Background. Diagnostic reasoning requires clinicians to think through complex uncertainties. We tested the possibility of a bias toward an available single diagnosis in uncertain cases. Design. We developed 5 different surveys providing a succinct description of a hypothetical individual patient scenario. Each scenario was formulated in 2 versions randomized to participants, with the versions differing only in whether an alternative diagnosis was present or absent. The 5 scenarios were designed as separate tests of robustness using diverse cases, including a cautious scenario, a risky scenario, a sophisticated scenario, a validation scenario, and a comparative scenario (each survey containing only 1 version of 1 scenario). Participants included community members (n=1104) and health care professionals (n=200) who judged the chances of Covid infection in an individual patient. Results. The first scenario described a cautious patient and found a 47% reduction in the estimated odds of Covid when a flu diagnosis was present compared with absent (odds ratio=0.53, 95% confidence interval 0.30 to 0.94, P=0.003). The second scenario described a less cautious patient and found a 70% reduction in the estimated odds of Covid in the presence of a flu diagnosis (odds ratio=0.30, 95% confidence interval 0.13 to 0.70, P<0.001). The third was a more sophisticated scenario presented to medical professionals and found a 73% reduction in the estimated odds of Covid in the presence of a mononucleosis diagnosis (odds ratio=0.27, 95% confidence interval 0.10 to 0.75, P<0.001). Two further scenarios-avoiding mention of population norms-replicated the results. Limitations. Brief hypothetical scenarios may overestimate the extent of bias in more complicated medical situations. Conclusions. These results demonstrate that an available simple diagnosis can lead individuals toward premature closure and a failure to fully consider additional severe diseases. Highlights. Occam’s razor has been debated for centuries yet rarely subjected to experimental testing for evidence-based medicine. This article offers direct evidence that people favor an available simple diagnosis, thereby neglecting to consider additional serious diseases. The bias can lead individuals to mistakenly lower their judged likelihood of Covid or another disease when an alternate diagnosis is present. This misconception over the laws of probability appears in judgments by community members and by health care workers. The pitfall in reasoning extends to high-risk cases and is not easily attributed to information, incentives, or random chance.
Commentaire du Dr Marius Laurent (PAQS)
- Cet article questionne le « principe de parcimonie » et son illustration par le « rasoir d’Occam » dans le monde complexe du diagnostic. Les solutions simples, faisant l’épargne de paramètres, sont-elles appropriées dans un univers complexe ? L’auteur nous met en garde : il teste cinq scenarii où le même problème se pose (dans des environnements de risque « Covid » différents) : un patient présente des signes compatibles avec la Covid-19, nous sommes en période de pandémie, on le teste (le test met 48 heures) et on le teste aussi pour un virus influenza (résultat en quelques heures) : quels sont les hypothèses diagnostiques et leur degré de certitude selon que le test influenza soit positif ou négatif ? De fait, ces deux infections sont indépendantes l’une de l’autre, ne s’influencent pas, et leur probabilité dépend des mêmes facteurs environnementaux testés par les cinq scenarii (port du masque ou non, milieu contaminé ou non…). Ceci n’empêche pas que la probabilité d’être en face de la Covid-19 diminue dans l’esprit des professionnels questionnés si on détecte un virus influenza. En d’autres mots, ce principe de parcimonie fait partie de notre bagage intellectuel lorsque nous posons un diagnostic, et est susceptible de nous jouer le mauvais tour de distordre notre perception des probabilités diagnostiques.
Redelmeier DA, Shafir E. The fallacy of a single diagnosis. Med Decis Making 2022. Doi : 10.1177/0272989X221121343.