Clinical decisions and time since rest break: An analysis of decision fatigue in nurses

Health Psychol. 2019 Apr;38(4):318-324. doi: 10.1037/hea0000725.

Abstract

Objective: The present study investigates whether nurses working for a national medical telephone helpline show evidence of "decision fatigue," as measured by a shift from effortful to easier and more conservative decisions as the time since their last rest break increases.

Method: In an observational, repeated-measures study, data from approximately 4,000 calls to 150 nurses working for the Scottish NHS 24 medical helpline (37% of the national workforce) were modeled to determine whether the likelihood of a nurse's decision to refer a patient to another health professional the same day (the clinically safest but most conservative and resource inefficient decision) varied according to the number of calls taken/time elapsed since a nurse's last rest break and/or since the start of shift. Analyses used mixed-effect logistic regression.

Results: For every consecutive call taken since last rest break, the odds of nurses making a conservative management decision (i.e., arranging for callers to see another health professional the same day) increased by 5.5% (p = .001, 95% confidence interval [CI: 2.2, 8.8]), an increase in odds of 20.5% per work hour (p < .001, 95% CI [9.1, 33.2]) or 49.0% (on average) from immediately after 1 break to immediately before the next. Decision-making was not significantly related to general or cumulative workload (calls or time elapsed since start of shift).

Conclusions: Every consecutive decision that nurses make since their last break produces a predictable shift toward more conservative, and less resource-efficient, decisions. Theoretical models of cognitive fatigue can elucidate how and why this shift occurs, helping to identify potentially modifiable determinants of patient care. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

MeSH terms

  • Adult
  • Decision Making / ethics*
  • Fatigue / diagnosis*
  • Female
  • Humans
  • Male
  • Nurses