Phenotyping for patient safety: algorithm development for electronic health record based automated adverse event and medical error detection in neonatal intensive care

BACKGROUND: Although electronic health records (EHRs) have the potential to provide a foundation for quality and safety algorithms, few studies have measured their impact on automated adverse event (AE) and medical error (ME) detection within the neonatal intensive care unit (NICU) environment. OBJE...

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Detalles Bibliográficos
Autores principales: Li, Qi, Melton, Kristin, Lingren, Todd, Kirkendall, Eric S, Hall, Eric, Zhai, Haijun, Ni, Yizhao, Kaiser, Megan, Stoutenborough, Laura, Solti, Imre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2014
Materias:
Focus on Biomedical Natural Language Processing and Data Modeling
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147599/
https://www.ncbi.nlm.nih.gov/pubmed/24401171
http://dx.doi.org/10.1136/amiajnl-2013-001914

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147599/
https://www.ncbi.nlm.nih.gov/pubmed/24401171
http://dx.doi.org/10.1136/amiajnl-2013-001914

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