Diagnostic Decision-Making and Strategies to Improve Diagnosis

Thammasitboon, Satid; Cutrer, William B.

doi:10.1016/j.cppeds.2013.07.003

Cited by 51 publications

(48 citation statements)

References 28 publications

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“…Checklists can be thought of as a cognitive forcing tool that demand the user think in a more ordered fashion. [56][57][58] Checklists are a debiasing strategy that challenges 'structure' of thought, attempting to force our cognition onto certain topics even if they were not previously considered. 59,60 Variations on checklists include computerised clinical decision support systems that may have a role in reducing cognitive load by providing decision aids, guidance and differential diagnostic lists.…”

Section: Checklistsmentioning

confidence: 99%

Cognitive Bias in Clinical Medicine

O’Sullivan

Schofield

2018

Journal of the Royal College of Physicians of Edinburgh

242

176

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Cognitive bias is increasingly recognised as an important source of medical error, and is both ubiquitous across clinical practice yet incompletely understood. This increasing awareness of bias has resulted in a surge in clinical and psychological research in the area and development of various 'debiasing strategies'. This paper describes the potential origins of bias based on 'dual process thinking', discusses and illustrates a number of the important biases that occur in clinical practice, and considers potential strategies that might be used to mitigate their effect.

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Section: Checklistsmentioning

confidence: 99%

Cognitive Bias in Clinical Medicine

O’Sullivan

Schofield

2018

Journal of the Royal College of Physicians of Edinburgh

242

176

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“…This error is also related to a cognitive bias known as representativeness [Croskerry, 2003;Thammasitboon and Cutrer, 2013;Lighthall and Vazquez-Guillamet, 2015]. This bias occurs when the examiners do not consider differential diagnoses, since they are looking for prototypic characteristics for the condition that is being diagnosed [Croskerry, 2003].…”

Section: Discussionmentioning

confidence: 99%

“…In medicine, the impact of methodological [Lijmer et al, 1999] and cognitive biases [Thammasitboon and Cutrer, 2013] on the diagnosis of many health conditions has been evaluated, but this has never been done in relation to caries detection. In our study, we showed that the children's oral health conditions affected the accuracy of examiners using visual inspection in detecting proximal caries lesions of primary molars.…”

Section: Discussionmentioning

confidence: 99%

“…For this reason, the visual and the radio-graphic examination could be influenced by external factors. The effect of cognitive biases on the diagnosis of various health conditions has been extensively evaluated in different medical fields [Thammasitboon and Cutrer, 2013;Blumenthal-Barby and Krieger, 2015]. In dentistry, however, this type of research is scarce [Blumenthal-Barby and Krieger, 2015].…”

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confidence: 99%

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The Influence of Cognitive Bias on Caries Lesion Detection in Preschool Children

et al. 2018

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We aimed to evaluate whether children’s caries experience exerts an influence on the performance of visual and radiographic methods in detecting nonevident proximal caries lesions in primary molars. Eighty children (3–6 years old) were selected and classified as having a lower (≤3 decayed, missing, or filled surfaces; dmf-s) or higher (> 3 dmf-s) caries experience. Two calibrated examiners then assessed 526 proximal surfaces for caries lesions using visual and radiographic methods. As a reference standard, 2 other examiners checked the surfaces after temporary separation. Noncavitated and cavitated lesion thresholds were considered and Poisson multilevel regression analyses were conducted to evaluate the influence of caries experience on the performance of diagnostic strategies. Accuracy parameters stratified by caries experience were also derived. A statistically significant influence of caries experience was observed only for visual inspection, with more false-positive results in children with a higher caries experience at the noncavitated lesion threshold, and more false results at the cavitated threshold. The detection of noncavitated caries lesions in children with a higher caries experience was overestimated (specificity = 0.696), compared to children with a lower caries experience (specificity = 0.918), probably due to confirmation bias. However, the examiners underestimated the detection of cavitated lesions in children with a higher caries experience (sensitivity = 0.143) compared to lower-caries-experience children (sensitivity = 0.222), possibly because of representativeness bias. The radiographic method was not influenced by children’s caries experience. In conclusion, children’s caries experience influences the performance of visual inspection in detecting proximal caries lesions in primary teeth, evidencing the occurrence of cognitive biases.

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“…Recently, clinical diagnostic reasoning has been characterised by ‘dual-processing models’ 15. This suggests that there are two components to making a clinical decision—a fast, unconscious or ‘system 1’ component and a more logical, analytical ‘system 2’ component.…”

Section: Introductionmentioning

confidence: 99%