The SQL tutorial looks at the numbers but doesn't emphasize two kind of glaring omissions in the WSJ article:
a) Dr Weaver is charging for a procedure _labeled_ 'cardiac', but there is no mention of what the procedure is, it's relevance to cardiology (if the label is accurate), or it's relevance to internal medicine (Dr Weaver's _labeled_ current specialty). For all we know, Dr Weaver is an ex-cardiologist, now practicing internal medicine for which he has found this procedure to be extremely useful in the patients he treats. For all we know, the procedure was mislabeled (esp. since it is pointed out that the data is noisy incl. spelling errors, multiple labels for same thing, etc.)
b) At one point, Dr. Weaver's _statistical_ use of the procedure (99.5%) is compared to a raw numerical value (6) by Cleveland Clinic cardiologists. For all we know, the clinic cardiologists only saw 6 patients for whom the procedure was relevant, or they never use the procedure because they have other more relevant/current techniques, or patients who are seen by the clinic are at a point where the procedure isn't required.
While the SQL tutorial is an interesting look at how to verify the accuracy of the statistics in an article, it tacitly provided validation for what is still poor reporting ie. the statistics need explanation and validation beyond simple numbers.
If you assume that most people are pretty honest (statistically they are), then the SQL queries are a neat way to highlight that the billing system (not the practioners) is in need of a second or third look.