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
BackgroundFalls 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 manual...
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Main Authors: | Dolci, Elisa (Author), Schärer, Barbara (Author), Grossmann, Nicole (Author), Musy, Sarah Naima (Author), Zúñiga, Franziska (Author), Bachnick, Stefanie (Author), Simon, Michael (Author) |
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Format: | Book |
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JMIR Publications,
2020-09-01T00:00:00Z.
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Online Access: | Connect to this object online. |
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