The impact of understaffed shifts on nurse-sensitive outcomes

J Adv Nurs. 2015 Jul;71(7):1564-72. doi: 10.1111/jan.12616. Epub 2015 Jan 9.

Abstract

Aim: To explore the relationship between exposure to understaffed shifts and nurse-sensitive outcomes at the patient level.

Background: Nurse-sensitive outcomes are adverse patient outcomes that can be used as indicators of the quality of nursing care.

Design: This study was conducted in 2014 and was a secondary analysis of administrative data from a large acute care hospital in Western Australia. The sample included 36,529 patient admissions over a two-year period from October 2004-November 2006.

Methods: An understaffed indicator variable was created from nurse staffing data and used to examine patient data to create a variable indicating the total number of understaffed shifts each patient had been exposed to during their hospital stay. Logistic regression was used to determine the odds of acquiring a nurse-sensitive outcome for those exposed to understaffed shifts.

Results: The prevalence ratio showed that for each of the nurse-sensitive outcomes there was an increase in prevalence for those who were exposed to an understaffed shift, with all ratios being greater than one. After adjusting for patient characteristics, nurse-sensitive outcomes found to have the understaffed variable significant in the logistic regression model were surgical wound infection, urinary tract infection, pressure injury, pneumonia, deep vein thrombosis, upper gastrointestinal bleed, sepsis and physiological metabolic derangement. All odds ratios were small effects.

Conclusion: Preventing understaffing is a consideration for improving the quality of care for patients. Attributing the understaffing variable at the patient level enables exposure to be captured across ward changes increasing the sensitivity with which this variable can be measured.

Keywords: acute care; nurse staffing; nurse-sensitive outcomes; nurses; patient outcomes; quality of care.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Humans
  • Length of Stay
  • Middle Aged
  • Nurse-Patient Relations
  • Nursing Staff, Hospital*
  • Personnel Staffing and Scheduling*
  • Western Australia