[_zbap]

Sorry, user logicallee explained this better than I did. You're looking at 4-5 graphs put next to each other for comparison. The nearest flatland with the huge towers is the one troubled clinic.

Here's an annotated version of that, drawn by a child apparently: http://i.imgur.com/1dcuuXI.png

As you can see, data of the clinic we were investigating is the first 6 long rows, and ones behind it are clinics we were not investigating. We asked to compare a number of clinics so not to tip our hand, and the administration took half a year of paranoid data checking before giving it to us.

I know, not the most intuitive graph, but the graph was meant to be a diagnostic for only me, the person who composed the data. As you can see, a single glance at the graph revealed the problem, without involving any numerical analysis.

[logicallee]

thanks, though seemed to me thaumasiotes who I replied understood perfectly! In particular he is correct that "Of the three non-fraudulent clinics, two show pretty elevated levels of that particularly lucrative code, the one that clips the ceiling for the fraudulent clinic. How much of that is fraud?" which he only could tell by correctly interpreting the graph (reading across that drug's column) - and it's a good question.

His second paragraph was only about the one clinic in question, he ignored the other 3 in his second paragraph, though he wasn't explicit about this, and asked a year-over-year question about the drug, concerning clinic A only.

My point was kind of tangential, that, INCIDENTALLY if the colors matched up in the rows (were repeated in the same order 4 times) you could look at it another way visually that you can't right now without counting by hand. Specifically, you could look at the aggregate trend for all four clinics year-over-year for the drug in question (the one with the spike) by seeing with your eye how the six colors move as you move your eye from Stripe A, to Stripe B, to Stripe C, to Stripe D. Right now, with your eye you can only tell or ask about year-over-year changes for a specific drug for clinic A, not for the other ones. If all four 2009's were peach, you could easily tell if there were 4 spikes in that year or just one. In fact in 2009 all four do seem to spike somewhat. Not being able to visually see aggregate year-over-year comparisons is probably the downside to the current presentation.

[_zbap]

Ah, I see, and take your point. I should have worked on a more reader-friendly version of this graph so I just assume people don't understand its bizarre nature. But, my work had been done many years ago with the investigation.

Here's the part that stood way out even with that unsophisticated graph: the flat land between various prescription codes. It's just there. It draws the eye and makes you ask questions, which is what we did. Another dimension not pictured there is distribution of doctors vs prescriptions. Theirs stood out on that too.

Even in their busiest years, they didn't treat any common ailments with any degree of distributed variety. By contrast, rest of the clinics did business as usual: whoever walked through their door got treated for whatever random thing they had.

[thaumasiotes]

Just based on eyeballing the graph, I'd say there's a cultural element to what codes get used, because individual clinics often show more or less activity at a particular code for all six years. Choosing a code is something of a gray area, so that's not necessarily malicious, but I think "whoever walked through their door got treated for whatever random thing they had" is slightly oversimplified -- the patients will have been treated appropriately, but local culture will have pulled them into being coded in certain ways over other, arguably equally-applicable ways.

(Clinics having their own "personality" in coding could also be explained by the clinics having locally well-recognized specialties. That's hard to evaluate without knowing which codes are which.)