Article Text
Abstract
Background Errors in clinical reasoning occur in most cases in which the diagnosis is missed, delayed or wrong. The goal of this review was to identify interventions that might reduce the likelihood of these cognitive errors.
Design We searched PubMed and other medical and non-medical databases and identified additional literature through references from the initial data set and suggestions from subject matter experts. Articles were included if they either suggested a possible intervention or formally evaluated an intervention and excluded if they focused solely on improving diagnostic tests or provider satisfaction.
Results We identified 141 articles for full review, 42 reporting tested interventions to reduce the likelihood of cognitive errors, 100 containing suggestions, and one article with both suggested and tested interventions. Articles were classified into three categories: (1) Interventions to improve knowledge and experience, such as simulation-based training, improved feedback and education focused on a single disease; (2) Interventions to improve clinical reasoning and decision-making skills, such as reflective practice and active metacognitive review; and (3) Interventions that provide cognitive ‘help’ that included use of electronic records and integrated decision support, informaticians and facilitating access to information, second opinions and specialists.
Conclusions We identified a wide range of possible approaches to reduce cognitive errors in diagnosis. Not all the suggestions have been tested, and of those that have, the evaluations typically involved trainees in artificial settings, making it difficult to extrapolate the results to actual practice. Future progress in this area will require methodological refinements in outcome evaluation and rigorously evaluating interventions already suggested, many of which are well conceptualised and widely endorsed.
- Patient safety
- human error
- medical error
- measurement/epidemiology
- decision support
- computerised
- decision-making
- information technology
- trigger tools
- primary care
- diagnostic errors
- health services research
- healthcare quality improvement
- evidence-based medicine
- quality improvement
- audit and feedback
- cognitive biases
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Footnotes
The authors of this paper are solely responsible for its content, and disclosed no competing interests. The findings and interpretations in the paper do not represent the opinions or recommendations of the institutions with which the authors are affiliated, the Agency for Healthcare Research and Quality, or the US Department of Health and Human Services, Department of Veterans Affairs.
Funding This study was funded by the Agency for Healthcare Research and Quality (AHRQ) ACTION II Task Order #8, Contract No. HHSA290200600001 and in part by the Houston VA HSR&D Center of Excellence (HFP90-020).
Competing interests None.
Provenance and peer review Not commissioned; externally peer reviewed.