Will catastrophic only health insurance be rescinded in the end?
Taunter explains how the .5% rescission rate figure discussed in the hearings on health insurance premiums and coverage is used to dismiss Congressional concerns as inconsequential and actually is a good business practice that will not change. It is worth going to the post to accurately follow the train of thought. Taunter concludes that the chances for rescission for a serious illness is:
If the top 5% is the absolute largest population for whom rescission would make sense, the probability of having your policy cancelled given that you have filed a claim is fully 10% (0.5% rescission/5.0% of the population). If you take the LA Times estimate that $300mm was saved by abrogating 20,000 policies in California ($15,000/policy), you are somewhere in the 15% zone, depending on the convexity of the top section of population. If, as I suspect, rescission is targeted toward the truly bankrupting cases – the top 1%, the folks with over $35,000 of annual claims who could never be profitable for the carrier – then the probability of having your policy torn up given a massively expensive condition is pushing 50%. One in two.
Rescission definition practice can be found here and unfair examples here. Here is why door number two is NOT 50/50.
It is suggested that application forms are formed to allow for inaccuracies and that some criterion used to cancel policies is easily avoidable at the time of the application, the implication being future use for the inaccuracy makes it worthwhile to allow ambiguity and not vet information, mainly for those who wind up claiming over $35,000 and who have severe, chronic conditions that make premiums from that person irrelevant to profit.
This may have not been the intent long long ago, and certainly fraud occurs, but rescission having a basis purely monetary and not legal (from a common consumer point of view on what fraud is), is the policy today if testimony is to be believed.
The first notion, that it is a small problem except for the person involved, is discussed in the first post. The key to amended %’s lies in the fact that Medicare takes care of the 65/over group of chronically ill and elderly clients, so the privately covered population is smaller than the per centages indicate as well, a major oversight. The second and third part of the problem will be in Part 2 and 3 (clever, huh?)
StatsGuy wrote in comments to the Taunter Media post:
The same light bulb went off when I read the 0.5%, but I could not have explained it _nearly_ as well. Very nice post.
I still wonder, though, whether it might be slightly worse than even this picture.
1) I believe your data is for the US population as a whole. (If I’m wrong, then this comment is meaningless – apologies.) But, in fact, much of the sickest part of the population receives health care via Medicare because older people are (to use your technical term) sicker.
So the % of people in the top tier AMONG PEOPLE NOT ON MEDICARE is much lower, which means that the conditional probability of suffering rescission given that you need treatment is much higher. Roughly, if the % of people among under-65 (and not on Medicaid) in the top bracket was half of what it is for the entire population, then the probability of suffering rescission given that you have a large claim is double even your current estimates.
2) The probability of losing the policy given that you really need it may be X% in any given year. But there’s a cumulative effect – over time, you build up a reservoir of uninsurable who lost insurance due to rescission, and now cannot get it back because they have a chronic condition.
on July 29, 2009 at 10:03 am | Reply Taunter
You are absolutely correct about #1, and this is a huge error factor. 10% of Medicare costs take place in the last month of life alone, and Medicare is roughly 45% of the national health care spend. So all of those patients are clogging up the top end of national distribution and not on private insurance in the first place. Unfortunately, I can’t find a private-only, or individual-pay-only distribution, and of course if I did find an individual-pay-only distribution it would be skewed on the top with denied claims (some people should be spending a lot, but actually spend much less, because their policy was pulled). The Reuters article says Medicare spends 30% of its outlay on the top 5% of its population, which means it has a flatter curve than non-Medicare (I would assume, without evidence, that fewer Medicare beneficiaries have negligible health expenses). This implies non-Medicare spending is even more highly concentrated with a few very high spenders.
On #2, I’m a little less confident, and it was one of the reasons I may have misunderstood James’ original post. There is a cumulative effect, but that effect is blunted to some degree by the fact that the people who account for the very high medical expenditures do not necessarily change much from year-to-year (with the obvious exception of the end-of-life expenses typically borne by Medicare). In fact, one of the reasons I suspect rescission became such a powerful phenomenon is that if Sally has breast cancer at a young age, she is going to be in the 99th percentile several times; the carrier is weighing years of such expenses against her premium. So it might not be the case that in a forty year career an average person has a 33% chance of ending up at some point in the top percentile (1-(.99^40)); it is probably the case that most people have a tiny chance of ever getting an expensive chronic condition (or at least an expensive, chronic condition before turning 65), and some people have a large chance of repeatedly being in the top percent.
Keep the discussion going. It is clear a profit motive has serious impact for some people…how would you bet even catastropohic only insurance premium money?