A cognitive forcing tool to mitigate cognitive bias – a randomised control trial View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Eoin D. O’Sullivan, Susie J. Schofield

ABSTRACT

BACKGROUND: Cognitive bias is an important source of diagnostic error yet is a challenging area to understand and teach. Our aim was to determine whether a cognitive forcing tool can reduce the rates of error in clinical decision making. A secondary objective was to understand the process by which this effect might occur. METHODS: We hypothesised that using a cognitive forcing tool would reduce diagnostic error rates. To test this hypothesis, a novel online case-based approach was used to conduct a single blinded randomized clinical trial conducted from January 2017 to September 2018. In addition, a qualitative series of "think aloud" interviews were conducted with 20 doctors from a UK teaching hospital in 2018. The primary outcome was the diagnostic error rate when solving bias inducing clinical vignettes. A volunteer sample of medical professionals from across the UK, Republic of Ireland and North America. They ranged in seniority from medical student to Attending Physician. RESULTS: Seventy six participants were included in the study. The data showed doctors of all grades routinely made errors related to cognitive bias. There was no difference in error rates between groups (mean 2.8 cases correct in intervention vs 3.1 in control group, 95% CI -0.94 - 0.45 P = 0.49). The qualitative protocol revealed that the cognitive forcing strategy was well received and a produced a subjectively positive impact on doctors' accuracy and thoughtfulness in clinical cases. CONCLUSIONS: The quantitative data failed to show an improvement in accuracy despite a positive qualitative experience. There is insufficient evidence to recommend this tool in clinical practice, however the qualitative data suggests such an approach has some merit and face validity to users. More... »

PAGES

12

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URI

http://scigraph.springernature.com/pub.10.1186/s12909-018-1444-3

DOI

http://dx.doi.org/10.1186/s12909-018-1444-3

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https://app.dimensions.ai/details/publication/pub.1111259060

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30621679


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