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Design and Analysis for Fall Detection System Simplification
Published on: April 6, 2020
Understanding unassisted falls: effects of nurse staffing level and nursing staff characteristics
Vincent S Staggs1, Jeff E Knight, Nancy Dunton
1Department of Biostatistics, University of Kansas Medical Center, Kansas City, KS 66160, USA. vstaggs@kumc.edu
Hierarchical Poisson modeling was used to explore hospital and nursing unit characteristics as predictors of the unassisted fall rate. Longitudinal data were collected from 1502 units in 248 US hospitals. The relation between the fall rate and total nurse staffing was positive at lower staffing levels and negative for levels around and above the median. The fall rate was negatively associated with registered nurse skill mix and average registered nurse tenure on the unit.
Hierarchical Poisson modeling was used to explore hospital and nursing unit characteristics as predictors of the unassisted fall rate. Longitudinal data were collected from 1502 units in 248 US hospitals. The relation between the fall rate and total nurse staffing was positive at lower staffing levels and negative for levels around and above the median. The fall rate was negatively associated with registered nurse skill mix and average registered nurse tenure on the unit.
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