Interruption management in the intensive care unit: Predicting resumption times and assessing distributed support

Area of Science:

• Cognitive psychology
• Human factors engineering
• Nursing research

Background:

• Interruptions are common in healthcare, but often studied without theoretical grounding.
• Laboratory studies on interruptions lack real-world applicability in complex settings like intensive care units (ICUs).

Purpose of the Study:

• To investigate how interruption properties affect nurses' resumption times of critical care tasks.
• To apply memory for goals and prospective memory theories to understand interruption impacts.
• To develop a model explaining nurses' behaviors in managing interrupted tasks.

Main Methods:

• Utilized a mobile eye tracker in an ICU setting.
• Employed multiple regression models to predict task resumption times.
• Analyzed interruption duration and physical location changes as key variables.

Main Results:

• Analyzable resumption lags occurred in 55.8% of interruptions, with longer durations and location changes significantly increasing lag time (adjusted R²=30.9%).
• Nurses employed behavioral strategies in 37.6% of interruptions, effectively minimizing or eliminating resumption demands.
• A descriptive model was developed to illustrate how nurse behaviors influence cognitive load during task resumption.

Conclusions:

• Interruption length and spatial displacement are critical factors prolonging nurses' task resumption in ICUs.
• Nurses' adaptive behaviors can significantly reduce the cognitive burden associated with interruptions.
• Findings offer insights for mitigating the disruptive effects of interruptions in critical care environments.