The 538 article actually makes a lot of sense and is a pretty decent introduction to a common public health issue. > Their assertion that tests === diagnostics

The 538 article actually makes a lot of sense and is a pretty decent introduction to a common public health issue. > Their assertion that tests === diagnostics that map 1:1 to a disease was baseless. Tests don't answer the question "doe patient have diabetes?", they answer the question "what is the patients glucose level?" 115 mg/dl. Medical tests that aren't actionable aren't useful. So while you're correct in a very narrow sense, you have to use the results to make a decision about treatment. If you're going to make treatment decisions based on tests that have some amount of inherent error, you may end up over or under-treating patients. > Maybe the patient forgot to fast, maybe the test was a fluke? Either way a consistent average of 85 would put that out of range. Medical tests have both random and systematic error. What you're talking about is random error (i.e. a single test result being bad). However, many tests have systematic error (i.e. the result being wrong every time the test is taken) just due to personal variation in what's "normal". The article makes the point that if more tests lead to worse outcomes[1] (due to overtreatment) then adding more tests is useless or worse than useless. This effect is particularly pronounced when testing across large populations, even if the test is highly accurate. [1] And in many cases they do. For example, early mammogram screenings result in worse outcomes for patients when done across a large population. See http://annals.org/article.aspx?articleid=2480757 http://annals.org/article.aspx?articleid=2480757