Cognitive biases and contextual factors explaining variability in nurses' fall risk judgements: a multi-centre...

Area of Science:

• Nursing
• Healthcare Decision Making
• Patient Safety

Background:

• Fall risk assessment is a complex nursing process with unclear reasons for variability.
• Existing research highlights inconsistencies in nurses' fall risk assessments.
• The appropriateness and drivers of this variability remain poorly understood.

Purpose of the Study:

• To investigate how nurses judge patient fall risk.
• To explore associations between cognitive biases, contextual factors, and nurses' fall risk judgments.

Main Methods:

• Online survey with 335 nurses across six hospitals in western Japan.
• Nurses rated fall likelihood in 18 patient scenarios.
• Assessment of cognitive biases (base-rate neglect, belief bias, availability bias) using validated measures.

Main Results:

• Key factors influencing fall risk assessment included patient requests for assistance, sleeping pill use, tubes/drains, and mobility.
• Variability in assessments was associated with nurses' gender, education, clinical specialty, and susceptibility to availability bias.
• Linear mixed-effects regression models identified significant predictors of judgment and variability.

Conclusions:

• While some variability in clinical judgment may reflect personalized care, inconsistencies due to cognitive biases are problematic.
• Healthcare organizations should implement targeted training to improve contextual expertise and mitigate cognitive bias influence.
• Enhancing nurses' ability to reduce cognitive bias impact is crucial for accurate fall risk assessment.