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...

Descripción completa

Detalles Bibliográficos
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: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Study Protocol
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5314632/
https://www.ncbi.nlm.nih.gov/pubmed/28209197
http://dx.doi.org/10.1186/s12913-017-2069-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5314632/
https://www.ncbi.nlm.nih.gov/pubmed/28209197
http://dx.doi.org/10.1186/s12913-017-2069-7

Ejemplares similares