Very interesting, I didn't know so much of the health expenditure burden lay on the top 1%. I'm guessing it also has to do with them not carrying insurance and paying out of pocket for their healthcare?

@Fabio I would also guess that it has a lot to do with the fact that they go and get care, because they can afford to.

A lot of people cannot afford the care that they should be getting, both in terms of preventative care and regular checkups, and in terms of dealing with acute injury or illness.

Would also have to look at what portion of the spend is for elective or cosmetic purposes.

I think this is largly an artifact of extremely high costs for some complicated treatments and lack of cost controls in the system. Last year my university health plan reported that they went broke due to five events that caused costs of more than 1 million dollars each...

I think that sometimes we connect "difficulty" with "speed"

I do agree that these charts can be difficult to interpret, but I wonder if that's because we assume they should be as quick to parse as a bar chart. If you commit the time to deciphering the chart, it becomes simple to interpret.

So: is it fundamentally "difficult" or is it just "time consuming"?

What software to you use to generate your graphics?

Acotgreave: I do think speed of comprehension is an important attribute. I have also written about the "return on effort" concept: if there is a large enough benefit for the effort needed to understand the chart, then readers will be more willing to expense that effort.

I have explained this type of chart in the context of predictive modeling lift to many classes of students, which is why I know that many people have trouble grasping the concept. It doesn't help that the original doesn't have the diagonal line showing the reference level of equal distribution. I find that many students even have trouble grasping the reason why equal distribution (in the case of predictive models, that's random selection) leads to a diagonal line. The other difficulty is to grasp that the units are pre-ordered by some variable before being put into ten groups.

Elias: Those were manually created Powerpoint diagrams. And yes, you can make nice-looking charts using Powerpoint or Excel. If I needed code, I'd have used R for a custom design like this. Others will use Illustrator.

A challenging chart can be worth the effort but usability should be an important goal of any designer. A reader is at least as likely to misinterpret a difficult chart as he is to fail to interpret it at all. In this case the reader walks away with a mistaken impression, and never has a reason to decide whether to commit the extra mental resources to figure it out.

Having worked in the health care sector, the chart(s) are consistent with everything known about expenditures. Their distribution is extreme valued, largely due to the chronically ill. Not mentioned (unless I missed it) is the consistency of the distribution with Pareto's classic 80-20 rule. The chronically ill also tend to be older and poorer with significant shortfalls in insurance coverage. Medicaid and medicare are picking up the tab for a large proportion of this group. On an historical note, many people attribute the kink in the graph around 1980 in life expectancy over time to the advent of managed care.

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