For doctors, most diagnoses come from the history and examination. In many non-medical pathways, it can feel like the reverse: very little diagnosis from history/exam, and a heavy reliance on tests or onward referral, sometimes with no working diagnosis at all. If someone doesn’t understand what history and examination are for, it’s easy to skip them and default to “do tests” or “admit/refer so a specialist can diagnose”. The problem is that tests are then interpreted without a Bayesian “a priori” anchor. Without a pre-test probability built from a good story, a focused exam, and an understanding of how common conditions are so you’re left with results that can mislead, over-diagnose, or generate incidental findings. And if you don’t have a detailed grasp of disease patterns, you don’t know which questions to ask or what to look for to diagnose dementia or depression or diabetes or diphtheria. You can’t form a meaningful differential if you don’t know what’s common, what’s dangerous, and what’s discriminating. So the whole process drifts into secondary referrals and scanning as the default route to certainty. In parallel, some non-medical exams don’t require a deep knowledge base, so people are expected to “look it up” in real time under pressure. That isn’t the same as understanding, and it’s hard to expect consistently good outcomes from it. The final issue is that often one doesn't know what one doesn't know. This can lead to overconfidence or a very defensive position. Finally if you want to be seeing patients and making good diagnoses there is course for this called Medicine. Exams do expect knowledge.