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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Detaylı Bibliyografya
Yayımlandı:BMC Health Serv Res
Asıl Yazarlar: 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
Materyal Türü: Artigo
Dil:Inglês
Baskı/Yayın Bilgisi: BioMed Central 2017
Konular:
Study Protocol
Online Erişim: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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