Category Archives: Mathematics

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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Older enrollments in Exchanges could cost insurers about 10%

According to a news report from Reuters, which is being picked up widely, early figures from four states are suggesting that the pool of insureds enrolling in the Exchanges is older than anticipated.  If this situation persists and is not an artifact of either the particular states involved or simply the urgency with which older people applied, it further threatens the ability of the Affordable Care Act to sustain its plan of equalizing opportunity to acquire health insurance. This is so because, although older people do pay more in the Exchanges established by the Affordable Care Act, they pay less than would be actuarially appropriate.  Young people, by contrast, pay more.

Here’s the key passage from the Reuter’s report.

The Obama administration is aiming to enroll about 2.7 million 18- to 35-year-olds in the exchanges by the end of March, out of 7 million total, or about 38 percent.

Early data from Connecticut, Kentucky, Washington and Maryland show that so far more than 20 percent of the 23,500 combined enrollees in private insurance plans are 18 to 34 years old, ranging from about 19 percent in Kentucky and Connecticut to about 27 percent in Maryland. About 36 percent of enrollees across the four states are 55 to 64. Additional demographic data is expected from California on Thursday.

A back of the envelope computation shows that this situation could result in additional losses of about 10% by insurers before risk adjustment payments are taken into account. And this is true even if each age group in the pool is as healthy as anticipated.  The insurer  losses resulting from disproportionate enrollment of older insureds has several important consequences: (1) insurers may decide to exit the pool in the future; (2) insurers may decide to raise premiums to adjust to the real pool as opposed to the projected pool; and (3) the government is going to pay more in Risk Corridor payments than anticipated.

Relationship between "true ratio", percent young in the pool, and Exchange insurer profitability
Relationship between “true ratio”, percent young in the pool, and Exchange insurer profitability

The graphic above attempts to explain the issue.  The x-axis shows the “true ratio” of expected medical claims to be paid between the oldest people in the pool and the expected medical claims to be paid of the youngest people in the pool.  No one knows this figure for sure, but it could well be about 5 to 1.  (This is why the Affordable Care Act is forced to hold premiums to a 3 to 1 ratio; otherwise premiums for the older group would be extremely high.) The y-axis shows the percentage of people entering the Exchange pools who are between 18 and 35. As the Reuters story indicates, it was hoped this group would comprise 38% of the pool.  The green dot shows the result that might be hoped for if the young (18-35) indeed constitute 38% of the pool and the true ratio of claims paid between oldest and youngest is 5 to 1.  At this level, insurers neither make unusual profits nor suffer unusual losses.  The blue dot shows the result that might be seen if the young end up constituting — as the Reuters says the early evidence shows — about 20% of the pool. As one can see the red dot produces losses that are close to 10% of the risk assumed by insurers.

I’m placing a Mathematica notebook on Dropbox showing the computation. The idea,  is that one finds a linear relationship between age and premium relationship that just covers claims payments for any value of the true ratio but subject to the constraint that the premium the oldest person pays can not be more than three times bigger than the premium the youngest person pays and under the assumption that those under age 35 constitute 38% of the pool. One then determines profits for any combination of true ratio and percentage of the pool under age 35. The process takes a little algebra (mostly rescaling operations), some calculus (finding “expectations” of distributions) and some visualization.

Notes

1.  Although I modeled it that way, I am fully aware that the relationship between age and claims is non-linear.  It’s probably more cubic.  I’m also fully aware the relationship between age and premiums tends not to be linear under the Affordable Care Act. You can use the wonderful Kaiser Calculator or go to the fabulous Health Sherpa website to see that.  And I’m also aware that using a uniform distribution to model the distribution of ages within the 18-35 group and the 35-64 group is imperfect. Still, for purposes of getting just some rapid order of magnitude estimates to guard against those who would dismiss the problem or wildly exaggerate it, I believe the linear assumption is supportable.  It keeps things simple in a situation in which one has to be very careful about false assertions of precision and in which predictions are often hideously wrong.

2. As mentioned earlier, if the disproportionate enrollment of the elderly does not persist, as supporters of the ACA hope, the problem identified in this entry is reduced.  Other problems, such as disproportionate enrollment of the unhealthy — which is a far more significant issue — may persist.  But we don’t have data at present on the health of those enrolling.  It is troublesome, however, that most of the time proponents of the ACA trot out someone who has actually enrolled in the Exchanges (or  is  a Jessica Sanford who thought they would), it is someone who has higher-than-average medical expenses. I wish they would more frequently show off someone who is healthy now but just wants protection against the possibility of an adverse health event.

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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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