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Understanding Unassisted Falls: Effects of Nurse Staffing Level and Nursing Staff Characteristics

Staggs, Vincent S. PhD; Knight, Jeff E. MPH, BSN; Dunton, Nancy PhD

doi: 10.1097/NCQ.0b013e318241da2d
Articles

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.

Department of Biostatistics (Dr Staggs) and School of Nursing (Mr Knight and Dr Dunton), University of Kansas Medical Center, Kansas City.

Correspondence: Vincent S. Staggs, PhD, 3901 Rainbow Blvd (MS 3060), Kansas City, KS 66160 (vstaggs@kumc.edu).

Funding for this work was provided by the American Nurses Association.

The authors declare no conflict of interest.

Accepted for publication: November 14, 2011.

Published online before print: December 19, 2011.

© 2012 Lippincott Williams & Wilkins, Inc.