Automated Fall Detection Algorithm With Global Trigger Tool, Incident Reports, Manual Chart Review, and Patient-Reported Falls: Algorithm Development and Validation With a Retrospective Diagnostic Accuracy Study

BACKGROUND: Falls are common adverse events in hospitals, frequently leading to additional health costs due to prolonged stays and extra care. Therefore, reliable fall detection is vital to develop and test fall prevention strategies. However, conventional methods—voluntary incident reports and manu...

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Detalles Bibliográficos
Autores principales: Dolci, Elisa, Schärer, Barbara, Grossmann, Nicole, Musy, Sarah Naima, Zúñiga, Franziska, Bachnick, Stefanie, Simon, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Original Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7536608/
https://www.ncbi.nlm.nih.gov/pubmed/32955445
http://dx.doi.org/10.2196/19516

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7536608/
https://www.ncbi.nlm.nih.gov/pubmed/32955445
http://dx.doi.org/10.2196/19516

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