Constructing diagnostic likelihood: clinical decisions using subjective versus statistical probability

Kinnear, John; Jackson, Ruth

doi:10.1136/postgradmedj-2016-134496

Cited by 1 publication

(2 citation statements)

References 26 publications

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“…The findings regarding the base rate fallacy are diverse. While an older study by Weber and colleagues only showed little prevalence of base rate neglect (Weber et al, 1993), a recent study by Kinnear & Jackson (2016) identified the major evidence of representativeness heuristic, resulting in base rate neglect. The latter study also identified that base rate neglect occurred despite a good understanding of statistical probability concepts.…”

Section: Empirical Data On the Prevalence Of Decision-making Biases In Medicinementioning

confidence: 94%

“…The latter study also identified that base rate neglect occurred despite a good understanding of statistical probability concepts. One possible explanation for this dissonance could be that the teaching of diagnostic decision-making foregrounds stereotypic presentations of diseases (Kinnear & Jackson, 2016).…”

Section: Empirical Data On the Prevalence Of Decision-making Biases In Medicinementioning

confidence: 99%

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How Human Decision-making Biases Influence Health Outcomes in Patient Care

Sibbel

Huber

2021

EJMI

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Purpose: Medical treatments and medical decision making are mostly human based and therefore in risk of being influenced by cognitive biases. The potential impact could lead to bad medical outcome, unnecessary harm or even death. The aim of this comprehensive literature study is to analyse the evidence whether healthcare professionals are biased, which biases are most relevant in medicine and how these biases may be reduced. Approach/Findings: The results of the comprehensive literature based meta-analysis confirm on the one hand that several biases are relevant in the medical decision and treatment process. On the other hand, the study shows that the empirical evidence on the impact of cognitive biases on clinical outcome is scarce for most biases and that further research is necessary in this field. Value/Practical Implications: Nevertheless, it is important to determine the extent to which biases in healthcare professionals translate into negative clinical outcomes such as misdiagnosis, delayed diagnosis, or mistreatment. Only this way, the importance of incorporating debiasing strategies into the clinical setting, and which biases to focus on, can be properly assessed. Research Limitations/Future Research: Though recent literature puts great emphasis on cognitive debiasing strategies, there are still very few approaches that have proven to be efficient. Due to the increasing degree of specialization in medicine, the relevance of the different biases varies. Paper type: Theoretical.

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Section: Empirical Data On the Prevalence Of Decision-making Biases In Medicinementioning

confidence: 94%

Section: Empirical Data On the Prevalence Of Decision-making Biases In Medicinementioning

confidence: 99%