Tag Archives: risk corridors

Insurer losses in Exchanges of 10% not unlikely

Experts who have taken a look at the Affordable Care Act have separately considered the effects of three possible sources of unexpected losses by insurers selling policies in the individual Exchanges: purchasers being older than originally projected, more purchasers being women than originally projected, and purchasers having poorer health than originally projected.  And, at least with respect to the potential for age-based problems, the prestigious Kaiser Family Foundation has given supporters of the ACA considerable comfort by saying, worst case, older purchasers might result in only a 2.5% increase in insurer costs.  But no one to my knowledge — until now — has carefully considered the combined effects of these three sources of potential cost increases and, most likely, pressure for future premium increases.

I have now made an effort to consider the effects of these three sources of insurer losses acting together. Based on that effort, which represents the culmination of work over the past month, I believe it quite possible that insurer losses could amount to 10%, approximately 4% due to purchasers being older than expected, 1% due to greater purchases by women, particularly those in their 20s and 30s, and another 5% due to purchasers having poorer health than expected.

There are four major caveats that should be emphasized up front.  (1) These figures are estimates with large error bars; and anyone pretending to great exactitude in this field, particularly as much of the best data is not yet available, is, I suspect, likely pursuing more of a political agenda than a scholarly one. Losses could be close to zero; losses could be in the 15% range. Still, as I am going to show, significant losses are a serious possibility. (2) These losses are computed without consideration of “risk corridors” under section 1342 of the Affordable Care Act. That provision basically calls on taxpayers to pay insurers losing money on the Exchanges a significant subsidy. After consideration of Risk Corridors, average net insurer losses could range anywhere from close to zero to around 6%-7%. (3) These are national figures.  There are states such as West Virginia in which the age distribution is considerably worse right now than it is nationally.  One should not expect any of the rates of insurer losses (or profits) to be uniform across states or, indeed, across insurers. The figures developed here are an attempt at a  rough average. (4) The figures are based on the last full release of data by HHS on enrollment in the Exchanges; if matters change and, for example, the proportion of younger enrollees grows or the proportion of men grows, the loss rates I project here are likely to decline.

The graphic below summarizes my conclusions.  It shows insurer losses (or gains) as a function of a “health age differential” under two scenarios. By health age differential I mean the difference in ages between someone who has the expected health expenses of the actual enrollee and the chronological age of the enrollee.  Thus, if an enrollee was actually 53 but had the health expenses of an average 57 year old, their health age differential would be 4.  If they had the health expenses of a 50 year old, their health age differential would be negative 3. The yellow line shows insurer losses as a function of the health age differential assuming that the joint distribution of gender and age stays the way it was when HHS last released data.  The blue line shows insurer losses as a function of the health age differential assuming that the joint distribution of gender and age ends up the way it was originally projected to be.  As enrollment under the ACA increases and the proportion of younger enrollees increases, one might expect the ultimate relationship to head from the yellow line down to the blue line.  My assertion that losses could well be 10% is based on the assumption that the joint distribution of gender and age stays the way it is now but that the health of enrollees is equivalent, on average, to those 2 years older than their chronological age.  An assumption that enrollees could have health equivalent, on average, to those 4 years older than their chronological age, yields insurer losses of greater than 15% assuming the current joint distribution stays in place and about 10% assuming the original distribution ends up being correct.

The key graphic for this entry
 

The graphic above is useful because it gives what hitherto had been missing in discussions of problems in the individual Exchanges: some sense of the relative magnitude of problems created by age-based adverse selection (older people enrolling disproportionately) and health-based adverse selection (sicker people enrolling disproportionately). Roughly speaking, the degree of price increases induced by the current age and gender imbalances is roughly equivalent to what would occur if the health of the enrollees was, on average, equivalent to those of persons 2.5 years old than they actually are.

So what does it all mean?

At some point,  a journalist is likely to ask me what this all means?  Is there going to be a death spiral?  I would say we are right on the cusp.  Losses of 10% by insurers relative to expectations, coupled with whatever increase results from medical inflation, isn’t so enormous that I could say, yes, for sure we are heading into a death spiral. But neither is it such a small number that the risk can be ignored.  Moreover, as noted above, the 10% figure is a national average and we need to reduce it because of risk corridors.  In some states, however, where the age and gender figures may be worse or the health of enrollees is particularly problematic or where insurers just bid too low and the winner’s curse overtakes them, I still believe there is a substantial risk of a serious problem. In other states, where age and gender figures are better or insurers more accurately forecast the health of their enrollees, the risk of a death spiral is minimal. And, of course, the more people that actually end up purchasing policies in the Exchanges over the next few months, regardless of whether they come from the ranks of the previously uninsured or those who find that they can not keep their current policies, the more stable the system of insurance created by the ACA is likely to be.

So, after a lot of research, I feel more confident than ever in giving a lawyer’s answer —  it all depends — and a cliche — we’re not out of the woods yet.

Computation details

The results obtained here are based on essentially the same data as user by the Kaiser Family Foundation, which includes data on the relation between age and premium under typical plans, data from the Society of Actuaries (SOA), also used by Kaiser, on the relation between gender, age and expected medical expenses, and my own prior work attempting, based on data from the Department of Health and Human Services released earlier this month, to derive a joint distribution of enrollment in the individual Exchanges based on age and gender.  And, although the math can get a little complicated, the basic idea behind the computations is not all that difficult. It is essentially the computation of some complicated weighted averages.  Each combination of gender and age has some expected level of insurance cost (computed by the Society of Actuaries based on commercial insurance data) and some expected premium (computed by Kaiser based on a study of the ACA). Thus, if we know the joint distribution of gender and age, we can weight each of those costs and each of those premiums properly.

There are three areas of the computation that prove most challenging.  First, because HHS has not released all of the needed data, one must develop a plausible method of moving from the marginal distributions that were provided by HHS on enrollment by age and enrollment by gender into a joint distribution by gender and age. Second, one must calibrate the SOA cost data and the Kaiser premium data, which are expressed in somewhat different units,  such that, if the joint distribution of gender and age was as was originally expected an insurer would just break even.  And, third, one must develop a reasonable method of modeling insured populations that are drawn disproportionately from persons who have higher medical expenses. I believe I have now come up with reasonable solutions to all three issues.

Solution #1

The solution to the first issue, moving from a marginal distribution to a joint distribution, was detailed in my prior blog entry. In short, one finds a large sample of possible joint distributions that match the marginal distributions and scores them according to how well they match the property that people who are subsidized more likely to enroll.  One takes an average of a set of solutions that score best. There is an element of judgment in this process on the degree to which individuals respond to subsidization incentives and, all I can say, is that I believe my methodology is reasonable, avoiding the pitfall of thinking that subsidization is irrelevant or of thinking that it is the only factor that matters in determining enrollment rates. I present again what I believe to be the most likely joint distribution of enrollment by gender and age.

Plausible age/gender distribution of ACA enrollees
Plausible age/gender distribution of ACA enrollees

Solution #2

The solution to the second problem is obtained using calculus and numeric integration. One computes the expected costs and expected premiums given the original joint distribution of enrollees, which is taken to be a product distribution of which one distribution is a “Bernoulli Distribution” in which the probability of being a male or female is equal and the other is a “Mixture Distribution” in which the weights are those shown below (and taken from the  Kaiser Family Foundation web site) and the components are discrete uniform distributions over the associated age ranges.

Original estimate of age distribution of enrollees
Original estimate of age distribution of enrollees

The Society of Actuary data on the relationship between age, gender and medical costs is shown here.

Society of Actuaries data on gender, age and commercial insured expense
Society of Actuaries data on gender, age and commercial insured expense

The premiums under the ACA are shown here.

ACA Premiums
ACA Premiums

These two plots combined can give us a subsidization rate plot by gender and age.  It is shown below along with an associated plot showing the distribution of enrollees by age as was originally assumed and as appears to be the case.

Subsidization rates by gender and age along with anticipated and current age distribution of enrollees
Subsidization rates by gender and age along with anticipated and current age distribution of enrollees

Solution #3

To model adverse selection based on expensive medical conditions, I simply added a health age differential to the insureds.  That is, in computing expected medical costs, I assumed that people were their actual age plus or minus some factor.  (Ages after this addition were constrained to lie between 0 and 64). The graphic above showed insurer losses as a function of this “health age differential” under two scenarios.

Technical Note

A Mathematica notebook containing the computations used in this blog entry is available . here on Dropbox. I’m also adding a PDF version  of the notebook here. I want to thank Sjoerd C. de Vries for coming up with an elegant method within Mathematica of describing the joint distribution used in the computations of various integrals.  I am responsible for any mistakes in implementation of this method and my use of Mr. de Vries idea implies nothing about whether he agrees, disagrees or does not care about any of the analyses or opinions in this post.

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Obama administration shocking decision to drop individual mandate — but only for some

I’m going to have to wait until tomorrow to say much more, but the Obama administration issued a shocking decision late today to exempt those who had individual policies cancelled this year from the individual mandate contained in the Affordable Care Act.  The Wall Street Journal apparently broke the story.  Here is the New York Times article.  Here is a Washington Post article from a strong Affordable Care Act supporter. Here is the Huffington Post article. Here’s Fox News. (CNN has yet to publish anything I can find on the subject) Not surprisingly, the insurance industry has already protested the apparent move. “This latest rule change could cause significant instability in the marketplace and lead to further confusion and disruption for consumers,” said Karen Ignagni, president of America’s Health Insurance Plans, the industry’s main trade group.

A copy of the decision, made thus far only in a letter from Secretary Kathleen Sebelius to six senators (all of whom are apparently facing tough re-election battles) is here.

Excerpt from Sebelius letter to senators
Excerpt from Sebelius letter to senators

Legality

The purported legal basis for the exemption comes in 26 U.S.C. 5000A(e)(5), which reads:

(e) Exemptions

No penalty shall be imposed under subsection (a) with respect to— …

(5) Any applicable individual who for any month is determined by the Secretary of Health and Human Services under section 1311 (d)(4)(H) to have suffered a hardship with respect to the capability to obtain coverage under a qualified health plan.

The Obama administration is now apparently interpreting having to comply with the mandate itself — but only after one’s individual insurance policy was cancelled — as the requisite hardship. A prior regulation issued on July 1, 2013, by HHS had taken a narrower view of what the requisite hardship was:

(g) Hardship—(1) General. The Exchange must grant a hardship exemption to an applicant eligible for an exemption for at least the month before, a month or months during which, and the month after, if the Exchange determines that—
(i) He or she experienced financial or domestic circumstances, including an unexpected natural or human-caused event, such that he or she had a significant, unexpected increase an essential expenses that prevented him or her from obtaining coverage under a qualified health plan;
(ii) The expense of purchasing a qualified health plan would have caused him or her to experience serious deprivation of food, shelter, clothing or other necessities; or
(iii) He or she has experienced other circumstances that prevented him or her from obtaining coverage under a qualified health plan.

I look forward to hearing from others, and in particular from people with a commitment to the rule of law who previously have supported the ideas behind the ACA, but it is not clear to me that any of the pre-existing bases contained in this regulation for claiming a hardship exemption would apply to having a predicted cancellation in one’s individual insurance policy. Maybe at this late hour there are arguments and other documents I am not considering. Surely, however, the existence of the ACA itself can not be the human-caused event creating the hardship. Moreover, I have trouble seeing how the cancellation of a plan makes it more difficult for these individuals — as opposed to others in similar circumstances — from obtaining coverage under a qualified health plan.  I can well imagine cynics saying that the only real hardship involved here is having believed President Obama when he said that if you liked your health plan you could keep it and thus not having saved up for the higher prices that often exist in policies with “Essential Health Benefits.” Of course, if , as the Obama administration has claimed, many of these cancelled policies were junk that the policyholder should be glad to be rid of, it becomes yet more challenging to see much of a hardship at all in being offered real insurance coverage with all of its greater benefits.

In any event, it does not take a fertile imagination to foresee legal challenges to this limited exemption from those not fortunate enough to have had health insurance in the past but who are not being given a similar exemption from the individual mandate. I can easily see challenges based on failures of administrative procedure and equal protection.

The Death Spiral

I and others will need to think hard about the issue of magnitude. Obama administration officials are reported as having stated at a briefing that all but 500,000 of those with canceled policies will be enrolling in policies under the Exchange. This claim, however, is impossible to reconcile with existing enrollment statistics and assertions that millions of individuals have had their individual policies cancelled.  It is difficult to see how this decision would not exacerbate at least somewhat the risk of an adverse selection death spiral overtaking the Exchanges in many states.  The tax created by the mandate has always been justified as necessary to induce people of low or moderate risk to join those of higher risk in purchasing policies on the Exchange. By now exempting perhaps millions of people from this requirement — and, in particular, people who are most likely to have satisfied medical underwriting in the recent past — the Obama administration decision will likely diminish enrollment, at least somewhat, in the insurance Exchanges and, correlatively increase price pressures and insurer losses during 2014. To the extent that insurers systematically lose money as a result of this apparent decision, the federal government will be spending millions more — perhaps hundreds of millions more — in payments under the Risk Corridors program.

Implications

There’s one more implication we need to think about.  Although experts vary greatly on the magnitude, clearly a number of small businesses are going to lose their health insurance policies this coming year for failure to conform to the new ACA requirements.  This is the “second wave” that is sometimes spoken about. Are the significant number of employees and dependents who are thus subject to a risk of loss of coverage likewise going to receive an exemption from the individual mandate?

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Phantom costs: The lawless proposal to buy off the insurance industry via a “fix” to Risk Corridors

In my last blog post, I began to explain the proposed “fix” to the Risk Corridors program that the Obama administration seeks to achieve through modifications of its regulations. This is the provision of the Affordable Care Act under which the federal government reimburses large proportions of money lost by insurers over the next three years selling insurance to individuals in the Exchanges or to small employers.  Originally thought by many to be budget neutral, if, as appears increasingly possible, insurers on average lose significant money in the Exchanges, Risk Corridors could cost the federal government hundreds of millions of dollars or more.

I also suggested in that prior blog post that the “fix” raised serious concerns about the rule of law and separation of powers.  In this post, I want to follow up and explain further the accounting trickery and word play in which the administration is engaged and why it is not authorized by any law passed by Congress. Basically, the proposed changes in the regulations amount to an illegal pay off to the insurance industry so that they do not exit the Exchanges after having had the rug pulled out from under them by another decision not to enforce the law as written.

In sum, the Obama administration is proposing without any statutory authorization to let insurers increase the amount they get from the federal government under the Risk Corridors provision of the Affordable Care Act by treating as a “cost” money that the insurers have not spent and that can not be fairly said to be a cost of doing business.  The Obama administration makes this use of phantom costs appear more palatable by terming it “profit” and likening it to an opportunity cost of capital. But the increased “profits” the Obama administration now seek to permit insurers to subtract as a cost has completely detached itself from anything to do with real opportunity costs of running a business. The Obama administration would have been equally dishonest had they permitted insurers to place triple their rent on their Risk Corridor accounts and term the extra 200% a cost of business that entitled them to yet more money from the government. The proposed regulations should be seen as unlawful as an attempt by the Executive branch to change hard percentages used in the statute such as  80% into 95% simply because the Executive thought it better balanced the interests at stake.

Background

The fundamental problem stems from the divergence between what the President repeatedly told Americans during his presidency — if you like your health care plan, you can keep it — and what the Affordable Care Act (a/k/a Obamacare) really said, particularly as it ended up being implemented by the President’s own executive agencies (here and here). The insurance industry acted as if the rule of law mattered, not the campaign rhetoric or people’s perceptions of it, and set its prices in the healthcare Exchanges in accord with the law and the administration’s own forecasts of its effects on competing policies otherwise available to healthy people.  So, when the President announced on November 14, 2013, that his administration would conform the law to his rhetoric and public expectations (by declining under certain circumstances to execute sections 2701-2709 of the Public Health Service Act as modified by the Affordable Care Act), the insurance industry had a fit. It appropriately warned the President that, by reviving competitive sources of health insurance for some of their healthiest potential insureds, he was destabilizing the insurance markets. And, since the keystone of the President’s signature piece of legislation, the Affordable Care Act, depends on happy private, profitable insurers, this was a warning the President and his executive agencies had to heed.  Instead of backing down on the November 14, 2013 announcement, the President doubled down on regulatory change. This past week the Department of Health and Human Services proposed in the Federal Register how current Risk Corridor regulations might be amended to give insurers relief.

A Quick Look at the Statute

For ready reference, here’s an excerpt of the key part of the Risk Corridors statute in question.  You can try to read it now or refer to it periodically as you progress through the remainder of this blog entry.

(b) PAYMENT METHODOLOGY.—
(1) PAYMENTS OUT.—The Secretary shall provide under the
program established under subsection (a) that if—
(A) a participating plan’s allowable costs for any plan
year are more than 103 percent but not more than 108
percent of the target amount, the Secretary shall pay to
the plan an amount equal to 50 percent of the target
amount in excess of 103 percent of the target amount;
and
(B) a participating plan’s allowable costs for any plan
year are more than 108 percent of the target amount,
the Secretary shall pay to the plan an amount equal to
the sum of 2.5 percent of the target amount plus 80 percent
of allowable costs in excess of 108 percent of the target
amount.

The Federal Register Proposal

The fundamental idea in the new Risk Corridors proposal is to put the insurers back in the same position they would have been in had the non-enforcement announcement (“the transitional policy”) not been made.One can see this point made repeatedly in the Federal Register proposal:

Therefore, for the 2014 benefit year, we are considering whether we should make an adjustment to the risk corridors formula that would help to further mitigate any unexpected losses for issuers of plans subject to risk corridors that are attributable to the effects of the transition policy. (78 FR 72349)

We are considering calculating the State-specific percentage adjustment to the risk corridors profit margin floor and allowable administrative costs ceiling in a manner that would help to offset the effects of the transitional policy upon the model plan’s claims costs. (78 FR 72350)

Although the adjustment that we are considering would affect each issuer differently, depending on its particular claims experience and administrative cost rate, we believe that, on average, the adjustment would suitably offset the losses that a standard issuer might experience as a result of the transitional policy. (78 FR 72350)

Two clearly illegal ways to “fix” the problem

The problem the administering agency (Health and Human Services) faces, however, is how. How does HHS “suitably offset the losses that a standard issuer might experience as a result of the transitional policy?” One simple way might have been to adjust the reimbursement percentages contained in the statute, changing them from 50% and 80% for different levels of losses to higher levels. The problem is that the statute (42 U.S.C. § 18062) specifically sets forth the 50% and 80% reimbursement percentages and it would challenge even the most fertile imaginations to contend that it was within the province of an administrative agency to interpret those, as, say, 70% and 95%. And in the current gridlock — and with proposals to repeal Risk Corridors circulating —  getting such a proposal through Congress would seem impossible.

Alternatively, the administration might have made the insurers whole by adding state-by-state constant terms to the formula for reimbursement that roughly approximated the amount a typical insurer might lose in that state. Again, though, that would just constitute a statutorily unauthorized give away of federal taxpayer to the insurance industry.  Congress did not authorize payments so that insurers could maintain the same profits they would have earned in an alternative regulatory environment; instead Congress attempted to compress the profits and losses of insurers based on the regulatory environment that they in fact were in.

The “fix” suggested by the Federal Register proposal: what’s the difference?

What I now want to persuade you of, however, is that, after one strips away the confusing accounting, the Federal Register proposal, in its essence, amount to the same thing as these clearly unauthorized alternatives.  They are, in effect, a coverup for a giveaway of government money. The are very much the assumption of legislative powers by the executive branch of government.

The conceptual problem

One can almost see the problem without doing the math. The very objective set forth repeatedly in the Federal Register proposal — of putting the insurer back into some alternative financial condition, almost as if the government had taken their property or committed a tort by changing the rules — is nowhere to be found in the Risk Corridors statute. Section 1342 speaks of real premiums earned and real costs incurred and looks at their ratio in order to determine federal aid to insurers writing in the Exchanges. That perspective is echoed in the initial regulations published in the Federal Register months before the “transitional policy” brouhaha broke out. The definitions of critical terms adopted in those regulations speak of costs “incurred” or the “sum of incurred claims” or “premiums earned.” (See note below on definitions). Moreover, the definitions are nationwide. There is no sense that the values in the regulations (such as limits on the amount of administrative costs that can be claimed by an insurer) need to be adjusted on a state-by-state basis. And that refusal to adjust the regulations based on different economics in different states exists under the current regulations even if insurers in different jurisdictions have different financial experiences under the Affordable Care Act or face different state regulatory environments.

So, with those darned percentages statutorily nailed down, how does one achieve the objective in the Federal Register proposal of giving insurers their anticipated profits back? The answer is that the Federal Register proposal attempts to add a phantom cost that will vary state-by-state in precisely the amount needed to do the job.  Of course, writing “state-specific phantom cost” into the regulations would alert everyone that the plan was just to shovel money to insurers to keep them happy regardless of what was in the law. So, instead, the idea was to seize upon a word already in the regulations — “profit” — and alter its definition beyond recognition. Expanded “profit” could then do the same job as “state specific phantom cost.”

The math

Here are the specifics. The statute makes the amount the insurer receives in Risk Corridor payments (or pays) depend on a ratio.  A higher ratio often results in more payments and never results in smaller payments from HHS. The numerator of the ratio is something called “allowed costs,” so the higher the allowed costs, the better HHS treats the insurer under Risk Corridors.  The denominator of the ratio is something called “the target amount.” Because higher ratios are good for the insurer, the smaller the “target amount” the better HHS treats the insures under Risk Corridors. (Remember, dividing by a smaller number yields a higher result.) And “target amount” is defined as total premiums less administrative costs.  So, the more an insurer can stuff into administrative costs, the smaller the denominator, the higher the ratio, and the better the insurer fares under Risk Corridors. Indeed, much of the regulatory effort has been appropriately devoted to deterring insurers from exploiting the formula by stuffing overhead they incur servicing non-ACA policies into “administrative costs” that increase their Risk Corridor payments. (Good idea!)

Back in March of 2013, in trying to figure out how to operationalize the ideas contained in the Risk Corridors statute, HHS decided to recognize that the insurer risks its capital in order to operate an insurance company. HHS recognized that it is therefore appropriate to treat some of that opportunity cost as a true cost. (I have no particular problem with the concept). Perhaps unfortunately, but as a convenient shorthand, HHS called this opportunity cost “profit.” Be clear, however, the term “profit” as used in the regulations had little to do with how much money the insurer actually made; it was just an easy term to reflect the fact that when insurers use money to establish offices and buy computers they forgo interest and dividends  that they might otherwise have earned.

But how much of this opportunity cost called “profit” should an insurer be entitled to use to reduce its Risk Corridor denominator?  After receiving comments that were apparently almost uniform on the subject — the one dissent advocated a lower number — HHS decided to use 3% of after-tax premiums. It called this number, “the profit margin floor.”

Several things are significant about the decision to use 3% of premiums.  First, the profit margin floor is 3%, not 6% or 9% or some higher number yet. No one apparently thought the number should be higher. Second, the number is uniform across states. This is entirely sensible because, to the extent that an allowance for capital costs is appropriate at all, capital costs of an insurer are incurred in a national market. Insurers in California do not have opportunity costs of capital that differ very much from insurers in Texas. And, third, the number is a coefficient of net premiums rather than assets probably because use of premiums provides a sensible surrogate for the amount of capital risked by running an Exchange insurance operation instead of running one’s entire insurance business.

What the new Federal Register proposal does is to increase the profit margin floor and to do it in a state-specific way. By increasing the profit margin floor, one can decrease the target ratio denominator and increase the Risk Corridors ratio, which in turn can increase the payment made by HHS to the insurer.  Mathematically, increasing the profit margin floor is little different than permitting the insurer to count triple-rent on its offices rather than real rent or to just pad its electric bills by, say, a million dollars. All are additions of non-existent “phantom costs” that act to decrease a denominator and, derivatively, increase a ratio upon which reimbursement depends.

Moreover, the amount by which the profit margin floor will need to be increased is not a trivial amount.  As shown in the Risk Corridors Calculator, “profit margins” may need to be tripled or more to bring an insurer back to the same position they were in originally.  I would not be surprised to see the profit margin floor in some states in which adverse selection proves particularly problematic to be upwards of 12%.  I am not aware of many insurers making 12% of their premiums in profits, which is precisely why, before they saw the need to repair the damage done by the President’s change of mind, HHS was using 3% as the appropriate figure with only lower numbers being suggested.

Why the proposed fix is unlawful

Any thought that the proposed increase in profit margin floor might have something to do with economic reality, with changes in the cost of capital, is belied by the way HHS explains the change and by the state-by-state approach it now proposes to take.  The HHS explanation is that, because different states are implementing “the transitional plan” differently, the need to adjust Risk Corridors to bring insurers back to their former position differs as well.

We believe that the State-wide effect on this risk pool will increase with the increase in the percentage enrollment in transitional plans in the State, and so we are considering having the State-specific percentage adjustment to the risk corridors formula also vary with the percentage enrollment in these transitional plans in the State. (78 FR 72350)

Of course, in some sense, this is true. But this simply highlights the point that the adjustments to profit margin floor have nothing to do with real costs, the concept the statute cares about.

Not enough? Take a look at the explanation for why HHS did not adjust profit margin floors it on an insurer-by-insurer basis.  It has nothing to do with different costs of capital that different insurers might face, but again, the state-by-state approach is used because it is a simpler way of approximating and offsetting the loss insurers would face in each state as a result of differential effects of the transition policy.

Although the adjustment that we are considering would affect each issuer differently, depending on its particular claims experience and administrative cost rate, we believe that, on average, the adjustment would suitably offset the losses that a standard issuer might experience as a result of the transitional policy. (78 FR 72350)

The administrative law and separation of powers issue is whether the agency empowered with administering Risk Corridors can count as a cost not an expense the insurers actually incur as a result of being in an Exchange but the “regulatory taking” that will occur differentially in each state as a result of President Obama changing his mind. I suppose that, if there is someone with standing to challenge this give away of government money, it will ultimately be for the courts to decide this question.  (By the way, if anyone can suggest someone who might have standing, email me). And I suppose someone can argue that it actually fulfills some general intent of the ACA to keep insurers involved in the Exchanges and not have them flee when other regulations change.

Executive administrative agencies such as the Department of Health and Human Services have the authority under some circumstances to interpret statutes; courts will often then defer to their interpretations. But this fix is not a stretch; if it actually does what its drafters intend, it will be a redraft of the Affordable Care Act itself. I see no difference except opacity between what the Obama administration has done by seizing on a code word “profit” and expanding its definition beyond recognition and saying that when the statute says 80% of losses, surely that could be construed as 95%. Both are unlawful.

Two final notes

The allowable administrative cost cap percentage and the medical loss ratio

Careful readers of the Federal Register will note that there are two other matters it discusses.

The Federal Register proposal also discusses the need to adjust the “allowable administrative costs ceiling (from 20 percent of after-tax profits) in an amount sufficient to offset the effects of the transitional policy upon the claims costs of a model plan.” This provision is needed because otherwise, even if the profit margin floor were increased, insurers would bump up against the existing administrative cost ceiling of 20%.  So, to make sure that the phantom cost “profit margin floor” increase really works, the proposed regulations propose removing that constraint. And to make sure that evil insurers do not take advantage of the relaxed constraint to allocate more of their costs to Exchange plans, the regulations make clear that the insurer would had to have met the 20% standard before consideration of increased “profit” was made.

The Federal Register proposal also discusses a need to adjust the Medical Loss Ratio (MLR) percentages. This is the provision of the ACA that says that if insurers spend too much of their money on non-claims matters, they have to pay a rebate to their insureds.  The problem becomes that if insurers are permitted to treat more than 20% of their premiums as administrative costs for purposes of Risk Corridors they might want to treat more than 20% of their premiums as legitimate administrative costs for purposes of MLR rebates. It’s a little fuzzy, but it sounds as if HHS wants to tweak the MLR regulations so that the MLR provisions do not take away from insurers what they will be winning if the remainder of the Federal Register proposal goes into effect.

The typo in the statute

There’s a complication we have to work through. This whole area is complicated by the fact that there is a typographic error in section 1342.  Here again is the relevant part.

(b) PAYMENT METHODOLOGY.—
(1) PAYMENTS OUT.—The Secretary shall provide under the
program established under subsection (a) that if—
(A) a participating plan’s allowable costs for any plan
year are more than 103 percent but not more than 108
percent of the target amount, the Secretary shall pay to
the plan an amount equal to 50 percent of the target
amount in excess of 103 percent of the target amount;
and
(B) a participating plan’s allowable costs for any plan
year are more than 108 percent of the target amount,
the Secretary shall pay to the plan an amount equal to
the sum of 2.5 percent of the target amount plus 80 percent
of allowable costs in excess of 108 percent of the target
amount.

See in subparagraph (1)(A) where it says “the Secretary shall pay to the plan an amount equal to 50 percent of the target amount in excess of 103 percent of the target amount.” But if you think about it, this could never happen.  Taken literally, there could never be a payment under this provision. So long as the target amount is a positive number, which it always will be since premiums are positive, the target amount can NEVER be in excess of 103% of the target amount.  5 can never be in excess of 103% of 5 (5.15).  10 can never be in excess of 103% of 10 (10.30). Can’t happen.

Looking at the next subparagraph, (1)(B), resolves the mystery of subparagraph (1)(A). It speaks about paying “ 80 percent of allowable costs in excess of 108 percent of the target amount.” (emphasis mine). And this makes complete sense.  The more the insurer loses, the more the government reimburses the insurer.  That’s the whole point of the provision.  I therefore believe that  subparagraph (1)(A) should be interpreted to mean “the Secretary shall pay to the plan an amount equal to 50 percent of  allowable costs in excess of 103 percent of the target amount.”

So, I assume that courts will interpret the statute to read as Congress must have intended it and not as some sort of cute joke resting on a mathematical impossibility.  See United States v. Ron Pair Enterprises, 489 U.S. 235 (1989) (“The plain meaning of legislation should be conclusive, except in the ‘rare cases [in which] the literal application of a statute will produce a result demonstrably at odds with the intentions of its drafters.’ Griffin v. Oceanic Contractors, Inc., 458 U. S. 564, 571 (1982). In such cases, the intention of the drafters, rather than the strict language, controls. Ibid.” )

Note on Definitions

As set forth in the regulations, “Allowable costs mean, with respect to a QHP [Qualified Health Plan], an amount equal to the sum of incurred claims of the QHP issuer for the QHP.” The regulation sensibly uses the word “incurred.” This is so because costs are things the insurer has to pay out or has to accrue liabilities for, not things that, under some other set of circumstances they might otherwise have had to pay out.  If that were not the case, the administration could redefine costs to include anything at all, such as the costs the insurer would have faced if every one of their insureds had cancer.

The regulations tweak the definition of “administrative costs” by adding an extra adjective. They introduce the concept of “allowable administrative costs.”  The insurer is not permitted to reduce its “target amount” by claiming some enormous sum (such as private jets for the CEO) as non-claims costs, subtracting them from premiums and reporting low net premiums (target amount) in order to get paid more by the government under the Risk Corridors program. Instead, the regulations define “allowable administrative costs” as non-claims costs that are not more than 20% of premiums. That makes some sense because section 10101 of the ACA (42 U.S.C. § 300gg-18) often requires insurers whose administrative costs are more than 20% of premiums to pay a rebate to their insureds.

Premiums are also reasonably defined under the existing regulations. They sensibly say, “Premiums earned mean, with respect to a QHP, all monies paid by or for enrollees with respect to that plan as a condition of receiving coverage.” Thus, under the statute and existing regulations, premiums must refer to real premiums, not hypothetical premiums. Premiums are moneys the insurer receives, not money the insurer might have received under some other set of circumstances. Again, this just has to be the case; if it were not true, the administration could funnel virtually an infinite amount of money to the insurance industry by saying that premiums are funds the insurer would have received if no one signed up for their plan. 

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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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Shocking secrets of the actuarial value calculator revealed!

That might be how the National Enquirer would title this blog entry.  And, hey, if mimicking its headline usage attracts more readers than “Reconstructing mixture distributions  with a log normal component from compressed health insurance claims data,” why not just take a hint from a highly read journal?  But seriously, it’s time to continue delving into some of the math and science behind the issues with the Affordable Care Act. And, to do this, I’d like to take a glance at a valuable data source on modern American health care, the data embedded in the Actuarial Value Calculator created by our friends at the Center for Consumer Information and Insurance Oversight (CCIIO).

This will be the first in a series of posts taking another look at the Actuarial Value Calculator (AVC) and its implications on the future of the Affordable Care Act. (I looked at it briefly before in exploring the effects of reductions in the transitional reinsurance that will take effect in 2015).  I promise there are yet more important implications hidden in the data.  What I hope to show in my next post, for example, is how the data in the Actuarial Value Calculator exposes the fragility of the ACA to small variations in the composition of the risk pool.  If, for example, the pool of insureds purchasing Silver Plans has claims distributions similar to those that were anticipated to purchase Platinum Plans, the insurer might lose more than 30% before Risk Corridors were taken into account and something like 10% even after Risk Corridors were taken into account. And, yes, this takes account of transitional reinsurance. That’s potentially a major risk for the stability of the insurance markets.

What is the Actuarial Value Calculator?

The AVC is intended as a fairly elaborate Microsoft Excel spreadsheet that takes embedded data and macros (essentially programs) written in Visual Basic, and is intended to help insurers determine whether their proposed Exchange plans conform to the requirements for the various “metal tiers” created by the ACA. These metal tiers in turn attempt to quantify the ratio of the expected value of the benefits paid by the insurer to the expected value of claims covered by the policy and incurred by insureds. The programs, I will confess, are a bit inscrutable — and it would be quite an ambitious (and, I must confess, tempting) project to decrypt their underlying logic — but the data they contain is a more accessible goldmine. The AVC contains, for example, the approximate distribution of claims the government expects insurers writing plans in the various metal tiers to encounter.

There are serious limitations in the AVC, to be sure. The data exposed has been aggregated and compressed; rather than providing the amount of actual claims, the AVC has binned claims and then simply presented the average claim within each bin.  This space-saving compression is somewhat unfortunate, however, because real claims distributions are essentially continuous. Everyone with annual claims between $600 and $700 does not really have claims of $649. This distortion of the real claims distribution makes it more challenging to find analytic distributions (such as variations of log normal distributions or Weibull distributions) that can depend on the generosity of the plan and that can be extrapolated to consider implications of serious adverse selection. It’s going to take some high-powered math to unscramble the egg and create continuous distributions out of data that has had its “x-values” jiggled.  Moreover, there is no breakdown of claim distributions by age, gender, region or other factors that might be useful in trying to predict experience in the Exchanges.  (Can you say “FOIA Request”?)

This blog entry is going to make a first attempt, however, to see if there aren’t some good analytic approximations to the data that must have underlain the AVC. It undertakes this exercise in reverse engineering because once we have this data, we can make some reasonable extrapolations and examine the resilience — or fragility — of the system created by the Affordable Care Act. The math may be a little frightening to some, but either try to work with me and get it or just skip to the end where I try to include a plain English summary.

The Math Stuff

1. Reverse engineering approximate continuous approximations to the data underlying the Actuarial Value Calculator

Nothwithstanding the irritating compression of data used to produce the AVC, I can reconstruct a mixture distribution composed mostly of truncated exponential distributions that well approximates the data presented in the AVC.   I create one such mixture distribution for each metal tier. I use distributions from this family because they have been proven to be “maximum entropy distributions“, i.e. they contain the fewest assumptions about the actual shape of the data. The idea is to say that when the AVC says that there were 10,273 claims for silver-like policies between $800 and $900 and that they averaged $849.09, that average could well have been the result of an exponential distribution  that has been truncated to lie between $800 and $900.  With some heavy duty math, shown in the Mathematica notebook available here, we are able, however, to find the member of the truncated exponential family that would produce such an average. We can do this for each bin defined by the data, resorting to uniform distributions for lower values of claims.

The result of this process is a  messy mixture distribution, one for each metal tier. The number of components in the distribution is essentially the same as the number of bins in the AVC data. This will be our first approximation of “the true distribution” from which the claims data presented in the AVC calculator derives. The graphic below shows the cumulative density functions (CDF) for this first approximation. (A cumulative density function shows, for each value on the x-axis the probability that the value of a random draw from that distribution will be less than the value on the x-axis).   I present the data in semi-log form: claim size is scaled logarithmically for better visibility on the x-axis and percentage of claims less than or equal to the value on the x-axis is shown on the y-axis.

CDF of the four tiers derived from the first approximation of the data in the AVC
CDF of the four tiers derived from the first approximation of the data in the AVC

There are two features of the claims distributions that are shown by these graphics.  The first is that the distributions are not radically different.  The model suggests that the government did not expect massive adverse selection as a result of people who anticipated higher medical expenses to disproportionately select gold and platinum plans while people who anticipated lower medical expenses to disproportionately select bronze and silver plans. The second is that, when viewed on a semi-logarithmic scale, the distributions for values greater than 100 look somewhat symmetric about a vertical axis.  They look as if they derive from some mixture distribution composed of a part that produces a value close to zero and something kind of log normalish. If this were the case, it would be a comforting result, both because such mixture distributions would be easy to parameterize and extrapolate to lesser and greater forms of adverse selection and because such mixture distributions with a log normal component are often discussed in the literature on health insurance.

2. Constructing a single Mixture Distribution (or Spliced Distribution) using random draws from the first approximation

One way of finding parameterizable analytic approximations of “the true distribution” is to use our first approximation to produce thousands of random draws and then to use mathematical  (and Mathematica) algorithms to find the member of various analytic distribution families that best approximate the random draws. When we do this, we find that the claims data underlying each of the metal tiers is indeed decently approximated by a three-component mixture distribution in which one component essentially produces zeros and the second component is a uniform distribution on the interval 0.1 to 100 and the third component is a truncated log normal distribution starting at 100.  (This mixture distribution is also a “spliced distribution” because the domains of each component do not overlap). This three component distribution is much simpler than our first approximation, which contains many more components.

We can see how good the second-stage distributions are by comparing their cumulative distributions (red) to histograms created from random data drawn from the actuarial value calculator (blue).  The graphic below show the fits to look excellent.

Note: I do not contend that a mixture distribution with a log normal distribution perfectly conforms to the data.  It is, however, pretty good for practical computation.

Actual v. Analytic distributions for various metal tiers
Actual v. Analytic distributions for various metal tiers

 

 3. Parameterizing health claim distributions based on the actuarial value

The final step here is to create a function that describes the distribution of health claims as a function of a number (v) greater than zero. The concept is that, when v assumes a value equal to the actuarial value of one of the metal tiers, the distribution that results mimics the distribution of AVC-anticipated claims for that tier.  By constructing such a function, instead of having just four distributions, I obtain an infinite number of possible distributions. These distributions collapse as special cases to the actual distribution of health care claims produced by the AVC. This process enables us to describe a health claim distribution and to extrapolate what can happen if the claims experience is either better (smaller) than that anticipated for bronze plans or worse (higher) than that anticipated for platinum plans. One can also use this process to compute statistics of the distribution as a function of v such as mean and standard deviation.

Here’s what I get.

Mixture distribution as a function of the actuarial value parameter v
Mixture distribution as a function of the actuarial value parameter v

Here is a animation showing, as a function of the actuarial value parameter v, the cumulative distribution function of this analytic approximation to the AVC distribution.  

Animated GIF showing Cumulative distribution of claims by "actuarial value
Cumulative distribution of claims by “actuarial value”

 

One can see the cumulative distribution function sweeping down and to the right as the actuarial value of the plan increases. This is as one would expect: people with higher claims distributions tend to separate themselves into more lavish plans.

Note: I permit the actuarial value of the plan to exceed 1. I do so recognizing full well that no plan would ever have such an actuarial value but allow myself to ignore this false constraint.  It is false because what one is really doing is showing a family of mixture distributions in which the parameter v can mathematically assume any positive value but calibrated such that (a)  at values of 0.6, 0.7, 0.8 and 0.9 they correspond respectively with the anticipated distribution of health care claims found in the AVC for bronze, silver, gold and platinum plans respectively and (b) they interpolate and extrapolate smoothly and, I think, sensibly from those values.

The animation below presents largely the same information but uses the probability density function (PDF) rather than the sigmoid cumulative distribution function. (If you don’t know the difference, you can read about it here.)  I do so via a log-log plot rather than a semi-log plot to enhance visualization.  Again, you can see that the right hand segment of the plot is rather symmetric when plotted using a logarithmic x-axis, which suggests that a log normal distribution is not a bad analytic candidate to emulate the true distribution.

Log Log plot of probability density function of claims for different actuarial values of plans

 

Some initial results

One useful computation we can do immediately with our parameterized mixture distribution is to see how the mean claim varies with this actuarial parameter v. The graphic below shows the result.  The blue line shows the mean claim as a function of “actuarial value” without consideration of any reinsurance under section 1341 (18 U.S.C. § 18061) of the ACA.  The red line shows the mean claim net of reinsurance (assuming 2014 rates of reinsurance) as a function of “actuarial value.” And the gold line shows the shows the mean claim net of reinsurance (assuming 2015 rates of reinsurance) as a function of “actuarial value.” One can see that the mean is sensitive to the actuarial value of the plan.  Small errors in assumptions about the pool can lead to significantly higher mean claims, even with reinsurance figured in.

Mean claims as a function of actuarial value parameter for various assumptions about reinsurance
Mean claims as a function of actuarial value parameter for various assumptions about reinsurance

I can also show how the claims experience of the insurer can vary as a result of differences between the anticipated actuarial value parameter v1 that might characterize the distribution of claims in the pool and the actual actuarial value parameter v2 that ends up best characterizing the distribution of claims in the pool.  This is done in the three dimensional graphic below. The x-axis shows the actuarial value anticipated to best characterize an insured pool. The y-axis shows the actuarial value that ends up best characterizing that pool.  The z-axis shows the ratio of mean actual claims to mean anticipated claims.  A value higher than 1 means that the insurer is going to lose money. Values higher than 2 mean that the insurer is going to lose a lot of money.  Contours on the graphic show combinations of anticipated and actual actuarial value parameters that yield ratios of 0.93, 1.0, 1.08, 1.5 and 2. This graphic does not take into account Risk Corridors under section 1342 of the ACA.

What one can see immediately is that there are a lot of combinations that cause the insurer to lose a lot of money.  There are also combinations that permit the insurer to profit greatly.

Ratio of mean actual claims to mean expected claims for different combinations of anticipated and actual actuarial value parameters
Ratio of mean actual claims to mean expected claims for different combinations of anticipated and actual actuarial value parameters

Plain English Summary

One can use data provided by the government inside its Actuarial Value Calculator to derive accurate analytic statistical distributions for claims expected to occur under the Affordable Care Act.  Not only can one derive such distributions for the pools anticipated to purchase policies in the various metal tiers (bronze, silver, gold, and platinum) but one can interpolate and extrapolate from that data to develop distributions for many plausible pools.  This ability to parameterize plausible claims distributions becomes useful in conducting a variety of experiments about the future of the Exchanges under the ACA and exploring their sensitivity to adverse selection problems.

Resources

You can read about the methodology used to create the calculator here.

You can get the actual spreadsheet here. You’ll need to “enable macros” in order to get the buttons to work.

The actuarial value calculator has a younger cousin, the Minimum Value Calculator.  If one looks at the data contained here, one can see the same pattern as one finds in the Actuarial Value Calculator.

Joke

Probably I should have made the title of this entry “Shocking sex secrets of the actuarial value calculator revealed!” and attracted yet more viewers.  I then could have noted that the actuarial value calculator ignores sex (gender) in showing claims data.  But that would have been going too far.

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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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Proposed cuts in transitional reinsurance could increase Exchange premiums 7-8% in 2015

Late last week, HHS released its 255-page HHS Notice of Benefit and Payment Parameters for 2015. Buried away in this technical documents are at least two interesting matters.

  1. HHS is planning to cut reinsurance payments to insurers participating in its Exchanges in a way that, in and of itself, could increase gross premiums 7-8% in 2015 and increase the risk of further adverse selection
  2. HHS has validated the claims of insurers that President Obama’s recent about-face on the ability of insurers to renew certain policies not providing Essential Health Benefits could destabilize the insurance market.  The Notice proposes changing the way insurers calculate their profits and losses so that the amount of payments made by government to insurers in the Exchange would increase. It claims, however, that it does not know how much this will cost.
The HHS Notice for 2015
The HHS Notice for 2015

Less reinsurance

Under the system in place for 2014, if insurers in an Exchange have to pay between $45,000 and $250,000 on one of their insureds, the government picks up 80% of that loss (assuming the $63 per insured life it taxes various other health insurance plans is sufficient to pay that amount). But in 2015, the money that goes into this transitional reinsurance pool (section 1341 of the ACA, 42 U.S.C. sec. 18061) declines by a third from $12 billion to $8 billion and the head tax correspondingly declines from $63 to $44. As a result, HHS proposes to now pick up only 50% of the tab for losses between $70,000 and $250,000. Thus, losses between $45,000 and the new $70,000 attachment point will now fall entirely on insurers without federal help and insurers will have to pay 30% more on losses between $70,000 and $250,000.

This reduction in free reinsurance provided by the taxpayers will almost certainly result in increased premiums for insureds. My estimate is that the average premium hike induced by this reduction in reinsurance is likely to be about 7-8%.

Here’s how I did this computation. I took loss distributions contained in the government’s “Actuarial Value Calculator.” That’s the Excel spreadsheet the government (and insurers) use to figure out what metal tier, if any, their policy falls into. I then performed the following steps.  You can verify what I have done in the Computable Document Format (CDF) document I have placed on Dropbox. You can view the document using the free CDF player or using Mathematica

Step 1.  I determined the expected value of claims under those loss distributions with reinsurance parameters set at the 2014 rates.  I get four results, one for each metal tier: {3630.52, 4223.87, 4468.95, 5556.06}. I then do exactly the same computation but use the 2015 reinsurance parameters. I get four results, one for each metal tier: {3906.67, 4550.95, 4807.06, 5948.53}.

Step 2. I multiply each result by the actuarial value of the associated metal tier to approximate the size of the premium needed to support the expected level of the claims. I get {2178.31, 2956.71, 3575.16, 5000.46} for the 2014 reinsurance parameters and {2344., 3185.67, 3845.65, 5353.68} for the 2015 reinsurance parameters.

Step 3. I then simply compute the percent increase in the needed 2015 premiums over the needed 2014 premiums and get {0.0760631, 0.077436, 0.0756584, 0.0706371}

If losses are, as I suspect they will be, greater than those assumed in the actuarial value calculator — because the pool is going to be drawn for a variety of reasons from a riskier group than originally anticipated —  the diminution in reinsurance is yet more significant and, standing by itself, could add more than 7-8% to the gross premiums charged in the Exchanges.

Whether the increase in gross premiums is about 7-8% or whether it is higher, it creates a heightened risk for an adverse selection problem.  This is so because, although subsidies insulate many people in the Exchanges from increases in gross premiums — net premiums are pegged to income rather than gross premiums for them — it will affect the significant number (estimated by HHS to be about 18% (4/22)) who are expected to purchase policies inside the Exchanges without subsidies.  The higher premiums go, however, the more we would expect to see the healthy drop out and find substitutes for the non-underwritten policies sold in the Exchanges. (If premiums are low enough, adverse selection is not a problem: insurance is a good deal for everyone and healthy and sick purchase it alike. See, e.g., Medicare Part B, which is very heavily subsidized and does not suffer seriously from adverse selection.)

Note to experts. Some of you might think I erred in saying that the 2014 reinsurance attachment point is $45,000 and not $60,000. But the 2015 notice says on page 11 that it will retroactively reduce the attachment point to $45,000.

HHS Validates Insurer Fears About Obama Reversal and the Destabilization of Insurance Markets

Many individuals, including me, have claimed that President Obama’s recent decision to permit insurers to “uncancel” certain individual plans that do not contain Essential Health Benefits could destabilize insurance markets. The Notice of Benefit and Payment Parameters just released appears to validate that assertion. Stripped of bureaucratese, the HHS document basically says that insurers are right to be disconcerted by the President’s about face.

For those who enjoy bureaucratese, however, or who properly want to validate my own conclusions about the document, here’s what it actually says.

On November 14, 2013, the Federal government announced a policy under which it will not consider certain non-grandfathered health insurance coverage in the individual or small group market renewed between January 1, 2014, and October 1, 2014, under certain conditions to be out of compliance with specified 2014 market rules, and requested that States adopt a similar non-enforcement policy.

Issuers have set their 2014 premiums for individual and small group market plans by estimating the health risk of enrollees across all of their plans in the respective markets, in accordance with the single risk pool requirement at 45 CFR 156.80. These estimates assumed that individuals currently enrolled in the transitional plans described above would participate in the single risk pools applicable to all non-grandfathered individual and small group plans, respectively (or a merged risk pool, if required by the State). Individuals who elect to continue coverage in a transitional plan (forgoing premium tax credits and cost-sharing reductions that might be available through an Exchange plan, and the essential health benefits package offered by plans compliant with the 2014 market rules, and perhaps taking advantage of the underwritten premiums offered by the transitional plan) may have lower health risk, on average, than enrollees in individual and small group plans subject to the 2014 market rules.

If lower health risk individuals remain in a separate risk pool, the transitional policy could increase an issuer’s average expected claims cost for plans that comply with the 2014 market rules. Because issuers would have set premiums for QHPs in accordance with 45 CFR 156.80 based on a risk pool assumed to include the potentially lower health risk individuals that enroll in the transitional plans, an increase in expected claims costs could lead to unexpected losses.

So, the government wants help in figuring out what to do. One method it is contemplating involves technical adjustments to the Risk Corridors program in a way that would get insurers more money (pp. 101-105).  Although I will confess to considerable difficulty in understanding exactly what it is that HHS suggesting, the basic idea, as I understand it, would be to assume that those who, by virtue of the President’s about face, “uncancel” their policies would have had claims expenses equal to 80% of the average claims of the rest of the pool (page 103-04). HHS will then, on a state-by-state basis figure out what the position of the insurer would have been and try to adjust Risk Corridors such that the position of the insured after application of adjusted Risk Corridors is similar to that which it would have been in had these persons, who pay the same premium as the rest but who tend to have only 80% of the claims expenditures, enrolled in their plan.

It is not clear to me where the statutory authority to make this change comes from. Section 1342 of the ACA (42 U.S.C. 18062) does not define its key terms of “target amount” and “allowable costs” in a fashion that would appear to my eye to extend to hypothetical costs and hypothetical premiums. I will also confess to being unsure as to who would have standing to challenge this proposed give away of taxpayer money to the insurance industry.

What is clear to me, however, is the proposed reform, by necessity, will result in greater previously unbudgeted expenditures by the federal government. If we are really talking about making insurers whole and the people in question might have profited insurers something like $1,000 a person, the federal government appears to be suggesting a change in regulations that could cost it hundreds of millions of dollars.  The HHS Notice declines to put an exact figure on the cost of the change:

Because of the difficulty associated with predicting State enforcement of 2014 market rules and estimating the enrollment in transitional plans and in QHPs, we cannot estimate the magnitude of this impact on aggregate risk corridors payments and charges at this time.

HHS is probably correct in saying it is difficult to estimate the cost of the proposed changes to Risk Corridors.  I don’t think we have a good feel for how many people will return to the plans President Obama has carved out for special treatment.  It does look, however, as if a floor of a couple of hundred million dollars on the cost of the proposal would be quite reasonable. This, of course, could give some ammunition to those, such as Florida Senator Marco Rubio, who have called for repeal of the Risk Corridors provision as an insurance “bailout.” (For a discussion, look here, here and here)

Final Note

Yesterday, I said I hoped to provide a major post.  This actually is not the post I was speaking about. There’s still more news coming.  Maybe today or maybe while recovering from a turkey overdose tomorrow.

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Should California be happy or concerned by its early enrollment data?

The short answer: concerned but not panicked

As discussed yesterday on this blog and elsewhere in the media, Cover California, the state entity organizing enrollment there, has released data showing the age distribution of the group thus far enrolling in plans on its Exchanges.  Although I took a rather cautionary tone about the age distribution — fearing it could stimulate adverse selection — the head of Cover California and some influential media outlets generally favorable to the Affordable Care Act have been considerably more cheerful.  So, who’s right?  For reasons I will now show — and probably to no one’s surprise — me. (More or less).

To do this, we need to do some math.  It’s a more sophisticated variant of the back of the envelope computation I undertook earlier on this blog. The idea is to compute the mean profit of insurers in the Exchange as a function of the predicted versus the actual age distribution of the pool they insure.  Conceptually, that’s not too difficult. Here are the steps.

1. Compute the premium that equilibrates the “expectation” of premiums and costs for the predicted age distribution of the pool they insure. Call that the “predicted equilibrating premium.”

2. Compute the expected profit of the insurer given the predicted equilibrating premium and the actual age distribution of the pool they insure.

3. Do Step 1 and Step 2 for a whole bunch (that’s the technical term) of combinations of predicted age distributions and actual age distributions.

Moving from concept to real numbers is not so easy. The challenge comes in getting reasonable data and, since there are an infinite number of age distributions and in developing a sensible parameterization of some subset of plausible distributions.

The Data

The data is interesting in and of itself.  To get the relationship between premiums and age, I used the robust  Kaiser Calculator.  Since healthcare.gov itself recommends the web site (their own site seems to have a few problems) and I have personally validated its projected premiums for various groups against what I actually see from various vendors, I believe it is about as reliable a source of data as one is likely to find anywhere right now.  So, by hitting the Kaiser Calculator with a few test cases and doing a linear model fit using Mathematica (or any other decent statistics package), we are able to find a mathematical function that well captures a (quadratic) relationship between age and premium.  (The relationship isn’t “really” quadratic, but quadratics are easy to work with and fit the data very well.) The graphic below shows the result.

Nationwide average health insurance premium  for a silver plan as a function of age
Nationwide average health insurance premium for a silver plan as a function of age

We can normalize the graphic and the relationship such that the premium at age 18 (the lowest age I consider) is 1 and everything else is expressed as a ratio of the premium at age 18. Here’s the new graphic.  The vertical axis is now just expressed in ratios.

Nationwide average health insurance premium ratio for a silver plan as a function of age
Nationwide average health insurance premium ratio for a silver plan as a function of age

To get the relationship between cost and age, I used a peer reviewed report from Health Services Research titled “The Lifetime Distribution of Health Care Costs.”  It’s from 2004 but that should not matter much: although the absolute numbers have clearly escalated since that time, there is no reason to think that the age distribution has moved much. I can likewise do a linear model fit and find a quadratic function that fits well (R^2 = 0.982).  Again, I can normalize the function so that its value at age 18 is 1 and everything else is expressed as a ratio of the average costs incurred by someone at age 18.  Here’s a graphic showing the both the relationship between age and normalized premiums in the Exchanges under the Affordable Care Act and normalized costs.

labeledNormalizedCombinationPlot

The key thing to see is that health care claims escalate at a faster rate than health care premiums. Others have noted this point as well. They do so because the Affordable Care Act (42 U.S.C. § 300gg(a)(1)(A)(iii)) prohibits insurers from charging the oldest people in the Exchanges more than 3 times what they charge the youngest people. Reality, however, is under no such constraint.

Parameterizing the Age Distribution

There are an infinite number of potential age distributions for people purchasing health insurance.  I can’t test all of them and I certainly can make a graph that shows profit as a function of every possible combination of two infinite possibilities. But, what I can do — and rather cleverly, if I say so myself — is to “triangulate” a distribution by saying how close it is to the age distribution of California as a whole and how close it is to the age distribution of those currently in the California Exchange pool.  I’ll say a distribution has a “Pool Parameter Value” of 0 if it comes purely from California as a whole and has value of 1 if it comes purely from the California Exchange pool.  A value of 0.4 means the distribution comes 40% from California as a whole and 60% from the current California Exchange pool. The animation below shows how the cumulative age distribution varies as the Pool Parameter Value changes.

 

How the age distribution varies as the pool goes from looking more like California as a whole to looking more like the current pool as a whole.
How the age distribution varies as the pool goes from looking more like California as a whole to looking more like the current pool as a whole.

Equilibration and Results

The last step is to compute a function showing the equilibrium premium as a function of the predicted pool parameter value. We can then use this equilibrating premium to compute and graph profit as a function of both predicted pool parameter value and actual pool parameter value.

The figure below shows some  of the Mathematica code used to accomplish this task.

Mathematica code used to produce graphic showing relationship between insurer profit in the California exchanges and the nature of the predicted pool and the actual pool
Mathematica code used to produce graphic showing relationship between insurer profit in the California exchanges and the nature of the predicted pool and the actual pool

Stare at the graphic at the bottom.  What it shows is that if, for example, California insurers based their premiums on the pool having a “parameter value” of  0 (looks like California) and the actual pool ends up having a “parameter value of 1 (looks like the current pool), they will, everything else being equal, lose something like 10% on their policies and probably need to raise rates by about 10% the following year. If, on the other hand, they thought the pool would have a parameter value of 0.5 and it ended up having a parameter value of 0.75 the insurers might lose only about 3.5%.

Bottom Line

If I were an insurer in California I’d be concerned about the age numbers coming in, but not panicked.  First, I hope I did not assume that my pool of insureds would look like California as a whole.  I had to assume some degree of adverse selection. But it does not look as though, even if I made a fairly substantial error,  the losses will be that huge.  That’s true without the Risk Corridors subsidies and it is all the more true with Risk Corridor subsidies.

What I would be losing sleep about, however, is that the pool I am getting is composed disproportionately of the sick of all ages. If I underestimated that adverse selection problem, I could be in deep problem. My profound discomfort would arise because,  while I get to charge the aged somewhat more, I don’t get to charge the sick anymore. And there’s one fact that would be troubling me. Section 1101 of the Affordable Care Act established this thing calledthe Pre-Existing Condition Insurance Pool. It’s been in existence (losing boatloads of money) for the past three years.  It held people who couldn’t get insurance because they had pre-existing conditions.  They proved very expensive to insure.  There are 16,000 Californians enrolled in that pool.  But that pool ends on January 1, 2014.  And the people in it have to be pretty motivated to get healthy insurance.  Where are they going to go? If the answer is that a good chunk of the 79,000 people now enrolled in the California pool are former members of the PCIP, the insurers are in trouble unless they get a lot more healthy insureds to offset these individuals.

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Eliminating Risk Corridors jeopardizes Exchange Insurance

Draft of S.1726
Draft of S.1726

In a Wall Street Journal op-ed today that tracks much of what has been said on this blog in recent years, Florida Senator Marco Rubio announced that he will introduce later today a bill (provisionally numbered S.1726 ) that would apparently eliminate “Risk Corridors,” the provision of the Affordable Care Act under which the government would reimburse insurers selling insurance on an Exchange for the next three years from a good portion of any losses that they suffer there. Rubio contends  that “ObamaCare’s risk corridors are designed in such an open-ended manner that the president’s action now exposes taxpayers to a bailout of the health-insurance industry if and when the law fails.”

Marco Rubio portrait
Marco Rubio

Senator Rubio is largely correct, I believe, in his understanding of Risk Corridors (section 1342 of the ACA, codified at 42 U.S.C. 18062) both as drafted in the statute and as implemented by the Department of Health and Human Services.  Unlike its cousins, the reinsurance provisions (42 U.S.C. § 18061) and the risk adjustment provisions (42 U.S.C. § 18063), both of which likewise help reduce the risks of writing policies for sale on an Exchange, Risk Corridors is not drafted to be budget neutral.  That was the way the Congressional Budget Office scored it — it assumed that receipts under the provision would equal outlays — but this was clearly a blunder that should have been apparent at the time and that minimized the advertised budgetary risk entailed by passage of the Affordable Care Act. As discussed in an earlier blog post, if the distribution of profit and loss by insurers selling in the Exchanges is skewed in the loss direction, the government will be obligated to pay out more than it takes in.  Where the funding for this new “entitlement” for the insurance industry would come from is unclear. Senator Rubio is thus correct again when he says that the bill will be paid for by the taxpayer.

Senator Rubio is not correct to imply, however, that, standing by itself, the underestimate of Risk Corridor exposure represents this enormous understatement of the cost to the taxpayer of the Affordable Care Act.  That law, for better or worse, always called for large taxpayer outlays to help prop up an insurance system that, as one of its critical architectural features, would attack medical underwriting by insurers.  Indeed, although it was not apparent to many until recently, precisely because of the Three Rs of Risk Corridors, “free” reinsurance and future “risk adjustments,” the Affordable Care Act always created this scheme that looked like it preserved private insurance but in fact converted insurers largely into claims processors in a system in which profitability and core insurance functions were largely controlled by the federal government.

To see the relative magnitude of the Risk Corridors program, consider the bigger picture. The CBO projected most recently, for example, that subsidies to help individuals purchase insurance via tax credits and cost sharing reductions would total $26 billion in 2014 and ramp up to $108 billion by 2017.  To be sure, that figure was based on the assumption, which is beginning to look very suspect, that there would be 7 million people in the Exchanges in 2014, and thus might decrease if enrollment is considerably lower.  Still, since by my calculations it seems unlikely that the Risk Corridor payments will amount to more than $1 billion per year (but see footnote below), it is not as if the cost of “Obamacare” suddenly went through the roof. Maybe Risk Corridors could be considered the “straw that broke the camel’s back,” but the Affordable Care Act has always been a stretch of the federal budget and it has been a stretch that many have long found deeply troubling.

CBO projections on the cost of the Exchanges
CBO projections on the cost of the Exchanges

The more serious issue surrounding Senator Rubio’s suggestion that Risk Corridors be repealed is that such an action might well be the straw that broke the insurers’ backs.  Insurers do not have to participate in the Exchanges and they certainly do not have to continue to do so in 2015. I suspect that if, anything stands right now or in the future between the deeply troubling enrollment numbers and an adverse selection death spiral caused by a combination of premium escalation and insurer withdrawals from the exchange marketplace, it is insurers’ belief that Uncle Sam will take care of the insurance industry.  Indeed, that’s the not-too-subtle consolatory hint that accompanied the letter sent last week by the Obama administration to state insurance commissioners. It tells regulators and insurers that, to enable the President to keep his oft-repeated campaign promise — I don’t even have  to tell you which one — the healthy insureds on which Exchange insurers were banking would now be given a sometimes cheaper (and sometimes competitive) alternative. How many of these victims of the previously broken promise would have purchased insurance on the Exchanges if forced to do so is open to question. But, at the present time, every insured helps those Exchanges survive, even if only barely.

By telling insurers that, contrary to the strong hints at the end of  the Obama administration letter, there will be no relief for the additional average costs now imposed on insurers,  passage of Senator Rubio’s bill might lead to the implosion of the insurance Exchanges and the death of a crucial portion of the Affordable Care Act. While such a result would hardly deter many from voting in favor of the bill, those who dislike the Affordable Care Act ought to think hard not just about how much they want it to end but in what way they want it to end. Dismantling the ACA is itself going to be difficult and painful — wait until we hear the cries from the people who deeply craved the subsidized insurance they thought they were receiving or who otherwise benefited from the Act — and ultimately entails very serious and difficult policy choices about how we want to finance healthcare in the United States.  Consumer driven? Single payor? If the law is to be unwound, it would be better if it were done in as deliberate and orderly way as practicable rather than as an unforeseen result of legislation that purported to deal with a narrow aspect of the ACA.

There is, it should be noted, a compromise position that will preserve something of Risk Corridors while not adding to the federal budget deficit.  One could amend the Risk Corridors provision to force it to be budget neutral.  This has already been done in the companion provisions of stop-loss reinsurance and risk adjustment and there is no reason that, if legislators could act in good faith, the law could not be modified to state that payments by the Secretary of HHS to insurers would be reduced pro rata to the extent necessary to make payments in under Risk Corridors equal payments out.  This potential reduction in payments might, it must be acknowledged, scare insurers and contribute to the implosion of Obamacare, but it would be less likely to do so that a bill that repealed Risk Corridors altogether.

A Footnote on the cost of Risk Corridors

Footnote: I’ve been thinking some more about a back of the envelope computations in a blog entry that attempted to develop a relationship between the number of people enrolling in insurance on the Exchanges and the size of the Risk Corridor payments. As those paying the closest attention to my prior blog post will recall, I made an assumption about the spread of the distribution of insurer profits and losses.  The assumption was not unreasonable, but it was also hardly infallible.  What if, I have been wondering, the spread was much narrower than I suggested it might be?

I decided to run the experiment again using a standard deviation of profits and losses only 1/10 of what it had been.  I thus create regimes in which the financial fates of most insurers selling policies are closely tied together.  What I find is that assuming that most insurers will either make money or that most insurers will lose money has a tendency to increase the payments the government will likely have to make if enrollment is small.  In this new experiment, payments peak at about $1.5 billion rather than $1 billion in the prior experiment.  Bottom line: the prior blog post was basically correct — we are dealing here with very rough estimates — but if all insurers are subject to similar economic forces the Risk Corridor moneys paid by the government might grow somewhat. Still, it is not as if the cost of Risk Corridors is suddenly going to dwarf the cost of premium subsidies and cost sharing reductions already required by the ACA.

 

 

 

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How much will it cost to restabilize the Exchange insurance markets?

Short answer: My best order-of-magnitude estimate is between $500 million and $1 billion for the coming year of which a third to a half could be attributed to the President’s decision to honor his promise to let Americans keep their existing health insurance.

Insurers are rightfully complaining that the move by the President to fulfill a promise he made to permit Americans with “substandard” but previously grandfathered policies to keep their health insurance is going to destabilize insurance markets.  There were such complaints going in to a meeting on November 15 between President Obama and selected insurance leaders and there were somewhat muted complaints coming out of the meeting. Insurers are concerned because the people who are now being given access to another market in which insurance policies may be cheaper are likely to be precisely the healthy people that insurers who wrote policies in the Exchanges assumed would be in those Exchanges.  Their concerns are important because unhappy and unprofitable insurers have a tendency either to stop writing insurance or to raise rates.  That hurts policyholders and it also hurts politicians who assured the public that the rates would be affordable. (The insurers are also upset because it’s a little challenging to uncancel policies on short notice, but we’ll leave that grievance for others right now.)

The instrument by which some are proposing to pacify the insurance industry for the surprise deprivation of healthy insureds is the hitherto obscure “Risk Corridors” provision baked into the Affordable Care Act (section 1342, 42 U.S.C. § 18062, for those scoring at home). It provides that the government cover up to 80% of losses an insurer incurs on an Exchange. It was always assumed — foolishly in my opinion, but assumed nonetheless — that this backstop would be costless because the government would also effectively tax up to 80% of profits via the same provision. If the insurers systematically lose money, however, because many of the people they thought would improve the Exchange pools with their good health are being given an option to separate themselves out and keep their old often-less-expensive and often-less-generous insurance policies, the Risk Corridors provision could cost the government a fair amount of money.

So, the question is, how much money is Risk Corridors likely to cost? To use the language from my prior post, how much VOOM?  If it’s a relatively small amount, that would suggest that the President (and others’) proposal to honor a campaign commitment to let people who liked their health plans keep them is a better idea than if it’s a relatively large amount of previously unbudgeted money. I thought we might try a back of the envelope computation to see what’s involved.

Time to trot out some calculus.  The Risk Corridors provision basically creates a mathematical function between profitability (as defined in that provision) and the size of a positive or negative transfer payment from the government to insurers writing policies in the Exchange.  So, if we knew the distribution of profitability of insurers under the Exchange we would calculate the mean payment (an “expectation” for those with some statistics background) the government would make (or receive). Of course, we don’t know that distribution yet, but we can make some guesses and get some order-of-magnitude estimates.

If one assumes that the distribution of the ratio between claims and premiums has a mean value of one (i.e. that insurers on average break even), the the expected payment of the government is zero.  That’s the assumption on which the Congressional Budget Office worked when it asserted that Risk Corridors would cost nothing. But what if one assumes that the distribution of the ratio between claims and premiums has a mean value of 1.1, i.e. insurers on average lose 10%.  We’ll also assume for the moment that the distribution of the ratio is “log normal” and that 95% of insurers have a claims/premiums ratio of between 0.922 and 1.22. If we do the math — here’s the link to the Mathematica notebook that stands behind these computations — it turns out that the average payment of the government is about 3% of the average premium (before subsidies).  If the mean of the distribution were 0.5, i.e. insurers on average have claims 50% higher than profits, and we hold everything else the same, the average payment of the government is about 34% of the average premium (again, before subsidies). So if, just for the sake of discussion, one assumed there were 2 million people in the Exchanges and that the average gross premium was $3,500, the government would end up shelling out $210 million per year to provide insurers with some relief if they lose 10% on average and would end up shelling out $2.37 billion per year to provide insurers with similar relief if they lose 50% on average.

The graphic below shows the size of the government’s Risk Corridors obligation as a function of the mean of the claims/premiums ratio under the continued assumption that the distribution is log normal and that the spread of the distribution is similar to that described above. With a little wiggle when the mean of the claims/premium ratio is close to one, the relationship is pretty linear.

 

Relationship between mean insurer claims/premiums and risk corridor payments
Relationship between mean insurer claims/premiums and risk corridor payments

To get the total bill for the government, however, we not only have to calculate risk corridor payments in relation to a premium amount, we also have to make a guess about how many people will enroll in the Exchanges and what their premiums will be.  It’s complicated because, precisely because of adverse selection, there’s likely an inverse relationship between the number of people that enroll and the mean of the claims/premiums ratio.  But since all we are trying to do here is get some order of magnitude estimates — the discussion of this Act has been hurt all along by false claims of precision — we can try to make some reasonable guesses.

Suppose, for example, that the relationship between the mean of the claims/premium distribution and the number of people enrolling in the Exchanges looks something like this.

Hypothesized ratio between enrollment and mean of claims/premium distribution
Hypothesized ratio between enrollment and mean of claims/premium distribution

What we can now do is graph the government’s overall risk corridor payments as a function of enrollment.  I’m going to assume that the average premium is $4,000 per enrollee.  That’s roughly the average $328 per month that Kathleen Sebelius reported for a silver plan.  If people flock to the gold and platinum plans, the average could be somewhat higher. This graph is essentially the headline of this blog entry.

Hypothetical relationship between enrollment and risk corridor payments
Hypothetical relationship between enrollment and risk corridor payments

So, what we we see is that if, for example, enrollment for this year were to be 1 million, the total risk corridor payments might be somewhat in excess of $1 billion. If enrollment were 2 million, risk corridor payments might be $500 million.  One enrollment crosses 3 million, the government actually could gain money via the risk corridors program.

There are a lot of unknowns going in to the graphic above.  I do not pretend that it is precise.  I do not even contend that it is accurate.  Nonetheless, I believe it is useful.  I do believe it provides a plausible order-of-magnitude estimate of an unforseen cost of the Affordable Care Act.  If you asked for my best guess, I would tell you the Risk Corridor payments will likely be between $500 million and $1 billion this coming year as I would guess enrollment in the Exchanges will come out between 1 and 2 million (assuming they ever fix healthcare.gov).  This does not mean, by the way, that the cost of the President’s fix (or of the similar bills now in Congress) is the full amount of the Risk Corridor payments. Some of these risk corridor payments might have been made even without the Obamafix. That is so because enrollments in the Exchanges may always have been overestimated and may have been made considerably lower as a result of all the fallout from the debacle of the healthcare.gov website rollout.

In the end, then, I suspect that for the coming year the price tag for the President keeping his promise that “If you like your health plan, you can keep your health plan” is going to be somewhere in the $200 million to $400 million range for the coming year.  That’s about a third of the overall stabilization bill. And we’ll never know for sure because we won’t know how many of those that in fact do keep their health plan would have enrolled on the Exchange.  In one sense, the money cited above may be seen as a rather inexpensive price to pay to make good on an alluring promise.  On the other hand, it may also be seen as yet another unforeseen or unadvertised cost of a bill to transform American healthcare. It’s easy to make feel-good campaign promises when you aren’t fully honest about the cost.

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