Associations between rates of unassisted inpatient falls and levels of registered and non-registered nurse staffing

Int J Qual Health Care. 2014 Feb;26(1):87-92. doi: 10.1093/intqhc/mzt080. Epub 2013 Nov 13.


Objective: To enhance understanding of how nurse staffing relates to unassisted falls by exploring non-linear associations between unassisted fall rates and levels of registered nurse (RN) and non-RN staffing on 5 nursing unit types, thereby enabling managers to improve patient safety by making better-informed decisions about staffing.

Design: Cross-sectional analysis of routinely collected data using hierarchical negative binomial regression.

Setting: 8069 nursing units in 1361 U.S. hospitals participating in the National Database of Nursing Quality Indicators(®). Main outcome measure Rate of unassisted falls per inpatient day.

Results: Associations between unassisted fall rates and nurse staffing varied by unit type. For medical-surgical units, higher RN staffing was weakly associated with lower fall rates. On step-down and medical units, the association between RN staffing and fall rates depended on the level of staffing: At lower staffing levels, the fall rate increased as staffing increased, but at moderate and high staffing levels, the fall rate decreased as staffing increased. Higher levels of non-RN staffing were generally associated with higher fall rates..

Conclusions: Increasing non-RN staffing seems ineffective at preventing unassisted falls. Increasing RN staffing may be effective, depending on the unit type and the current level of staffing.

Keywords: accidental falls; nursing personnel; patient safety; personnel staffing and scheduling.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accidental Falls / statistics & numerical data*
  • Cross-Sectional Studies
  • Hospitals / standards
  • Hospitals / statistics & numerical data
  • Humans
  • Nursing Staff, Hospital / standards
  • Nursing Staff, Hospital / statistics & numerical data*
  • Quality Indicators, Health Care / statistics & numerical data
  • United States / epidemiology
  • Workforce