Identification of important factors in an inpatient fall risk prediction model to improve the quality of care using EHR and electronic administrative data: A machine-learning approach

BACKGROUND: Inpatient falls, many resulting in injury or death, are a serious problem in hospital settings. Existing falls risk assessment tools, such as the Morse Fall Scale, give a risk score based on a set of factors, but don’t necessarily signal which factors are most important for predicting fa...

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Detalles Bibliográficos
Autores principales: Lindberg, David S., Prosperi, Mattia, Bjarnadottir, Ragnhildur I., Thomas, Jaime, Crane, Marsha, Chen, Zhaoyi, Shear, Kristen, Solberg, Laurence M., Snigurska, Urszula Alina, Wu, Yonghui, Xia, Yunpeng, Lucero, Robert J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8562928/
https://www.ncbi.nlm.nih.gov/pubmed/32980667
http://dx.doi.org/10.1016/j.ijmedinf.2020.104272

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8562928/
https://www.ncbi.nlm.nih.gov/pubmed/32980667
http://dx.doi.org/10.1016/j.ijmedinf.2020.104272

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