The Effect of Cognitive Load and Task Complexity on Automation Bias in Electronic Prescribing

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Date: Nov. 2018
From: Human Factors(Vol. 60, Issue 7)
Publisher: Sage Publications, Inc.
Document Type: Author abstract
Length: 276 words

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Abstract :

Objective: Determine the relationship between cognitive load (CL) and automation bias (AB). Background: Clinical decision support (CDS) for electronic prescribing can improve safety but introduces the risk of AB, where reliance on CDS replaces vigilance in information seeking and processing. We hypothesized high CL generated by high task complexity would increase AB errors. Method: One hundred twenty medical students prescribed medicines for clinical scenarios using a simulated e-prescribing system in a randomized controlled experiment. Quality of CDS (correct, incorrect, and no CDS) and task complexity (low and high) were varied. CL, omission errors (failure to detect prescribing errors), and commission errors (acceptance of false positive alerts) were measured. Results: Increasing complexity from low to high significantly increased CL, F(1, 118) = 71.6, p Conclusion: Results challenge the notion that AB is triggered by increasing task complexity and associated increases in CL. Omission errors were associated with lower CL, suggesting errors may stem from an insufficient allocation of cognitive resources. Application: This is the first research to examine the relationship between CL and AB. Findings suggest designers and users of CDS systems need to be aware of the risks of AB. Interventions that increase user vigilance and engagement may be beneficial and deserve further investigation. Keywords: automation bias, cognitive load, task complexity, human-computer interaction, working memory, health information technology, medication management and safety, patient safety, medication alerts, compliance, reliance DOI: 10.1177/0018720818781224

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Gale Document Number: GALE|A559210338