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

Grundgeiger, Tobias; Sanderson, Penelope; MacDougall, Hamish G.; Venkatesh, Balasubramanian · 2010 · OpenAlex-citations

DOI: 10.1037/a0021912

archive: archived pipeline: cataloged verified

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Summary

This study investigates how interruptions affect task resumption in intensive care units (ICUs), addressing a gap between theoretically rich laboratory studies and descriptive field studies in healthcare. The authors aim to determine which interruption properties influence the time nurses take to resume interrupted tasks (resumption lag) and to assess how nurses use distributed cognitive strategies to manage these interruptions. The research is motivated by the need to understand why interruptions, which consistently disrupt performance in laboratory settings, result in relatively few errors in clinical practice. The researchers employed a mobile eye-tracking system to collect data from ten registered nurses working in a tertiary ICU. This equipment recorded the nurses' field of view, eye movements, and ambient audio, allowing for the precise measurement of resumption lags—the time between the end of an interruption and the nurse’s first fixation on objects associated with the primary task. The study utilized the memory for goals theory and prospective memory theory to guide the analysis. Multiple regression models were developed using six predictors derived from these theories: whether the primary task step was finished, interruption lag, interruption length, fixation on task representations, distractions during the interruption, and context changes. The results indicated that in 55.8% of interruptions, there was a finite, analyzable resumption lag. The main regression model explained 30.9% of the variance in these lags. Specifically, longer interruption lengths and changes in physical location due to the interruption significantly lengthened the resumption lag. In the remaining 37.6% of cases, nurses employed behavioral strategies that eliminated or greatly diminished the resumption lag. These strategies involved distributing cognitive demands across the environment, such as using artifacts or altering monitoring behaviors, thereby reducing the reliance on individual prospective memory. The significance of this study lies in its integration of individual cognitive models with the framework of distributed cognition. It demonstrates that while interruptions do impose cognitive costs, nurses actively mitigate these effects by leveraging their environment. The findings suggest that the disruptive potential of interruptions in healthcare can be reduced by supporting or designing systems that facilitate these distributed cognitive strategies. This approach offers a more nuanced understanding of interruption management in complex work domains, moving beyond simple error rates to examine the cognitive mechanisms and environmental supports that enable effective task resumption.

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• prospective memory interruptions