Selecting clinical diagnoses: logical strategies informed by experience

J Eval Clin Pract. 2016 Aug;22(4):588-97. doi: 10.1111/jep.12417. Epub 2015 Jul 23.


This article describes reasoning strategies used by clinicians in different diagnostic circumstances and how these modes of inquiry may allow further insight into the evaluation and treatment of patients. Specifically, it aims to make explicit the implicit logical considerations that guide a variety of strategies in the diagnostic process, as exemplified in specific clinical cases. It focuses, in particular, in strategies that clinicians use to move from a large set of possible diagnoses initially suggested by abductive inferences - the process of hypothesis generation that creates a diagnostic space - to a narrower set or even to a single 'best' diagnosis, where the criteria to determine what is 'best' may differ according to different strategies. Experienced clinicians should have a diversified kit of strategies - for example, Bayesian probability or inference to a lovely explanation - to select from among previously generated hypotheses, rather than rely on any one approach every time.

Keywords: Bayesian probability; Peirce; abduction; diagnosis; hypothesis; induction.

MeSH terms

  • Bayes Theorem
  • Clinical Decision-Making / ethics*
  • Clinical Decision-Making / methods*
  • Diagnosis*
  • Humans
  • Lymphadenopathy / diagnosis
  • Pain / diagnosis
  • Physician-Patient Relations
  • Problem Solving
  • Skin Diseases / diagnosis
  • Stomach Ulcer / complications
  • Stomach Ulcer / diagnosis
  • Vertebral Artery Dissection / diagnosis