Constructing diagnostic likelihood: clinical decisions using subjective versus statistical probability.
Postgrad Med J
; 93(1101): 425-429, 2017 Jul.
Article
in En
| MEDLINE
| ID: mdl-27941006
ABSTRACT
BACKGROUND:
Although physicians are highly trained in the application of evidence-based medicine, and are assumed to make rational decisions, there is evidence that their decision making is prone to biases. One of the biases that has been shown to affect accuracy of judgements is that of representativeness and base-rate neglect, where the saliency of a person's features leads to overestimation of their likelihood of belonging to a group. This results in the substitution of 'subjective' probability for statistical probability.METHODS:
This study examines clinicians' propensity to make estimations of subjective probability when presented with clinical information that is considered typical of a medical condition. The strength of the representativeness bias is tested by presenting choices in textual and graphic form. Understanding of statistical probability is also tested by omitting all clinical information.RESULTS:
For the questions that included clinical information, 46.7% and 45.5% of clinicians made judgements of statistical probability, respectively. Where the question omitted clinical information, 79.9% of clinicians made a judgement consistent with statistical probability. There was a statistically significant difference in responses to the questions with and without representativeness information (χ2 (1, n=254)=54.45, p<0.0001).CONCLUSIONS:
Physicians are strongly influenced by a representativeness bias, leading to base-rate neglect, even though they understand the application of statistical probability. One of the causes for this representativeness bias may be the way clinical medicine is taught where stereotypic presentations are emphasised in diagnostic decision making.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Physicians
/
Models, Statistical
/
Decision Support Systems, Clinical
Type of study:
Diagnostic_studies
/
Prognostic_studies
/
Qualitative_research
/
Risk_factors_studies
Limits:
Humans
Language:
En
Journal:
Postgrad Med J
Year:
2017
Document type:
Article
Affiliation country:
United kingdom