https://ncbi.nlm.nih.gov/pubmed/28209197
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12913-017-2069-7
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