Predicting out of intensive care unit cardiopulmonary arrest or death using electronic medical record data

BACKGROUND: Accurate, timely and automated identification of patients at high risk for severe clinical deterioration using readily available clinical information in the electronic medical record (EMR) could inform health systems to target scarce resources and save lives. METHODS: We identified 7,466...

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Detalles Bibliográficos
Autores principales: Alvarez, Carlos A, Clark, Christopher A, Zhang, Song, Halm, Ethan A, Shannon, John J, Girod, Carlos E, Cooper, Lauren, Amarasingham, Ruben
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3599266/
https://www.ncbi.nlm.nih.gov/pubmed/23442316
http://dx.doi.org/10.1186/1472-6947-13-28

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3599266/
https://www.ncbi.nlm.nih.gov/pubmed/23442316
http://dx.doi.org/10.1186/1472-6947-13-28

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