Earlier quoted context omitted.
Doctors observe a result of the test, and know the basic probabilities (in the example, 99% test accuracy, 1% of population have the disease). The problem is that they [often] draw incorrect conclusions from those observations (99% test accuracy and you tested positive? well then you likely - 99% - have the disease, right?). The question formed as 'your one patient tested positively' is more immediately relevant, I'd…
Of course, doctors do not randomly assign tests to patients. Their prior that a patient has a disease is a lot higher than the background frequency of it occurring. Getting them to estimate their prior would be interesting.
Other cases that come to mind: -- doctors who offer "full body scans" as a part of an executive physical; you're pretty much guaranteed to turn up something that is 2 sigma away from the population norm, somewhere in the body, on such a scan
-- spinal x-rays for back pain. Doctors almost always find something abnormal, and use that to justify the back pain and treat aggressively. But, we don't really have a good prior; if you x-rayed 1000 people off the street, would we find similar abnormalities frequently?