Accepted for/Published in: JMIR Nursing
Date Submitted: Jul 14, 2022
Open Peer Review Period: Jul 14, 2022 - Sep 8, 2022
Date Accepted: Sep 9, 2022
(closed for review but you can still tweet)
Opportunities to Support Decision-Making about Patient Mobility: Using Work Domain Analysis to Understand the ICU Nurse Work Environment
ABSTRACT
Background:
Patient mobility is an evidenced-based physical activity intervention initiated during intensive care unit (ICU) admission and continued throughout hospitalization to maintain functional status, yet mobility is a complex intervention and not consistently implemented. Cognitive work analysis (CWA) is a useful human factors framework for understanding complex systems and can inform future technology design to optimize outcomes.
Objective:
To understand the complexity and constraints of the ICU work environment as it relates to nurses carrying out patient mobility interventions, using CWA.
Methods:
We conducted a work domain analysis and completed an abstraction hierarchy using the CWA framework. Data from documents, observation (32 hours) and interviews (n=20) with nurses from two hospitals were used to construct the abstraction hierarchy.
Results:
Nurses seek information from a variety of sources and integrate patient and unit information to inform decision-making. The completed abstraction hierarchy depicts multiple high-level priorities that nurses balance, specifically, providing quality, safe care to patients while helping to manage unit-level throughput needs. Connections between levels on the abstraction hierarchy describe how and why nurses seek patient and hospital unit information to inform mobility decision-making. The analysis identifies several opportunities for technology design to support nurse decision-making about patient mobility.
Conclusions:
Future interventions need to consider the complexity of the ICU environment and types of information nurses need to make decisions about patient mobility. Considerations for future system re-design include developing and testing clinical decision support tools that integrate critical patient and unit-level information to support nurses in making patient mobility decisions.
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© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.