Category Archives: Essays

The Kaiser analysis of ACA enrollment has problems

On December 17, 2013, the Kaiser Family Foundation published an influential study that comforted many supporters of the Affordable Care Act who had been made nervous by early reports that the proportion of younger persons enrolling in Exchanges was significantly less than expected.  If true, such a disproportion could have created major stress on future premiums in the Exchanges because the private Exchange system under the ACA depends — or so it was thought — on younger persons subsidizing older persons. The Kaiser study asserted, however, that even if one cut the number of younger persons by 50%, insurer expenses would exceed insurer premiums by “only” 2.4%.  This finding under what it thought was a “worst case scenario” underpinned Kaiser’s conclusion that a “premium death spiral was highly unlikely.”

This post evaluates the Kaiser analysis. I do so in part because it disagreed a bit with my own prior findings, in part because it has gotten a lot of press, and because I have had a great deal of respect for Kaiser’s analyses in general.  I conclude that this Kaiser analysis rests, however, on an implausible assumption about the behavior of insurance purchasers and lacks much of a theoretical foundation. Once one eliminates this implausible assumption and employs a better theory of insurance purchasing, the threat of a death spiral becomes larger.

The reason for all this is a little complicated but try to bear with me and I will do my best to explain the problem.  Essentially, what Kaiser did was to run its simulation simply by lopping off people under the age of 34 and assuming that, for some reason, the disinclination of people to purchase health insurance on an Exchange would magically stop at age 34.  Thus, if an enrollment of, say, 2 million had been projected to come 800,000 from people age 18-34, 600,000 from middle aged people and 600,000 from the oldest group of enrollees, the “worst case” scenario Kaiser created (Scenario 2) would reduce enrollment to 1.6 million by having 400,000 come from people age 18-34, 600,000 from middle aged people, and 600,000 from the oldest group of enrollees. Thus, the youngest group would now constitute 25% of enrollees rather than 40%, and the other groups would constitute 37.5% of enrollees rather than 30%.

Although there is often nothing automatically wrong with this sort of “back of the envelope computation” — I have done many of them myself —  sometimes they give answers that are wrong in a meaningful way. And sometimes “meaningful” means a difference of just a few percentage points. Thus,  although the difference between 0.045 and 0.024 is not large on an absolute scale, this is one of these instances in which there could be a big difference between predicting premium increases augmented by 2.4% due to this particular form of adverse selection and predicting a premium increases augmented by 4.5% due to this particular form of adverse selection.   The first might be too small to lead to a quick adverse selection death spiral; the second, particularly if it combined with other factors increasing premiums, might be enough to start a problem. Death spirals are  a non-linear phenomenon a little like the “butterfly effect” in which small changes at one point in time can cascade into very large changes later on. What I feel comfortable saying is that the additional risk of a death spiral created by disproportionate enrollment of the an older demographic is greater than Kaiser asserts.

By simply lopping off the number of people under 35 who would enroll, the Kaiser model lacked a good theoretical foundation.  The model Kaiser should have run — “Scenario 3” —  is one in which the rate of enrollment is a sensible function of the degree of age-related subsidy (or anti-subsidy). Their two other scenarios could then be seen as special cases of that concept. Had they run such a “Scenario 3”, as I will show in a few paragraphs, the result is somewhat different.

Let me give you the idea behind what I think is a better model. I’m going to present the issue without the complications created by the messiness of data in this field.  We need, at the outset to know at least two things: (1)  the number of people of each age who might reasonably purchase health insurance if the subsidy were large enough (the age distribution of the purchasing pool); and (2) the subsidy (or negative subsidy) each person receives for purchasing health insurance as a function of age. By subsidy, I mean the ratio between the expected profit the insurer makes on the person divided by the expected expenses under the policy, all multiplied by negative one. The bigger the subsidy, the more money the insurer loses and the more likely the person is to purchase insurance.

Suppose, then, that the probability that a person will purchase health insurance is an “enrollment response function” of this subsidy. For any such enrollment response function, we can calculate at least three items: (1) the total number of people who will purchase insurance; (2) the age distribution of purchasers (including the “young invincible percentage” of purchasers between ages 18 and 35); and (3) — this is the biggie — the aggregate return on expenses made by the insurer.  Thus, some enrollment response function might result in 6.6 million adults purchasing insurance of whom 40% were “young invincibles” that generated a 1% profit for the insurer on adults while another enrollment response function might result in 2.9 million adults purchasing insurance of whom 20% were “young invincibles” that generated a 3% loss for the insurer on adults.

What we can then do is to create a family of possible enrollment response functions drawn from a reasonable functional form and find the member of that family that generates values matching the “baseline assumptions” made by both Kaiser and, apparently, by HHS about total enrollment and about the “young invincible percentage.” We can then calculate the aggregate return of the insurer on adults and call this the baseline return. What we can then do is assume different total enrollments and different young invincible percentages, find the member of the enrollment response function family that corresponds to that assumption, and then calculate the new revised return on adults. The difference between the baseline return and the new revised return on adults can be thought of as the loss resulting from this form of adverse selection. There are a lot of simplifications made in this analysis, but it is better, I believe, than either the back of the envelope computation by Kaiser that has gotten so much press and, frankly, the back of the envelope computation I did earlier on this blog.

Here’s a summary of the results.  When I (1) use the Kaiser/HHS age binning of the uninsured and indulge the simplifying assumption that the age distribution is uniform within each bin; (2) use Kaiser’s own estimate of the subsidy received by each age, (3) assume 7 million total purchasers ; and (4) assume 40% young invincibles with uniform age distribution within age bins, I find that the baseline return on adults is 1.0%. When I modify assumption (3) to have 3 million total purchasers and, as Kaiser did in Scenario 2, modify assumption (4) to have 20% young invincibles, the baseline return on adults is -3.5%.  Thus, a better computation of Kaiser’s worst case scenario is not a reduction in insurer profits of 2.4%, but rather a reduction of 4.5%.  

The graphics here compare enrollment rates, the age distribution of enrollees and various statistics for the baseline scenario and the scenario in which there are 3 million total purchasers and approximately 20% young invincibles.

Comparison of baseline scenario v. worst case using better assumptions
Comparison of baseline scenario v. worst case using better assumptions

We can use this methodology to run a variety of scenarios. I present them in the table below. A Mathematica notebook available here shows the computations underlying this blog entry in more detail. I am also making available a CDF version of the notebook and a PDF version of the notebook.

Various scenarios showing changes in insurer profits due to different enrollment response functions
Various scenarios showing changes in insurer profits due to different enrollment response functions

Please note that the computations engaged in here essentially ignore those under the age of 18.  This is unfortunate, but I do not have the data on the expected premiums and expenses of  children. It does not look as if Kaiser had that data either. Since children are expected to comprise only a small fraction of insured persons in the individual Exchanges, however, this omission probably does not change the results in a major way.

A humbling thought

The more I engage in this analysis, the more I realize how difficult it is.  There are data issues and, more fundamentally, behavioral issues that we do not yet have a good handle on.  Neither my model nor Kaiser’s model can really explain, for example, why, as has recently been noted, enrollment rates are so much higher in states that support the ACA by having their own Exchange and with Medicaid expansion than in states that more greatly oppose the ACA.  As I have suggested before, there is a social aspect and political aspect to the ACA that is difficult for simple models to capture.  Moreover, as I noted above, this is an area where getting a number “close to right” may not be good enough.  Premium increases of, say, 9% might not trigger a death spiral; premium increases of 10% might be enough.  And neither my nor anyone else’s social science, I dare say, is precise enough to distinguish between 9% and 10% with much confidence.

So, longer though it makes sentences, and less dramatic as it makes analyses and headlines, the humbling truth is that we can and probably should engage in informed rough estimates as to the future course of the Affordable Care Act, but it is hard to do much more as to many of its features. I wish everyone engaged in this discussion would periodically concede that point.

Other Problems with Kaiser

There are  other issues with the Kaiser analysis. Let me list some of them here.

Even accepting Kaiser’s analysis premium hikes would likely be more than 2%

Kaiser’s discussion of insurer responses to losing money is inconsistent. Look, for example, at this sentence in the report: “[i]f this more extreme assumption of low enrollment among young adults holds, overall costs in individual market plans would be about 2.4% higher than premium revenues.”  Kaiser further reports “Insurers typically set their premiums to achieve a 3-4% profit margin, so a shortfall due to skewed enrollment by age could reduce the profit margin of insurers substantially in 2014.” I don’t have a quarrel with this sentence.  But then look at what the Kaiser report says. “But, even in the worst case, insurers would still be expected to earn profits, and would then likely raise premiums in 2015 to make up the shortfall,” No! According to Kaiser’s own work, “even in the worst case,” insurer costs would be 2.4% greater than premium revenues.  Since there is little float in health insurance and investment return rates are low these days, insurers would likely not earn profits.  Then it gets worse. “However, a one to two percent premium increase would be well below the level that would trigger a “death spiral.” Perhaps so, but if insurers need to earn 3-4% to keep their shareholders happy and they are losing 1-2%, a more logical response would not be a 1-2% increase in premiums but a 4-6% increase. And, as Kaiser points out, larger premium increases could trigger a premium death spiral in part because death spirals are like avalanches: they start out small, only a little snow moves, but once the process starts it can become very difficult to abort.

Logical Fallacies

The first paragraph of Kaiser’s report asserts:  “Enrollment of young adults is important, but not as important as conventional wisdom suggests since premiums are still permitted to vary substantially by age. Because of this, a premium “death spiral” is highly unlikely.” Even if the first sentence of this quote were correct — a point on which this entry has cast serious doubt — the second sentence does not follow.  To use a sports analogy, it would be like saying that,  the role of a baseball “closer” is important but not as important as conventional wisdom suggests. Therefore the Houston Astros, who lack a good closer, are highly unlikely to lose.  No!  There are multiple factors that could cause an adverse selection death spiral.  Just because one of them is not as strong as others make out, that does not mean that a death spiral is unlikely. That’s either sloppy writing or just a pure error in logic.

Other Factors

And, in fact, if we start to look at some of those other factors, the threat is very real.  As discussed here in more depth, I would not be surprised if adverse selection based on completely unrated gender places as much pressure on premiums as adverse selection based on imperfectly rated age. And, as I have discussed in an earlier blog entry, the transitional reinsurance that somewhat insulates insurers from the effects of adverse selection will be reduced in 2015. This will place additional pressure on premiums.

And, on the other hand, the individual mandate, assuming it is enforced, will triple in 2015 and risk adjustment measures in 42 U.S.C. § 18063, will likely provide greater protection for insurers.  These two factors are likely to dampen adverse selection pressures.

Notes on Methodology

There are a number of simplifying assumptions made in my analysis.  Some of them are based on data limitations. Here are a few of what I believe are the critical assumptions.

1. Functional form: I experimented with two functional forms, one based on the cumulative distribution function of the logistic distribution and the other based on the cumulative distribution function of the normal distribution.  These are both pretty conventional assumptions and make sure that the enrollment rate stays bounded between 0 and 1. The results did not vary greatly depending on which family of functions the enrollment response functions were drawn from.

2. Uniform distribution of ages within each age bin of potential purchasers. I believe this is the same assumption made by Kaiser and it results from the absence of any more granular data on the age distribution of the uninsured that I was able to find.

3. The enrollment rate depends on the subsidy rate standing alone and not other possibilities such as subsidy rate and age. The data on enrollment rates is very sparse and so it is difficult to use very complex functions.  Perhaps a more complex analysis would assert that enrollment depends on both subsidy rate and age, since age may be a bit of a proxy for the variability of health expenses and thus of risk.

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Gender could be as big a problem as age for the Affordable Care Act

Concerns about whether insurance sold on  the individual Exchanges under the Affordable Care Act will succumb to an adverse selection death spiral have focused mainly on the shortage of younger enrollees into the system. This shortage is potentially a problem because, due to section 1201 of the ACA, premiums for younger enrollees must be at least one third of that for older enrollees even though actuarial science tells us that younger enrollee expenses are perhaps just one fifth of those for older enrollees. Younger enrollees are needed in large numbers to subsidize the premiums of the older enrollees. But at least premiums under the ACA respond at least somewhat to age.

The lesser studied potential source of  adverse selection problems, however, is the fact that medical expenses of women for many ages are essentially double those of men and yet the ACA forbids rating based on gender.  In a rational world, one would therefore expect women of most of the ages eligible for coverage in the individual Exchanges to enroll in plans on the Exchange at a higher rate than men. But, since the women have higher than average expenses than men, premiums based on the average expenses of men and women will prove too low, creating pressure on insurers to raise prices. And, of course, there could also be some disproportionate enrollment by older men who have higher medical expenses than women of equal age. While I welcome contrary arguments in what I regard as a fairly new area of study involving the ACA, gender-based adverse selection would certainly appear to be  a real problem created by the structure of that law.  To me, it looks to be potentially as large a problem as age-based adverse selection. It is certainly one that needs continuing and careful evaluation.

Caveats

I see only three limited factors that reduce what would otherwise appear to be a significant additional source for significant adverse selection. As set forth below, however, I do not believe that any of these factors are likely to materially reduce the problem.

1. Ignorance

The first is ignorance. Adverse selection emerges only if individuals can accurately foretell their future medical expenses with some accuracy. To the extent, therefore, that men and women are ignorant of the effect of gender on their projected medical expenses, adverse selection is potentially diminished. I say “potentially,” however, because of a subtlety: people don’t have to know why their expenses are what they are in order for adverse selection to emerge; they only have to be somewhat accurate in their guess. Thus, even if men and women don’t make the cognitive leap from seeing lower (or higher) medical expenses to issues of gender, but they still on balance get it right, adverse selection can exist. Thus, I end up doubting that ignorance of the correlation between gender and medical expense is going to retard adverse selection problems very much.

2. Correlation between gender and expense is lower for those 50-65.

The second factor that might reduce adverse selection based on gender is, curiously enough, adverse selection based on age. The difference between male and female medical expenses diminishes as one exits the middle 40s and heads into the 60s. Indeed, somewhere in the late 50s, the rates cross and men have slightly higher average medical expenses than women. Therefore, to the extent that it is the 50-65 set that is disproportionately purchasing coverage in the individual Exchanges, the potential for gender-based adverse selection is diminished — but only somewhat .  I say “but only somewhat” because if males over the age of about 55 or 58 enroll at higher rates than women of similar ages there will actually be adverse selection pressures due to the higher medical expenses of men that age. On the other hand, to the extents efforts are made to reduce age-based adverse selection by promoting coverage to the younger (potentially child-bearing) set, the potential for most forms of gender-based adverse selection increases.

3. Gender-correlated risk aversion

The third factor that could in theory reduce adverse selection problems is if men are more risk averse than women with respect to medical expenses and therefore purchase health insurance at equivalent rates even though their risk is objectively lower. Men could conceivably be somewhat more risk averse due to prevailing gender roles in the economy: on average it is possible that health problems among men may affect the family’s income more than health problems among women.  Although as an academic I feel I would be remiss in failing to at least mention this possibility, in the end I doubt it amounts to very much. The roles of men and women in the family economy are complex and variegated. And the sources of risk aversion with respect to health are likewise multifold, having a lot to due with individual psychology, family history and family structure. And, of course, it could be that middle aged men are less risk averse than women, in which case the effects of adverse selection are worse.

The data

How do we know about the effects of gender? The graphics below show two studies on the topic. The first is from the Society of Actuaries and was relied on by the Kaiser Family Foundation in its recent study of the effect of age rating. Look at the solid blue (male) and pink (female) lines. (Cute, Kaiser). One can see that until age 18, the costs for men and women in the commercial market has been about the same. By the time we get to, say, age 32, the cost for women is about 2.5 times that for men. The gap then shrinks so that by the time we get to age 58 or so, men’s costs actually start to somewhat exceed women’s.

Society of Actuaries report on gender and healthcare expenses
Society of Actuaries report on gender and healthcare expenses

A study by the respected Milliman actuarial firm, although differing in detail, shows roughly the same pattern. At age 30 or so, female expenses (blue) and about double those of males (green). The gap shrinks until about age 55, at which point male expenses exceed female expenses.  (I’m not sure why Milliman shows female expenses being so much higher than male expenses for the age bracket marked “to 25” unless by “to 25” they mean ages 18-25.)

The_young_are_the_restless__Demographic_changes_under_health_reform_-_Milliman_Insight

Is Gender-Based Adverse Selection Actually Happening?

As to whether the theoretical possibility of gender-based adverse selection is actually materializing, there is yet strikingly little evidence. I have scoured the Internet and found almost nothing on the gender of enrollees. In some sense this is not surprising since, unlike age, on which we have a trickle of data from CMS, which somehow is just unable to compile and release more complete information, gender is completely irrelevant to premium rates. On the other hand, as shown below, the federal application asks about gender, as do a few other state applications such as California, Kentucky and Washington State. So, in theory we should be able to get the information at some point.  In the meantime, if anyone has information on this issue, I would love to see it. What we really need is a breakdown of enrollees based on both age and gender because the ratio’s role varies depending on whether enrollees below age 55 or so are involved or whether enrollees above age 55 are involved.

Two other notes

1. Someone might, I suppose, think that since the role of gender reverses at about age 55, the effects of gender on adverse selection cancel each other out. This would be totally wrong.  If women have higher medical expenses than men up to about age 55 and if women therefore enroll at higher rates, that can cause adverse selection and premium pressures for enrollees of those ages. And if men have have higher medical expenses than women after about age 55 and if men therefore enroll at higher rates, that can cause adverse selection and premium pressures for enrollees of those ages. The effects are cumulative and not offsetting.

2. Does this mean I am opposed to unisex rating? No, not necessarily. First, women face higher medical expenses than men from about 20 to 50 significantly because of childbearing expenses. A family law expert on my faculty confirms what I suspected, which is that there is certainly no routine cause of action by the pregnant female against the prospective father for prenatal maternity expenses. We currently ascribe these expenses to the woman even though a male generally has contributed to those expenses through consensual sex. One could argue that unisex rating offsets this proxy for responsibility.

Second, if there are adverse selection problems caused by unisex rating, they can, in theory, be addressed by programs that that subsidize insurers for female enrollees. Impolitic as it might be to say so, one could treat being a fertile woman as a “risk factor” in the same way that section 1343 of the ACA currently treats medical conditions such as heart disease.  The cost of the subsidies resulting therefrom could be seen as compensating somewhat for the transaction costs of figuring out which childbearing expenses the male partner has contributed to as well as tracking down the male partner and trying to hold him financially responsible.

What I am concerned about, however, is ignoring the issues created by unisex rating. Since it is not currently corrected for by section 1343 of the ACA and corrected for only in a very indirect and partial way by sections 1341 and 1342 of the ACA, there is the potential for the absence of gender rating to destabilize and ultimately shrink the insurance markets in ways that do few people any good. Wishing that a problem would go away or hoping that people don’t see the opportunities to optimize their behavior is seldom a recipe for successful government programs.

 

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Coverage on January 1, 2014 matters

Contrary to the views of some, the number of people who have insurance coverage through the Exchanges as of January 1, 2014, matters to everyone.  It matters because the pool that exists on that date will determine, at least for a while, whether the premiums charged by insurers in the Exchange are likely to be stable and the extent of the federal government’s multiple obligations to subsidize plans purchased on the various Exchanges. It is not as if insurers get a claims paying holiday simply because more and healthier people may enroll later in the year. It also matters because a major point of the Affordable Care Act was to increase in an efficient and relatively painless way the net number of people who have insurance or social protection against significant illness.  If the numbers in the Exchanges and in the expanded Medicaid program do not way more than offset the number of persons who lose their insurance as a result of the ACA, or if the cost of extending health protection in this fashion proves too high, the ACA will not have accomplished its goals.

Given the chaos that has erupted as procrastination strains Exchange infrastructure and deadlines are repeatedly extended, it is difficult to tell right now whether the ACA is performing as hoped. A few things are clear, however. The first thing is that the Obama administration is not releasing the sort of information from which an objective assessment could be made.  Platitudes such as “Millions of Americans, despite the problems with the website, are now poised to be covered by quality affordable health insurance come New Year’s Day,” from President Obama at his last press conference are just not a substitute for knowing how many people have enrolled in the plans in the various Exchanges, and more importantly, have paid for coverage. What are their ages? How about some real numbers as a Holiday present?

Second, the Obama administration is acting as if a large number of enrollees in the aggregate is the measure of success. This is simply not true. Putting aside the problem of it being paying customers rather than mere enrollment that ultimately matters, meeting or exceeding projections in some states does not compensate for deficiencies in many other states.  Because the pools are state-based, Texas insurers and insureds are not helped if enrollment in New York or Connecticut exchanges ultimately equals or exceeds targets. The insurance market in Texas and many other states will still be unstable with some insurers likely pressing for significant premium increases, contemplating withdrawal from the Exchanges, and demanding larger subsidies from the federal government via Risk Corridors and other programs.

Third, even those who have been on the more pessimistic side of matters, must acknowledge that there has indeed been a surge in many state Exchanges and in many states covered by the federal Exchange. On December 11, I wrote: “With a decent last minute kick, it is not unimaginable that California could make 1/3 of its total by the December 23, 2013 deadline and get closer to its ultimate goal by the end of March.” With enrollments at 17,000 per day, California may in fact be there. Colorado, which previously had dismal enrollment numbers, reports 33,356 enrolled as of Monday, which puts it at of the 136,000 projected enrollment for 2014 and 52% of the way towards the Obama administration’s projections for this time of the open enrollment season. (33356/(0.47 x 136000)). Other states such as New York and Connecticut, which previously were doing better than most, have also reported a high pace of enrollment.

Whether that surge has been as large in many other states remains to be seen. Proponents of the ACA like to cherry pick their states with at least as much zest as opponents do. Perhaps both sides share the belief that insurance enrollment is at least much a social phenomenon as a purely economic one. Numbers for large states (with large numbers of uninsureds) such as Texas, Florida, Georgia, Indiana,  Illinois, North Carolina and Florida have yet to report any numbers that I have seen.   And, as mentioned above, even if California and New York and some other states have enrollment sufficient to forestall premium instability and possible entrance into an adverse selection death spiral, that will not greatly help states in which enrollment ends up being less than half of that projected.

Finally, we need to look beyond the last minute holiday rush for health coverage and see what happens between now and March 31, 2014. The carrot of the ACA has basically been eaten for 2014.  If you wanted health care coverage and could afford the prices on the Exchange it made little sense to wait until after the December deadline to acquire it.  This is all the more true given that the President has permitted people to game the system by simply enrolling in a plan now and deciding until January 10, 2014, whether to pay.

Now, however, the first surge is likely over.  Will there be the needed second surge? All that really remains is the stick: the individual mandate tax penalty.  Many people, including me, believe that even before the events of last week, it was too small in 2014 to achieve its goal of inducing enrollment by those in good or average health.  The number of people for whom insurance would not be a good deal at, say, $2,000 a year net but for whom it would be a good deal at (effectively) $1,705 per year ($2,000 – the $295 per person tax penalty) is not likely to be enormous. This is so because ACA premiums often depart greatly from actuarial risk by their prohibition on medical underwriting, accurate age rating, gender rating and their — shall we say — loose enforcement of tobacco rating.

Moreover, with the administration exempting last week upwards of half a million people from the individual mandate, the number of people who need fear the stick got even smaller.  So, yes there are mega-procrastinators or people who have been stymied by the dysfunctionality of various Exchange website in obtaining coverage. There are former skeptics who see their neighbors helped by health insurance coverage under the ACA and who now enroll just as there may be some turned off by whatever problems emerge in administration of the plans.  On balance, I would not be surprised to see modest increases in enrollment between now and the middle of March.  I remain highly skeptical, however, that there will be a second surge equivalent to what has occurred this past week.  As they say, however, only time will tell.

Personal Note

I am enjoying a family vacation in the Colorado mountains this winter holiday.  It’s snowing outside my window as I write this and the beauty of a quiet snowfall can eclipse what may seem so important at other times. So please continue to read ACA Death Spiral periodically, but don’t expect a huge amount of activity for about the next week.  I’m confident we’ll be back exploring issues in the new year.

 

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The Risk Corridor Calculator: How the government plans to use fictitious profits to shovel more money to insurers

Snapshot of the Risk Corridor Calculator
Snapshot of the Risk Corridor Calculator

This is a different kind of blog entry.  There isn’t going to be too much text here. Instead, I want to direct you to a spreadsheet I created (The Risk Corridors Calculator) available on Google Docs and the first (click here to watch it on YouTube) of two videos I’ll be making that explain

(1) how Risk Corridors work under the regulations originally proposed by the Department of Health and Human Services (HHS)

(2) how the insurance industry could lose money notwithstanding Risk Corridors as a result of President Obama changing his mind and conditionally permitting certain insurers for one year to “uncancel” certain  policies that the Affordable Care Act would otherwise have have prohibited starting in 2014; and

(3) how the proposed revisions to the Risk Corridor regulations will shovel money to many insurers and could put them back in the same position they would have been had President Obama not changed his mind.

[Note from 8:32 a.m. 12/6/2014: I discovered a small error in the Risk Corridors Calculator. It has been fixed.  It does not affect anything essential in this blog. Unfortunately, I will need to conform the video to the Calculator, which is likely not to happen until later today. So, if you watch the video today, it is conceptually fine, but just be aware that one of the formulas was off.]

In essence, however, the proposed HHS regulations impute fictitious “profits” to insurers that they then get to subtract from their net premiums.  As a result, it will look to the Risk Corridors program as if the insurer is losing more money in an Exchange plan and therefore entitled to greater government assistance.  (The government has now acknowledged that, although the Congressional Budget Office scored it as costing nothing, Risk Corridors need not be budget neutral.) Another way of thinking about the proposal is that it creates phantom costs that affect the apparent (though not the real) profitability of the insurer and then shovels money to insurers based in part on those phantom costs. It is little different than the government insisting that the insurer lost money due to claims that it actually did not pay and is therefore entitled — even under a formula that is formally unchanged — to greater payments from the government.  Viewed yet another way, it is almost as if the proposed regulations treat what President Obama did as a “tort,” and remedy the wrong by licensing the aggrieved insurers to use contorted accounting to place themselves back in the same position they would have been in had the President not, in effect, interfered with the prospective economic advantage they thought they had in the Exchanges.

Neither this blog entry nor the video will address whether the proposed regulations are permissible as a matter of administrative law or separation of powers. Nor will I explore today whether the regulatory changes can be seen as a necessarily evil. Exposing what is actually going on here, however, must create some serious concerns for all concerned about the rule of law. When section 1342 of the Affordable Care Act (42 U.S.C. § 18062) speaks of “allowable costs,” one would initially think it referred to costs actually incurred by the insurer as a result of running its program. Those costs might be paying claims, paying the electric bill, marketing costs and, perhaps, some reasonable allowance for profit — such as the 3% of after tax premiums actually placed in the original regulations.

But it is going to take some work to show that, by “allowable costs,” the statute meant costs that the insurer did not actually incur in running its program. The burden will be even higher due to the fact that the proposed regulations apparently contemplate varying this heightened profit allowance from state to state. This will be done not in response to different rates of return on capital in the different states, but only to take account of differential losses to insurers caused by different state responses to President Obama’s about-face on whether certain plans that violate ACA requirements could continue to be sold outside of the Exchanges.

In short, the increase in “profit” sure looks like a book-keeping entry whose sole purpose has nothing to do with anything in the statute but is instead designed to restore the insurer to the position it would have been in had federal policy not changed. It is as if the insurers are being given some sort of entitlement to the profits they would otherwise have made and the administration is looking for any term in the statute not glued down (such as an 80% reimbursement rate on certain losses) in order to accomplish this goal.

Fleshing out  more fully these matters of statutory interpretation, separation of powers, and administrative law will be left for later, however, along with a fuller explanation of what is going on inside the Risk Corridor Calculator that I created. For now, play with the spreadsheet and enjoy the video.

Resources

Society of Actuaries, Health Watch: Risk Corridors under the Affordable Care Act — A Bridge over Troubled Waters, but the Devil’s in the Details

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The Two Million Scenario: What if the Affordable Care Act enrolls a lot fewer people in the Exchanges than predicted?

People can be blinded by dreams in many spheres
People can be blinded by dreams in many spheres

Many people who remain basically positive about the Affordable Care Act are viewing the enrollment statistics like the football fan whose team is 2-6 and who point out that the team could win 7 out of its 8 remaining games and still probably make the playoffs.  Yes, getting off to a really bad start doesn’t preclude a happy ending. Success may still be mathematically possible. But unless there’s good reason to think that the fundamental factors such as poor coaching,  poor game plans or unexpected injuries that have led to the bad start no longer apply, the more reasonable prediction is that things will continue more or less as they have.

It’s time to start thinking realistically about what happens if a core component of the Affordable Care Act, subsidized, non-underwritten health insurance available from private insurers, essentially fails to provide many with better access to medical care. This might not happen in every state — there might be a few whose Exchanges can be deemed “successful” — but it is looking more and more to me as if we are heading for enrollments in many states well, well short of that on which the arguments for the ACA were significantly premised. Indeed, some supporters of the ACA have started moving the goal posts, revising history to say that the real goal of the Act wasn’t to reduce the number of uninsureds but to have an actuarially sound pool. (So the purpose of the Act was to help insurance companies stay afloat?) And it hardly helps enrollment when President Obama urges his allies to hold back enrollment efforts so the insurance marketplace does not collapse this coming week under a crush of new users even after he earlier assured the nation  healthcare.gov  was supposed to be working much better by this time.

For purposes of this blog entry, I’m going to assume that enrollment in the Exchanges ends up being about 2 million for 2014 instead of the projected 7 million.  I can’t rigorously justify that number — but, of course, neither could the pundit who is now saying 4 million. And, if I had time and space I’d prefer to do this analysis under a variety of scenarios, but, for now, the 2 million figure feels about right. And if I were betting on which side of the 2 million we will fall, it would be the lower side. What are the consequences? I can’t address all of them in a single blog entry — and trying to predict matters past 2014 gets very treacherous — but here are some.

And, for those of you who don’t want to read further, here’s the headline:

Insurance sold through Exchanges without medical underwriting — a central promise of the Affordable Care Act — is likely to implode in a significant number of states by 2015 while limping along in several others but providing little net desired decrease in the number of people without quality health insurance.  The silver lining in this failure will be that the program will likely cost less than projected due to fewer number of people receiving subsidies, although this reduction will be partly offset by higher-than-projected subsidies to the insurance industry. Expect significant pressure to grow among supporters of the Affordable Care Act to use these net savings to increase the subsidies available to people buying coverage through the Exchanges and to lure insurers in the problem states back into the Exchanges.

1. The number of people without private health insurance may actually grow

This is so because, if 2 million obtain insurance through the Exchanges but more people (3.5 million is a prevailing estimate from sources ranging from Forbes to Jonathan Gruber) lose their current individual health insurance, that’s a net decrease in the number of insured.  And if we add in the loss of 100,000 or so people from the Pre-Existing Condition Insurance Plan that likewise is terminated or those who heretofore were in various state high risk pools, there is a serious risk that the Affordable Care Act will have decreased the number with private health insurance.

In fairness, I have not taken Medicaid expansion into account. Some may see it as unfair to count just the number of people with private health insurance rather than the number with access to health care through private insurance or public schemes such as Medicaid. And, indeed, in those states in which Medicaid has been expanded — one can’t blame President Obama too much if other states choose not to participate — enrollment has outpaced enrollment in private plans at about a 4-to-1 ratio. This suggests, by the way, that people are willing to use a web site, even some clunky ones, to sign up for health care if they think the price is right.

The rejoinder to the argument that we should consider Medicaid, however, is that an awful lot of political energy and an awful lot of monetary investment has been predicated on healthcare reform benefiting more than just the poor but the middle class too. If it turns out the middle class has, net, been hurt by the 2014 features of Affordable Care Act or has paid a large investment for the 2014 features of a law that, net, does provide little marginal benefit, it’s fair to criticize the 2014 features of the Act for their architectural shortcomings. And, yes, I know all about staying on your parents’ policy until you are 26 and limitations on rescissions, but none of those pre-2014 “achievements” should count in assessing the 2014 record.

2. The number of people with quality health insurance may stay about the same

Yes, there will be people who formerly had no health insurance or who had rotten health insurance who, thanks to the 2014 aspects of the ACA, now have health insurance that covers more.  There are many news accounts from pro-ACA forces providing evidence of this. Here’s one (although all the “success stories” are likely to have high medical claims); here’s another (notice again that the successes are likely to have high medical claims).

But it may well be that for every such success story apparently to be catalogued by paid grants from the government, there is another who had health insurance tailored to their needs (such as policies for the 50 and over set that did not cover maternity expenses) who now find themselves priced out of the health insurance market with its Essential Health Benefits requirement (section 1302 of the ACA). Here’s a website inviting people to post their cancellation notices.  Here are some anecdotes relating such problems (although one always have to be very careful about exaggerations in this arena; see here for a discussion of a particular case by Consumer Reports).  Here’s another.

On balance, though, it’s quite believable that, many of the gains due to subsidization may be offset due to government offering only products that have more “features” than many people are willing to pay for.  To analogize, consider a law that prohibited people from owning either a clunker car (defined somehow) or a car without four-wheel drive. The theory behind the law was that clunkers were unsafe and that four-wheel drive is sometimes useful: even if you don’t need it right now, you might need it or have needed it at some point.  Fair enough. But such a law might not actually increase the number of people driving quality cars that fit their needs. Some people just can’t afford a new car.  And others, who could afford a respectable car without four wheel drive and didn’t think they needed it right then (urban Floridians, for example), might simply decide not to get a car rather than use scarce marginal dollars for cars with features they don’t need. While such a result need not occur — it depends on all sorts of factors — my sense is that this is where we are heading with the Affordable Care Act and its fairly demanding and undifferentiated requirements for coverage in policies sold on the Exchanges.

3.  Federal mandate tax payments may be a little bit bigger than expected for 2014

The Congressional Budget Office estimates this spring that the United States Treasury would receive about 2 billion dollars as a result of the individual mandate tax (26 U.S.C. § 5000A). That figure was premised, however, on a belief that 7 million people would enroll in the Exchanges.  If only 2 million people get insurance through the Exchange that’s roughly 5 million fewer than anticipated who will not. There thus could be as many as 5 million more people who will have to pay the individual mandate (26 U.S.C. §5000A) and could lead to something like another $500 million in revenue next year.

Before we spend the money of 5 million more Americans who might have to pay extra in tax, however,  we need to we need to subtract off two categories of people.  (1) We should subtract off those who acquire faux-grandfathered policies created by President Obama’s recent turnabout to let people who like their (potentially cruddy) coverage keep it under some circumstances and not have to pay the individual mandate.  (2) We should subtract off the small number of people who were projected to purchase policies on the Exchange but, because of poverty or otherwise, would not have had to pay the mandate tax had they failed to do so.

So, let’s say on balance that 3 million fewer people than projected pay the tax under 26 U.S.C. 5000A. It’s hard to know exactly what sort of tax revenue would be involved, but it is likely in excess of $285 million per year because each such person would have been responsible for at least a $95 per person penalty. (I know, I know, there are lots of complications because the penalty is difficult to enforce and because you only have to pay half for children, but then there are complications the other way in that $95 is a floor and one may have to pay 1% of household income). Why don’t we use round numbers, though, and say that the government might get about $300 million more in tax revenue for 2014 (although they may not get the money until 2015) due to lower-than-projected enrollments in the Exchanges.

4. Before the federal government subsidizes them, insurers in the Exchange will lose billions

4. Before consideration of various subsidies (a/k/a bailouts) of the insurance industry created by the Affordable Care Act, insurers could lose $2 billion as a result of having gambled that the Exchanges would be successful.  Here’s how I get that figure. No one knows for sure but, if the experience under the PCIP plan is any guide, when about 1/3 of the projected number of people apply to a plan that is not medically underwritten, expenses per person can be more than double that originally expected.  Even if we assume that experience under the PCIP is not fully applicable, given an enrollment 1/3 of that projected, it would shock me if covered claims were not at least 125% of that expected. If so, on balance that means that losses per insured could total roughly $1,000. If we multiply $1,000 per insured by 2 million insureds, we get about $2 billion. If the Exchanges lose money at the same rate as the PCIP, insurer losses could be upwards of  $7 billion. Again, I make no pretense of precision here. I am simply trying to get a sense of the order of magnitude.

5. The federal government will subsidize insurers more than expected but insurers will still lose money

The Affordable Care Act creates several methods heralded as protecting insurers writing in the Exchanges from claims that were greater than they expected.  One such method, Risk Corridors under section 1342 of the ACA, could end up helping insurers in the Exchanges significantly. But, if, as discussed here, enrollment in the Exchanges for 2014 is 2 million persons, the cost of helping the insurance industry in this fashion will be another $500 million for 2014. Risk Corridors, which have recently been aptly analogized to synthetic collateralized debt obligations (CDOs), requires the government to reimburse insurers for up to 80% of any losses they suffer on the Exchanges.  It also imposes what amounts to a special tax (again of up to 80%) on profits that insurers may make on the Exchanges. The system was supposed to be budget neutral but, as I and others have observed, will in fact require the federal government to pay money in the event that insurer losses on the Exchange outweigh insurer gains. The basis for my $500 million computation is set forth extensively in a prior blog entry. It will only be more if, as discussed in another prior blog entry, the Obama administration modifies Risk Corridors to indemnify insurers for additional losses they suffer as a result of President Obama’s decision to let those with recently cancelled medically underwritten health insurance policies stay out of the Exchanges.

If claims are, as I have suggested 25% higher as a result of enrollment of 2 million, insurers will lose, after Risk Corridors are taken into account, about 9% on their policies. It would thus not surprise me to see insurers put in for at least a 9 or 10% increase on their policies for 2015 simply as a result of enrollment in the pools being smaller than expected.

The relatively modest 9% figure masks a far more significant problem, however.  It is just a national average. Consider states such as Texas in which only 2,991 out of the 774,662 projected have enrolled thus far.  If, say, Texas ends up enrolling “only” increasing its enrollment by a factor of 16 and gets to 50,000 enrollees, I would not be surprised to see claims be double of what was projected.  Even with Risk Corridors, insurers could still lose about 24% on their policies. A compensating 24% gross premium increase, even if experienced only by that portion of the insurance market paying gross premiums, could well be enough to set off an adverse selection death spiral.

Footnote: For reasons I have addressed in an earlier blog entry, one of those methods, transitional reinsurance under section 1341 of the ACA is best thought of as a premium subsidy that induces insurers to write in the Exchanges. Because the government’s payment obligations are capped, however, the provision is unlikely to help them significantly if the cost per insured ends up being particularly high throughout the nation.

6. The federal government might save $19 billion in premium subsidies

The Congressional Budget Office assumed that premium subsidies would be $26 billion in 2014, representing a payment of about $3,700 per projected enrollee.  If the distribution of policies purchased and the income levels of purchasers are as projected, but only 2 million people apply, that would reduce subsidy payments down to $7.5 billion.  And if the policies sold in 2014 cost a little less than projected, that might further reduce subsidy payments.  I think it would be fair, then, to estimate that low enrollment could save the federal government something like $19 billion in premium subsidies in 2014. This savings coupled with heightened tax revenue under 26 U.S.C. §5000A — could we round it to $20 billion — would be more than enough to cover insurer losses resulting from the pool being smaller and less healthy than projected.

The Bottom Line

I suspect my conclusion will make absolutist ideologues on the left and right equally uncomfortable.  What I am wondering is if the Affordable Care Act might not die in 2015 with a giant imploding bang but rather limp on with a whimper. On balance, what we may well see if only 2 million enroll in Exchanges pursuant to the Affordable Care Act is a system that fails to function in some states and remains fragile and expensive elsewhere. On the one hand, it will be an expensive system because of the enormous overhead incurred in creating a highly regulated industry that provides assistance to a relatively small number of people. On the other hand, precisely because it will be helping far fewer people than projected, it might well cost significantly less  than anticipated. I would expect this departure from what was projected to lead to two sorts of pressures:

(1) There will be a claim from ACA supporters that we can use the savings to increase subsidies or the domain of the subsidies beyond the 400% of Federal Poverty Line cutoff  and thereby reduce the adverse selection problem that will already be manifesting itself.

(2) There will be a claim from ACA detractors that all of this confirms that, apart from ideological considerations, the bill is an expensive turkey and that, if  the only way to save it is to impose more and more regulation and spend more and more money, it ought simply to be repealed.

Complicating factors

Rules

There are many factors that could result in the estimates provided in this entry being quite wrong.  I do not want to fall into the same trap as others who have ventured into this field and claim that there are not very large error bars around all of these numbers.  And I do not believe the system is necessarily linear. It may be that small changes have cascading effects. Here are several reasons my estimates might be wrong.

1. The rules change in 2015. There are at least three significant rule changes in 2015.

a. The tax under 26 U.S.C. 5000A for not having government-approved health insurance increases significantly, going from the greater of $95 per person or 1% of household income to the greater $295 per person or 2% of household income. Insurers may therefore assume that enrollment will be greater in 2015 than in 2014.  Some people will be pushed over the edge by the higher tax rate into purchasing health insurance. If so, insurers may feel less pressure to increase prices because they believe their experience in 2014 will not be repeated in 2015.

b. The employer mandate will presumably not be delayed again by executive order which may have two offsetting events: employers reducing the number of full time employees thereby adding more to the Exchanges or employers maintaining health insurance thereby reducing the potential pool for the Exchanges.

c. As discussed in an earlier blog entry, there will be a decline in transitional reinsurance now provided free to insurers in the Exchange which, in and of itself, will put significant pressure on premiums

Realities

Finally, this is a field where events just frequently overtake predictions.  All of these predictions go out the window, for example:

a. if there is a major security breach in the government computer systems and people’s personal information is disclosed;

b. healthcare.gov continues to seriously malfunction during the critical pre-December 23 sign up period

c. if the yet-to-be-built payment system for insurers does not function and people become dissatisfied as a result;

d. if people find, as some are projecting (here and here), that the set of medical providers available in the Exchange policies is drastically reduced over what they expected; and

e. there is a major sea change in legislative power in Washington.

f. other

 

 

 

 

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What happens if just some states enter the death spiral?

The Affordable Care Act does not establish a uniform national pool for persons purchasing Bronze, Silver, Gold and Platinum policies on the Exchanges. Rather, it creates at least one such pool for each of the states involved in the program .  And that is true even if multiple states use the same “Exchange” — the one in Washington D.C. — to establish coverage.

This fracturing of the pool and of the administrative apparatus creates an architectural problem: what happens if, as may well be the case, insurers in the Exchanges muddle through in a few states but suffer massive losses in many others? Most likely, insurers in the problem states will exit from the Exchanges or require significant premium hikes on top of rates that already give many potential customers sticker shock. But this reaction by profit-motivated insurance companies could lead more Americans to complain that imposition of a uniform individual mandate tax under 26 U.S.C. § 5000A throughout the nation is unfair. And, if the increases are large enough and a large enough number of people stick with the Exchanges — because they don’t see another choice — this  could increase the cost of premium subsidies to the federal government and its taxpayers beyond the substantial numbers already projected.

The key point I want to make here is that even the best and brightest people often fall into the trap of thinking that the Affordable Care Act Exchange-based system for reducing the number of uninsureds will either succeed or fail.  Either the system will fall into an adverse selection death spiral or it will not. Perhaps that is the case. But this binary thinking probably is not right.  It’s kind of like quantum physics: the Exchanges could both succeed and fail at the same time.  It just depends what state you’re in. (Physics pun intended).

Here’s how. Although it is too early to tell for sure — and the persistent failure of healthcare.gov and many of the state exchange sites such as Maryland and Oregon hinders augury — it looks as though the Affordable Care Act is having somewhat more success in some states than others. Proponents of the ACA like to point to California experience where it is claimed that 70,000 people have made it through at least some more advanced state of the enrollment process.  The gloomy point to Oregon where apparently no one has successfully enrolled or Texas, which, despite having the largest number of uninsureds, had only 2,991 enrolled in a plan last time anyone counted. (Here’s the handy chart in the Washington Post.) Both the optimistic and pessimistic point to Kentucky where the number of enrollees is proportionately higher than in many states but in which the population of insureds seems disproportionately old.

So, in a few months it could be that Exchange insurance in some states such as California where the technology has worked better and the political environment is more sympathetic to the ACA is able to persist into 2015 without major rate hikes or insurer withdrawals. In those states, there remains some considerable logic to imposing a tax of what will be 2% of household income or roughly $325 per household member (kids count as half) for failure to buy health insurance.  But what might we do in states such as Texas or Mississippi or West Virginia or perhaps many others where the insurers experience severe adverse selection that even Risk Corridors (42 U.S.C. § 18062) is unable to cure adequately? If the result is, as one would expect, a reduction in the number of insurers continuing to participate in the Exchange and an increase in rates, the Affordable Care Act is likely to become even less popular in those jurisdictions.  This would be all the more true for those people — a small group, but still people nonetheless — whose income is such that the rates remain less than the 8% of household income level that would otherwise excuse them under 26 U.S.C. § 5000A(e)(1) from having to buy the expensive policies.

Fixing such a problem will be extraordinarily difficult. If Congress remains in gridlock with some finding the ACA so abhorrent that reform of even its worst excesses is unacceptable and others divided on the merits of any particular reform, Congress will have little ability to address the genuine problems of those in the failure states.  And would Congress be willing to write a statute that excused people in some states from paying an individual mandate tax while insisting that it continue in others? What criterion would be used to distinguish the tax paying from the tax exempt states?  If Congress tries, expect some heavy duty litigation on the constitutionality of such a non-uniform tax: “all Duties, Imposts and Excises shall be uniform throughout the United States.” (U.S. Constitution, Article I, Section 8, clause 1). Would Congress be willing to adjust “Risk Corridors” or “Risk Adjustment” (section 1343 of the ACA) to give special preference to insurers in states whose Exchanges have effectively failed? If Congress can not relieve the difficulties of the death spiral states, expect pressure to grow yet further for repeal of the entire law.

Again, we are left with a design problem in the Affordable Care Act.  Blinded by the dream of reducing the number of uninsureds and providing healthcare to a broader segment of American society, it creates a system in which, conceivably, under just the right circumstances it might work, but in which even small departures from desired assumptions risk plunging that system into a “basin of attraction” aptly known as “the death spiral.” We end up torn asunder in a black hole of insurance market failure from which there is no escape. Worse, it is constructed in a way such that state-by-state adjustments, even with a less dysfunctional Congress, will prove difficult indeed.

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