Assessment, Diagnosis, and Clinical Reasoning
Core concepts
Clinical reasoning moves from data collection (history, observation, physical assessment, tests) to hypothesis generation, interpretation, and clinical decision-making. Know subjective vs. objective data, reliability and validity of tests, sensitivity and specificity, positive and negative predictive value, and differential diagnosis thinking.
Use structured frameworks: problem list, SOAP (Subjective, Objective, Assessment, Plan), and red-flag screening. Recognise cognitive biases - anchoring, confirmation bias, availability heuristic - that lead to diagnostic error. Understand when to refer and when to reassess.
Traps in questions
- Sensitivity vs. specificity: a highly sensitive test is good for ruling out (SnNout); a highly specific test is good for ruling in (SpPin).
- PPV depends on prevalence: a positive result in a low-prevalence population is more likely false positive.
- Anchoring bias: the first plausible diagnosis is not always correct; reassess when findings diverge.
- Assessment vs. diagnosis: allied health assessment informs, but formal diagnosis may require medical input.
Rule of thumb
"SnNout and SpPin." Sensitive test negative rules out; specific test positive rules in.
Worked example
A screening test with 95% sensitivity returns negative. That result is useful for excluding the condition (few false negatives), but a positive result in a low-prevalence setting may still be a false positive - confirm before acting.