Category Archives: Journalism

No, New York Times, “guesswork” is not the reason ACA premiums are rising

The New York Times, whose editorial board has long been a strong supporter of the Affordable Care Act, published an article on its front page yesterday in which the headline read, “Seeking Rate Increases, Insurers Use Guesswork.” And, lest there be much doubt that the article suggested that speculation — the sort that regulators might understandably reject as a basis for premium hikes — rather than hard facts were leading to the frightening premium hikes, here are some quotes selected by author Reed Abelson for publication:

“But many insurers, including those seeking relatively hefty increases below 10 percent, say they are asking for higher premiums because they remain unsure about the future and what their medical costs will be.”

“It’s the year of actuarial uncertainty, and actuaries are conservative,” said Dr. Martin Hickey, chairman of the National Alliance of State Health CO-OPs and the chief executive of the New Mexico exchange. “The safest thing to do is to raise rates.”

Yes, to be sure, there was the suggestion in other parts of the article that higher than expected claims were part of the problem, but both the headline and remaining comments suggest that the high rates of increase were the result of unsupported speculation.

Wrong, New York Times! If you actually read the justifications for the premium increases submitted by insurers and their accompanying actuarial memoranda, you can see there are two dominant themes: (1) higher than expected claims expenses and (2) diminution of federal subsidies to the insurance industry.  You can also see lengthy memoranda containing facts and figures explaining their experience last year and the basis for their trending those experiences into the future. And, while one need not invariably take the insurance industry at its word or at face value, this is an instance where they have to make the best case possible for their rate increases. Regulators will scrutinize insurers’ work. Misstatements or rank guessing would seem to be against the insurance industry’s interest.

So instead of quoting people, who might themselves be guessing, let’s look at what the insurers actually said. I am going to bore you with 17 representative filings from across the nation. I do so because I want to make clear that the evidence is overwhelming. Most of these are contained in or accompanied by lengthy memoranda containing elaborate tables justifying the increases. I’ve attempted to be diverse in my selection of insurers to avoid repetition of, for example, the Blue Cross position or the Aetna position.

1. Blue Cross and Blue Shield of Alabama

BCBSAL proposes an average 28% increase to rates for the products offered in 2015. The main drivers of the need for a rate increase are as follows:

• Single risk pool experience which is significantly more adverse than that assumed in current rates

• Medical inflation and increased utilization as indicated in Section 5: Projection Factors

• Expected increases in the average population morbidity of the Individual Market, also described in Section 5: Projection Factors

• Reinsurance program changes, described in Section 9: Risk Adjustment and Reinsurance

BCBSAL determined that the following items did not contribute significantly to the need for a rate increase:

• Taxes and fees: Minimal changes in the amount needed for taxes and fees, described in Section 10: Non-benefit Expenses and Profit & Risk

• Benefit changes: No changes to offered benefits for 2016

2. HealthNet of Arizona

The projected claims experience was developed using calendar year non-grandfathered 2014 experience. If our rate request is approved, the expected premium for the entire risk pool is $313.91 PMPM. This represents an increase of 24.7% in average premium. 2014 premiums received were $127,867,744. Claims paid were $171,764,569. Since 2014 medical costs are increasing with an annual trend of 5.5%. Prescription drug costs are increasing with an annual trend of 10.3%. Claims costs are 85.1% of premium. Administrative costs are 14.5% of premium. Profit is -4.8% of premium.

3. Cigna Health and Life Insurance Company (Connecticut)

The most significant factors requiring the rate increase are:

Changes in Medical Service Costs: The increasing cost of medical services accounts for the majority of the premium rate increases. Cigna anticipates that the cost of medical services in 2016 will increase over the 2015 level because of prices charged by doctors and hospitals and more frequent use of medical services by customers.

Transitional Reinsurance Program Changes: The federally mandated transitional reinsurance program is in effect for three years (2104, 2015, and 2016). The amount of funding available to issuers under the reinsurance program to offset adverse claim experience decreases each year ($10B in 2014, $6B in 2015, and $4B in 2016). Additional premium is required to compensate for the reduced reinsurance support in 2016.

Morbidity (Risk Pool) Adjustments: The marketplace for non-grandfathered individual plans is affected by provisions of the Patient Protection and Affordable Care Act (the Affordable Care Act) that became effective in 2014, including:
guarantee issue and renewal requirements
modified community-rating requirement
federal premium subsidies for low and moderate income individuals.

The effects of these 2014 changes when coupled with previous regulatory changes and overall utilization experienced in 2014 suggest that it is appropriate to increase the overall claim level assumption reflected in the premiums for individual plans in Connecticut.

4. Aetna Health, Inc. (Florida)

Why We Need to Increase Premiums
Medical costs are going up and we are changing our rates to reflect this increase. We expect medical costs to go up 10%. Medical costs go up mainly for two reasons – providers raise their prices and members get more medical care.
For policies issued to individuals in Florida, some examples of increasing medical costs we have experienced in the last 12 months include:
· The cost for an inpatient hospital admission has increased 8.0%.
· The average cost for outpatient has increased 8.4%.
· Costs for pharmacy prescriptions have gone up 8.0%.
· The use of outpatient hospital services has increased 4.5%.

What Else Affects Our Request to Increase Premiums
Several requirements related to the Affordable Care Act (ACA) impact these rates. These include:
· “Keep What you Have” and its impact on the population that will enroll in the plans covered by this filing
· Enhanced network access standards – which limit our ability to control the cost and quality of medical care
· Changes to required taxes and fees
· Phase-out of the Transitional Reinsurance Program which increases rates for plans issued to individuals

5. Humana Employers Health Plan of Georgia, Inc. (Georgia)

Many factors influence this rate calculation. The primary factors include
‐ Population health‐ Expected changes in the aggregate health level of all individuals insured by all carriers in the individual health insurance market.
‐ Claims cost trend‐ Changes in expected claims costs associated with changes in the unit cost of medical services, changes in Humana’s contracts with hospitals, physicians, and other health care providers, and the increase or decrease in utilization of medical services including changes in the severity and mix of services used.
‐ Plan Changes‐ Changes to plan designs due to changes in federal requirements.

6. Wellmark Health Plan of Iowa, Inc. (Iowa)

Reason for Rate Increases The effective average rate increase for these products is 28.7%, varying by plan as listed in the table above. The primary drivers of the proposed rate increases include, but are not limited to:

• Adverse Experience/Risk Adjustment Transfer: The risk of the market is more adverse than what we had assumed in the current rates; which leads to a significant projected risk adjustment transfer payment to other carriers.

• Medical and Drug Inflation: Both increased utilization and increased cost per service/script contribute to projected claims trend.

• Phase out of Federal Transitional Reinsurance Program: As this program phases out over three years, the expected receivables from this program are smaller for 2016 than they were for 2015.

7. CareFirst of Maryland (Maryland)

The main driver of the financial performance of these products and the proposed rate increase is the very significant increase in average morbidity between 2013 (the pre-ACA pool which underwent underwriting) and 2014 (the post-ACA guarantee-issue pool). The allowed claims per member per month (PMPM) increased from $197 in 2013 to $391 in 2014, a much higher and faster increase than anticipated.

8. HealthPlus Insurance Company

The biggest driver of rate change is 2014 claims experience that is more adverse than assumed in current rates. Another driver is due to the lower Federal reinsurance recoveries.

9. Coventry Health & Life Insurance (Missouri)

Why We Need to Increase Premiums
Medical costs are going up and we are changing our rates to reflect this increase. We expect medical costs to go up 9.4%. Medical costs go up mainly for two reasons – providers raise their prices and members get more medical care.

What Else Affects Our Request to Increase Premiums
We offer individuals in Missouri a variety of plans to choose from. We are changing some benefits for these plans to comply with state and federal requirements.
Several requirements related to the Affordable Care Act (ACA) may also impact these rates. These include:
• Changes to our expected projected average population morbidity and its relationship to the projected market average for risk adjustment.
• Changes to required taxes and fees
• Phase-out of the Transitional Reinsurance Program which increases rates for plans issued to individuals

10. Aetna Health Inc. (Nevada)

Why We Need to Increase Premiums
Medical costs are going up and we are changing our rates to reflect this increase. We expect medical costs to go up 10.6%, excluding the effect of benefit changes described below. Medical costs go up mainly for two reasons – providers raise their prices and members get more medical care.

For Individuals in Nevada, some examples of increasing medical costs we have experienced in the last 12 months include:
• Primary Care Physician visits have increased by 124.2%.
• Inpatient bed days have increased by 51.0%.
• Expenses for emergency treatment have increased 22.7%.

What Else Affects Our Request to Increase Premiums
A prominent hospital system in Nevada moved from participating to non-participating in 2014 and is expected to stay that way into 2016. This has an adverse impact on claims costs since the more favorable lower-cost in-network reimbursement rates no longer apply.

Several requirements related to the Affordable Care Act (ACA) also impact these rates. These include:
• Enhanced network access standards – which limit our ability to control the cost and quality of medical care
• Changes to required taxes and fees
• Phase-out of the Transitional Reinsurance Program which increases rates for plans issued to individuals

11. Blue Cross Blue Shield of New Mexico (New Mexico)

[E]arned premiums for all non-grandfathered Individual plans during calendar year 2014 were $84,497,659, and total claims incurred were $105,605,811.

After application of the ACA federal risk mitigation provisions, the total BCBSNM Individual non-grandfathered block of business experienced a financial loss of 17% of premium in 2014.

The proposed rates effective January 1, 2016, are expected to achieve the loss ratio assumed in the rate development.

Changes in Medical Service Costs:

The main driver of the increase in the proposed rates is that the actual claims experience of the members in these Individual ACA metallic policies is significantly higher than expected. After application of the ACA federal risk mitigation provisions, the total BCBSNM ACA block of business experienced a loss of 19% of premium in 2014.

12. Medical Mutual of Ohio (Ohio)

Medical Mutual of Ohio is proposing an overall rate increase of 16.9% for plans effective January 1, 2016. This increase will potentially impact the 37,673 existing MMO members. The rate change ranges from 7.4% to 26.0%, varying by plan, age, change in tobacco user status, change in family composition, and the geographic area where the member resides.
The experience of MMO Individual ACA plans was not favorable in 2014. MMO has paid nearly $167 million claims and only received $114 million in premium. In 2014, MMO lost about $42 million dollars on its individual ACA business alone. With the rate increase implemented for 2015 and proposed for 2016, MMO’s experience is expected to improve, becoming profitable in 2016.
The following items are the main drivers for the proposed rate increase:
1. The transitional reinsurance recovery decreased from the 2015 level and will have a smaller impact offsetting the total claims.
2. The increase in the medical and drug cost is about 6.2% annually. Out of that increase, 40% is due to the change in unit cost, 31% is due to the change in utilization and the rest is due to the change in the mixture of services.
3. We expected the morbidity and demographics to improve in 2016 due to increased penalty of non-compliance, a greater understanding of the ACA law, and a reduction in the amount of pent-up demand for services. This alleviates the rate increase needed based on the experience.
4. There’s no changes in benefit from 2015 to 2016.
5. The administrative cost and commission will decrease $2.51 per member per month. The profit and risk will increase $7.92 per member per month. The taxes and fees will increase $4.51 per member per month.

13. Geisinger Quality Options (Pennsylvania)

Geisinger Quality Options has proposed an overall base rate increase of 58.36% for Individual PPO members renewing in the Marketplace effective January 1, 2016 through December 1, 2016. The overall increase is largely due to the claims experience in ACA compliant individual market plans being much higher than what was assumed in current rates. Other contributing factors include annual claims trend, federally-prescribed ACA fees and reduced benefits in the Transitional Reinsurance Program.

14. Pacific Source Health Plans (Oregon)

This filing requests an aggregate increase of 42.7 percent over the rates approved in our 2015 Oregon Individual filing. The proposed rates are based on PacificSource’s historical Oregon Individual claims experience adjusted for PacificSource’s historical average risk compared to the market average risk, anticipated medical and pharmacy claims trend, expected change in market morbidity from 2014 experience period to 2016 projection period, changes in benefits, and expected state and federal reinsurance recoveries. The proposed rates also reflect changes in the taxes and fees imposed on health insurers for 2016. The range of rate increases is 23.4 percent to 60.4 percent and impacts PacificSource’s 8,216 Oregon Individual members. The variation in rate increases is driven by some changes in benefits i.e. copays, deductibles, OOP max, as well as adjustments to geographic area factors. The overall average impact of benefit changes on the requested rate increase is 0.0 percent.

The increase in rates from 2015 to 2016 is primarily driven by a dramatic worsening of claims experience in 2014 as compared to 2013, and the reduction of expected reinsurance recoveries in 2016. Note that this is the first rate filing where a full year of post ACA experience data was available. This data shows that the overall increase in morbidity from PacificSource pre ACA experience to post ACA market experience is much greater than originally projected in our 2014 and 2015 rate filings. The combined medical and pharmacy annual trend used in this filing is 7.0 percent, which reflects expected changes in costs, changes in utilization, and the impact of leveraging. The primary driver of the annual trend assumption is specialty drug cost and utilization, particularly Hepatitis C drugs. Administrative expenses and margin are budgeted to decline compared to the 2015 rate filing.

Over the calendar year 2014, the Oregon Individual block earned 30.2 million in premium and incurred an estimated 50.0 million in claims, for a raw medical loss ratio of 165.2 percent. Premium and claims expenses are shown before the impact of reinsurance, risk adjustment, and risk corridor. At this time we do not expect risk corridor payments to be made to issuers. After expected risk adjustment and state and federal reinsurance recoveries, we estimate a 2014 loss ratio of 116.5 percent. Combined administrative expenses, commissions, taxes, and assessments were approximately 24.6 percent of premium.

15. Scott & White Health Plan (Texas)

The Scott & White Health Plan is requesting an average rate increase of 32.3% to the Individual HMO Rating Pool. There are 24,294 covered individuals as of January 2015. 10.0% of the 32.3% increase is due to health care cost inflation, 14.3% of the increase pertains to changes in Risk Adjustment and Reinsurance assumptions, 2.7% is due to changes in fees, and the remaining 5.3% is due to actual and expected unfavorable experience.

16. Optima Health Plan (Virginia)

The rate increase is the same for all members in the same plan. Where the 2016 plan is different than the 2015 plan these members will be automatically enrolled into the 2016 plan shown. Premium rates are effective January 1 2016.
Claims expenses were very high in 2014 relative to earned premium. However payments from the federal transitional reinsurance and risk adjustment programs are expected to help significantly.
The federal reinsurance program is only temporary and while it is continuing into 2016 the amount of reinsurance per claim is less than in 2014 and 2015. As such premium rates will be increased to account for this impact. Additionally the risk adjustment program alone does not appear to provide sufficient relief to enable the Company to meet its pricing targets.
It is anticipated that 2014 had some amount of higher claims due to new members having pent-up demand for services and less healthy people tending to be the first to sign-up for ACA-compliant plans given the new rating and underwriting rules. Because of this we do not assume that 2016 will necessarily be as high a claim level as seen in 2014 but some of what has been experienced will remain.
These reductions from 2014 levels will be countered by upward pressure on costs from other sources such as medical trend as described below.
The proposed rate increase is intended to account for expected claims activity in 2016 given historical experience and changes in morbidity as well as any expected assistance from the federal reinsurance and risk adjustment programs. With the proposed rate increase the anticipated loss ratio is 80 percent.
Medical trend for these products is anticipated to be an average of 7 percent per year on paid claims for example after member cost sharing or a total of 14.5 percent over the period from 2014 to 2016. This was developed based on historical experience as well as consideration for information available on general medical inflation trends. Medical trend includes a combination of utilization and costs of services. This increase in cost is included in the calculation of the rate increase.

17. Security HealthPlan of Wisconsin (Wisconsin)

The biggest driver of the rate change is SHP’s underlying claims experience used in developing the projected index rate. We used SHP’s 2014 individual non-grandfathered, ACA allowed claims as the basis for claim development. The 2014 claims and membership distributions indicate experience is worse than we priced for in 2015 rates. Further, based on a Wisconsin risk score analysis conducted by Milliman, we are projecting no risk adjustment transfer payment. This assumption of no payment results in higher rates in 2016 since we had projected SHP would receive money from the risk adjustment pool when developing the 2015 rates.

Another driver of the rate change is due to the lower federal transitional reinsurance recoveries in 2016. The recoveries assume in 2016 SHP will receive 50% of all SHP’s individual members’ per member per year incurred claims between $90,000 and $250,000. In 2015, rates were priced assuming recoveries to be 50% of claims between $70,000 and $250,000 based on the federal parameters in place at the time of pricing.

The projection of claims from the experience period to the effective period assumes 5.0% annual medical and drug trend. These trends were estimated based on data from SHP, conversations with SHP senior management, Milliman research, general industry knowledge, and our judgment of recent trends.

Conclusion

So, does this sound like “guesswork” to you?  It does not to me.  All of these insurers are lying or mistaken about what is causing their requests for premium hikes? I don’t think so.  Of course, there is “trending” in which insurers approximate how previous increases will continue to the future and this requires some art on the part of insurers.  Of course, insurers may want to present their requests for rate hikes in a way more likely to be approved. But what they have presented is no more “guesswork” here than the work of any insurer in setting rates for almost any form of insurance. It is the sort of actuarial projections that are generally approved by regulators.

Health insurers now have a decent feel what it is going to cost them to participate in Obamacare.  And these insurers have a pretty common perspective: the whopping increase are driven by  greater utilization than expected among those electing coverage  (adverse selection and moral hazard), increases in the cost of medicine, and reduction of federal subsidies.

Exactly what some people predicted.

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CBO projection of $8 billion from Risk Corridors is baffling

The Congressional Budget Office just issued a report that assumes the Affordable Care Act system of individual policies sold in Exchanges without medical underwriting can remain relatively stable. Tightly bound up with that assumption is its prediction about a controversial ACA program known as “Risk Corridors” that requires profitable insurers to pay the federal government up to 80% of profits they make on policies sold on the Exchanges but that also requires the federal government to pay insurers up to 80% of the losses they suffer from policies sold on the Exchanges.  The CBO now believes it has enough information to predict that Risk Corridors will actually make money — $ 8 billion over three years — for the government at the expense of insurers.

This CBO prediction of $8 billion in federal revenue, which has gained much publicity,  pulls the rug out from critics of the ACA such as Senator Marco Rubio who have introduced legislation that would repeal Risk Corridors as an insurance industry “bailout.” Such a blunting of Senator Rubio’s proposed repeal legislation is crucial in the ongoing battle over the ACA because repeal of Risk Corridors could  result in insurers (who just might not believe the CBO’s numbers) exiting the Exchanges for fear of having no government protection against losses resulting from unfavorable experiences in the new market the government has created. On the other hand, if the CBO is just getting its number wrong, Rubio’s case for repeal of Risk Corridors remains as strong (or problematic) as it ever was. The CBO projection is also important because Risk Corridors nets the government money if and only if the ACA works, insurers are able to make some profits, and a death spiral never takes hold. And this, as readers of this blog are aware, is a prediction about which many have serious doubts. 

Here’s the short version of the rest of this post.

I’ve done the math and I don’t see how the CBO is getting this $8 billion number unless it is assuming either very high enrollment in policies covered by Risk Corridors or very high rates of return made by insurers.  Or it made a mistake. I don’t think the CBO’s own numbers support very high enrollment in policies covered by Risk Corridors and I don’t believe either an emerging reality or the CBO’s own rhetoric justify assuming very high rates of return.  So I think the CBO ought to take a second look at its prediction. People should not yet make policy decisions based on the CBO estimate.

Reader, you now have a choice. I’m afraid that the next several paragraphs of this post become very technical. It’s kind of forensic mathematics in which one attempts to use statistics and numerical methods to deduce the circumstances under which something said could be true.  If that sounds dreadful, scary or tedious, I would not protest too loudly were you to skip ahead to the section titled “How could I be wrong?”  Before you leave, however, realize that what I am attempting to accomplish in the part you skip is a form of proof by contradiction. I prove that if what the CBO was saying were true, then insurers would have to be making 8% profit.  But nobody, including the CBO thinks they will make 8% profit, so the $8 billion number can’t be right.

On the other hand, dear reader, if you liked the Numb3rs television show (including my minor contributions thereto) or math or detective work or just care a lot about the Affordable Care Act, the rest of this post is for you.  What I am about to discuss is not only exciting math, but also the soul of the Affordable Care Act — whether the individual Exchanges without medical underwriting can remain relatively stable.

Forensic mathematics in action

Conceptually, here’s the calculation one needs to do.  What we want to figure out is the distribution of insurer profits (measured as a ratio of expenses divided by premium revenues)  upon which the CBO must be relying. I assume the CBO is using a  member from the “Normal” or “Lognormal” family of distributions because those are typical models of financial returns and there is little reason to think that the distributions of insurer profits (expenses minus revenues) will materially depart from those assumptions.  To continue reading this post, you don’t have to know exactly what those distributions are except that they look for our purposes like the “bell curves” you have seen for many years.  I’ve placed a graphic below showing some normal (blue) and lognormal (red) distributions. Although it should not matter all that much, I’m going to use a lognormal distribution from here on in because the ratio of insurer expenses to premiums should never be negative and the lognormal distribution, unlike its normal cousin, never takes on negative values.

Examples of probability density functions for normal and lognormal distributions
Examples of probability density functions for normal and lognormal distributions

The problem is that there are an infinite number of lognormal distributions from which to choose.  How do we know which distribution the CBO is emulating in its computations?  How do we know just how positive the CBO assumes the individual Exchange market is going to be on average or how dispersed insurer profits are going to be? As it turns out, the complexity of the lognormal distribution can be characterized with just two “parameters” often labeled μ (mu, the mean of the distribution) and σ (sigma, the standard deviation of the distribution).  Once we have those two parameters (just two numbers), we can deduce everything we need about the entire distribution.

Now, to solve for two parameters, we often need two relationships. And, thoughtfully, the CBO has given us just enough information.  It has told us how much money in total it intends to raise from Risk Corridors ($8 billion) and the ratio (2:1) between money it collects from profitable insurers and the money it pays out to unprofitable insurers. These two facts help constrain the set of permissible combinations of Risk Corridor populations (the number of people purchasing policies in plans subject to the Risk Corridor program) and insurer profitability distributions. What I want to show is that it takes an extremely high Risk Corridor population in order to get rates of return that are not way larger than most people — including the CBO — think likely to occur.

I first want to calculate the amount of money insurers would pay to HHS under the Risk Corridors program if the total amount of premiums collected were $1. Some of the payments — those by highly profitable insurers  —  will be positive.  Those by highly unprofitable insurers will be negative. To do this I take the “expectation” of what I will call the “payment function” over a lognormal distribution characterized by having a mean of  μ and a standard deviation of  σ.  By payment function, I mean the relationship shown below and created by section 1342 of the ACA, 42 U.S.C. § 18062. This provision creates a formula for how much insurers pay the Secretary of HHS or the Secretary of HHS pays insurers depending on a proxy measure of the insurer’s profitability. The idea is to calculate a ratio of “allowable costs” (roughly expenses) to a “target amount” (roughly premiums).  If the ratio is significantly less than 1 (and outside a neutral “corridor”), the insurer makes money and pays the government a cut. If the result is significantly greater than 1 (and outside the neutral “corridor”), the insurer loses money and receives a “bailout”/”subsidy” from the government.  The program has been referred to with some justification as a kind of “derivative” of insurer profitability, the ultimate “Synthetic CDO.

The graphic below shows the relationship contained in the Risk Corridors provision of the ACA.  The blue line shows the net insurer payment (which could be negative) to the government as a function of this proxy measure of the insurer’s profitability. Ratios in the green zone represent profits for the insurer; ratios in the red zone represent losses. Results are stated as a fraction of  “the target amount,” which, as mentioned above, is, roughly speaking, premium revenue.

How much the insurer pays (positive) or receives (negative) under Risk Corridors as a function of  measurement of profitability
How much the insurer pays (positive) or receives (negative) under Risk Corridors as a function of a ratio-based measurement of profitability

When we do this computation, we get a ghastly (but closed form!) mathematical expression of which I set out just a part in small print below. (It won’t be on the exam). I’ll call this value the totalPaymentFactor. Just keep that variable in the back of your mind.

Excerpt of the formula for insurer total payout
Excerpt of the formula for insurer total payout

I next want to calculate the amount of payments profitable insurers will make to HHS. To do this, we truncate the lognormal distribution to include only situations where the ratio between premiums and expenses is greater than 1. Again, we get a pretty ghastly mathematical expression, a small excerpt of which is shown below. I will call it the expectedPositivePaymentFactor.

Formula for expected negative insurer payments under risk corridors over a truncated lognormal distribution
Formula for expected negative insurer payments under risk corridors over a truncated lognormal distribution

Finally, I want to calculate the amount of payments unprofitable insurers will receive from HHS. To do this, we truncate the lognormal distribution to include only situations where the ratio between premiums and expenses is less than 1. Again, we get a pretty ghastly mathematical expression, which, for those of you who can not get enough, I excerpt below. I will call it the expectedNegativePaymentFactor.

Formula for expected positive insurer payments under risk corridors over a truncated lognormal distribution
Formula for expected positive insurer payments under risk corridors over a truncated lognormal distribution

The CBO has told us in its recent report that the government will collect twice as much from profitable insurers (expectedPositivePaymentFactor) as it pays out to unprofitable ones (expectednegativePaymentFactor).  We can use numeric methods to find the set of μ, σ combinations for which that relationship exists.  The thick black line in the graphic below shows those combinations.

 

Black line shows combination of mu and sigma that result in the correct ratio of positive and negative insurer payouts under Risk Corridors
Black line shows combination of mu and sigma that result in the correct ratio of positive and negative insurer payouts under Risk Corridors

To determine which point on the black line above, which combination of the parameters μ, σ , is the actual distribution, we need to use our information about the totalPaymentFactor.  The idea is to realize that the totalPaymentFactor must be equal to the quotient of the CBO’s estimated $8 billion and the total premium collected by Risk Corridor plans over the next three years.  But we know that the total premium collected should be equal to the mean premium charged by the Exchanges multiplied by the number of people in Risk Corridor plans. Some math, discussed in the technical notes, suggests that the mean premium under the ACA is about $3,962. And the CBO accounts for 8 million people being in Risk Corridor plans in 2014, 15 million being in Risk Corridor plans in 2015 and 25 million being in Risk Corridor plans in 2016. This means that the total premiums collected by insurers under Risk Corridor plans over the next 3 years should be about $190.2 billion. And this in turn means that the totalPaymentFactor must be 0.042.

Ready?

It turns out that of all the infinite number of lognormal distributions there is only one that satisfies the requirements that (a) the government will collect twice as much from profitable insurers (expectedPositivePaymentFactor) as it pays out to unprofitable ones (expectednegativePaymentFactor) and (b) for which the totalPaymentFactor takes on a value of 0.042. It is a distribution in which the mean value is 0.923 and the standard deviation is 0.113.  I plot the distribution below. A dotted line marks the break even point for insurers.  Points to the left of the break even line correspond with profitable insurers; points to the right correspond with unprofitable insurers.

Lognormal distribution of insurer profitability consistent with CBO data
Lognormal distribution of insurer profitability consistent with CBO data

Here are some factoids about the uncovered distribution.  The  average insurer will have expenses that are 92.3% of premiums and the median insurer will have expenses that are only 91.6% of profits. In other words, they will be making 7.7 cent and  8.4 cents respectively on every dollar of premium they take in.  For reasons discussed below, this is a difficult figure to accept. It is particularly difficult in light of the pessimistic news that is emerging about things such as the age distribution of enrollees , reports from Deutsche Bank that one of the largest insurers in the Exchanges, Humana, expects to receive (not pay!) a lot of money under the Risk Corridors program, the hardly exuberant forecasts of other publicly traded insurers about the ACA, and the recent general downgrading of the insurance sector by Moody’s partly because of the ACA.

Implicit in my finding about the most likely distribution of profitability is an assertion by the CBO that 76% of insurers will be profitable under the ACA while 24% will be unprofitable. About 17% will be sufficiently unprofitable that they will receive subsidies (a/k/a bailouts) from the federal government and 9% will be sufficiently unprofitable that their marginal losses will be covered at 80%. Only 15% of insurers will be “inside” the risk corridor and neither pay nor receive under the program.

How could I be wrong?

I feel  confident that I’ve done the ” gory math part” of this blog post correctly. Mathematica, which is the software I’ve used to do the integral calculus and the numeric components involved just does not make mistakes.  I also feel pretty confident that I understand how the Risk Corridors program works under section 1342 of the ACA.  That’s kind of my day job. And so, readers who skipped down to this part, I do believe that if the CBO were right about the $8 billion, that could only happen if insurers were, on average, earning an implausible 8% in the Exchanges.

If I’m wrong, then, it is because, except for the little issue I will mention at the end, I have made bad assumptions about the total premiums insurers expect to collect over the next three years in policies covered by Risk Corridors. That error could come from two sources. I could have the mean premium per policy wrong or I could have the relevant enrollment wrong. Let’s look at each of these.

Could I be wrong about the mean premium?

I computed the mean premium in the computation above by using data collected by the Kaiser Family Foundation on the ratio of premiums by age under most insurance plans and the typical Silver plan premium for a 21 year old (non-smoker). I then used the original forecast about the age distribution of insureds to compute an expected premium.  I got $3,962.  And this number seems very much in line with earlier HHS estimates, which were that mean premiums would be $3,936. So, I think I have the mean premium correct.

Could I be wrong about the number of people in Risk Corridor plans?

I computed the number of people enrolled in policies covered by Risk Corridors by looking at the CBO’s own figures.  I’m not vouching that the CBO is right in its projections, but this is not the day to argue that point.  The CBO now says (Table B-3, p. 109) that individual enrollment in the Exchanges will be 6 million, 13 million and 22 million respectively over the next three years.   And it says that employment-based coverage purchased through Exchanges (which I assume are SHOP Exchanges) will be 2 million, 2 million and 3 million respectively.  So , by addition, that’s where the figures I used of 8 million,  15 million and 25 million come from.  I’m not aware of anyone else who would purchase a policy subject to Risk Corridors. Again, bottom line, I don’t think I’m doing anything wrong here.

The little issue at the end: Could ACA definitions be responsible for the incongruity?

The only other conceivable explanation of the divergence between the CBO figures and my analysis is that I am failing to take a subtlety of Risk Corridors into account.  Remember, careful readers, that sentence earlier up that started out: “The idea is to calculate a ratio of “allowable costs” (roughly expenses) to a “target amount” (roughly premiums).” I stuck in the “roughlies” because the “allowable costs” are not exactly expenses and the “target amount” is not exactly premiums. When you look at the statute and the regulations, you can see that both of these terms are tweaked: basically you subtract administrative costs from both values.  And you subtract reinsurance payments from expenses — but that makes sense because the insurer reduced premiums in anticipation of those reinsurance payments.

So, in the end, I don’t see why these subtleties should affect my analysis in any significant way. But I am not infallible. And I do pledge that if someone points out an error to me, I will dutifully assess it and report it.

Sensitivity Analysis

Out of an abundance of caution, however, I have rerun the numbers on the assumption that premium revenue from policies subject to Risk Corridors is 50% greater than my original estimate either because of an underestimate of per policy costs or a failure to understand that there is some additional group within Risk Corridors protection.  When I do that, though, I find that the ratio of expenses to premiums is 0.943, meaning that insurers are still earning a pretty substantial 5.6%.  Although that is more believable than the earlier figure of 7.7%, it is still pretty high. 

Conclusion

To be honest, it makes me very nervous to say that the CBO did its math wrong or, worse, to accuse it of bad faith.  These are intelligent, educated professionals and they have access to a lot more data and a lot more personnel than I do.  Here at acadeathspiral  it’s just me and my little computer along with some very powerful software.  On the other hand, it’s not as if the CBO hasn’t been wrong before. It assumed earlier that the government would reduce its deficit $70 billion over 10 years as a result of Title VIII of the ACA (the so-called CLASS Act on long term care insurance) when many independent sources believed — rightly as it turned out — that the now-repealed CLASS Act was obviously structured in a way that could never fly.  The CBO assumed in July 2012 that 9 million people would enroll in the Exchanges in 2014, a number that is now down to 6 million. And, while there are explanations for each of these changes, the bottom line is that CBO is fallible too.

So, if I might, I would strongly urge the CBO to double check its numbers and provide more information on the data it relied upon and the methodology it employed in getting to its results.  I’d ask Congress, which has ongoing oversight of the ACA, to insist that the Congressional Budget Office, which is exempt from Freedom of Information Act requests from ordinary citizens, provide further detail.  American healthcare is indeed too important to have policy decisions made on the basis of what could be some sort of mathematical error.

Really Technical Notes

  1. I’m using a reparameterized version of the lognormal distribution that permits direct inspection of its mean and standard deviation rather than the conventional one, which in my opinion is less informative.   The explanation for doing so and the formula for reparameterization is here.
  2. To compute the average premium, I took the premium ratios used by the Kaiser Family Foundation, calibrated it so that a 21 year old was paying the national average payment for a silver plan purchased by a 21 year old. I then computed the expected premium over the distribution of purchase ages originally assumed by those modeling the ACA.
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Stunning report: only 11% of Exchange purchasers were uninsured

According to a report from reputable consulting firm McKinsey & Co. , only 11% of those purchasing health insurance in the individual health insurance market were previously uninsured. Although the report, discussed at length in a Wall Street Journal article, is the most extreme to date in examining whether the Affordable Care Act is, as promised, significantly reducing the number of uninsured or simply substituting one form of insurance for another, it is roughly in line with other surveys conducted recently. Michigan-based Priority Health reported that only 25% of its more than 1,000 enrollees surveyed in plans that comply with the law were previously uninsured. Health Markets Inc., an insurance agency that enrolled around 7,500 people in exchange plans, said 65% of its enrollees had prior coverage with, presumably, the remaining 35% uninsured.

The figures from McKinsey, coupled with the other survey data, are crucial to any evaluation of the success of the Affordable Care Act.  Its proponents like to brag that 10 million people have gained insurance as a result of the ACA.  As has already been pointed out by many, (see here and here) that figure is a grotesque exaggeration. But hitherto it had been assumed that at least a substantial portion of the individual Exchange purchasers were coming from the ranks of the uninsured. If the McKinsey report, which was based on a survey of over 4000 purchasers, holds up, it further reduces the number of people who have been helped in the most significant way by the ACA.

It is not enough that a few people have indeed been helped by the ACA. Billions of dollars of overhead have been spent on getting the individual Exchanges up and running.  Millions of people have been made to worry that their insurance coverage — imperfect as it may be — will be lost. Most likely, millions of individuals have already lost health insurance coverage as a result of the ACA. And, as I have discussed, millions of people dependent on small business as the source of their health insurance are likely to be further alarmed as those policies start to renew later this year. Many of them may lose advantageous coverage too.  There are many ways to improve people’s health with billions of dollars.   If the upside of Title I of the ACA — the part containing the elaborate individual Exchange mechanism is mostly a substitution of expensive ACA coverage — which, yes, has some additional benefits — for less expensive forms of coverage, then it those provisions are, to that extent, not making the sort of material improvement in people’s health that would constitute the only real justification for the expenditures.

The more modest ACA proponents (such as Jonathan Gruber on occasion)  have admitted that there will be losers as a result of the individual Exchange mechanism.  They have contended, however, that there will be a far larger number of winners. And ACA proponents have been quick to point to the 2.1 million (at last count) of enrollees in the individual Exchanges as amongst those winners.  If, however, 70-90% of those enrollees aren’t genuine winners but merely people cutting their losses, that is a very disturbing fact that must be given considerable attention in future debates over this landmark program.

Now, the McKinsey estimate is just that, only an estimate. Perhaps they have an axe to grind.  I don’t know. And, doubtless, we will see more work in this field in the months to come.  But it is hard to believe a reputable consulting company would fib or err by 30 or 40% on a statistic of this importance and that was bound to get a lot of publicity. Of all the things I have read, however, in the past month about the ACA, the fact that enrollment in the Exchanges may not even come close to equating with reductions in the number of uninsured is the most disturbing.

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No, 10 million have not gained coverage through the ACA

A blog entry by Josh Marshall on the Talking Points blog and largely repeated by Ezra Klein on the Washington Post WonkBlog contends that 9 or 10 million people have obtained coverage through the Affordable Care Act. This statistic, which I am frightened will be repeated by those predisposed to the Affordable Care Act until such time as it is deemed true, is just nonsense.  There is something called “causation” and just because A occurred and then B occurred does not mean that A caused B. There is also this arithmetic operation called “subtraction,” and while one can make a pile of numbers look bigger by neglecting to subtract off the ones that make the result smaller, such an omission corrupts the resulting sum.

Where does the 10 million figure come from?

The 9-10 million figure is comprised from 3.1 million people under the age of 26 who have coverage, 2.1 million people who have allegedly obtained coverage in the individual Exchanges, and 4.4 million who have allegedly obtained coverage through Medicaid expansion.  The graphic shows the computation. Each of the constituent numbers has serious problems.  And there are negative numbers that Marshall and Klein have neglected to take into account.

Marshall-Klein addition
Marshall-Klein addition

The 2.1 million counts people who have not paid for their policies

The 2.1 million figure has problems. It uses the “enrollment” number rather than the “paid for” number.  We don’t yet know the conversion rate between putting an item in one’s shopping cart — perhaps to preserve the right to obtain retroactive coverage — and actually paying for coverage.  Early conversion rates in some states, as discussed on this blog, have been less than two thirds. So, until we know how many people actually purchased policies, the 2.1 million represents an upper bound on coverage, not the actual number.

Mr. Marshall asserts, by the way, that it is “deep and intense form of denial” to say that people won’t pay for their policies.  All I can say is, “let’s see.”  I promise I will post on this blog a very unfun entry titled “I was wrong” if it is shown that at least 80% of the 2.1 million that have enrolled thus far actually get coverage in the Exchanges pursuant to the ACA.  Let’s see if Mr. Marshall is willing to make a similar promise if more than 20% don’t get coverage.

The 4.3 million Medicaid number counts people who would have obtained Medicaid without the ACA

As Klein though not Marshall acknowledges, the 4.4 million number is high because there would have been an expansion in the number of people in Medicaid even without the ACA provisions taking effect in 2014.  Moreover, as Klein has the honesty to concede, “some states are also counting people who’re simply renewing existing Medicaid policies.” So what’s the real number. Klein says he doesn’t know and I can’t say I do either. But, according to data from the Kaiser Family Foundation,  Medicaid enrollment increased by 3.4 million between 2008 and 2009, by 3.4 million between 2009 and 2010, by 2.4 million between 2010 and 2011 and by 1.3 million between 2011 and 2012.  Wouldn’t a fair minded person thus subtract  at least 1 million from the 4.4 million figure? Wouldn’t a fair minded person want to at least mention the issue?

By the way, I know that we are just counting people covered “because of” the ACA, but while we’re at it perhaps we should remember that more people are on Medicaid may not be this unalloyed wonderful thing. Many may be on Medicaid as a result of increased poverty or may be substituting Medicaid other health insurance coverage that they earlier had.

[Note: Following my publication of the original version of this blog entry, Sean Trende published on RealClearPolitics.com a far more detailed and, frankly, better analysis of this number that I have did here. He notes that much of the expansion in Medicaid numbers comes from states that did not in fact expand Medicaid.  His estimate is that the correct number of persons who received Medicaid coverage because of the Affordable Care Act is about 10% of the Marshall-Klein number, perhaps 380,000.]

The 3.1 million number counts people who already had coverage

The 3.1 million number apparently counts everyone under the age of 26 who has coverage under their parent’s policy. But what would the number be “but for” the Affordable Care Act? How many of the 3.1 million are insured “because of” the ACA. First, many insurers were already covering dependents up until age 25 or close thereto.  Two thirds of the states had laws required that they do so. Thank the states, not the ACA. Second, much of the effect is substitution.  Not all, but a good number of these young adults could have obtained coverage on their own through their job or otherwise but, because of the peculiar way many group policies obtained through an employer work, found it cheaper to enroll on their parents plan.  All the ACA does, then, with respect to these people is reallocate where people get their insurance and the costs different types of insurers face.  Actual scholarship conducted by the National Bureau of Economic Research found that found that early implementation of the ACA increased young adult dependent coverage by 5.3 percentage points and resulted in a 3.5 percentage point decline in their uninsured rate.  The National Bureau of Economic Research thus estimated the reduction in uninsured young adults caused by the ACA at least in 2010 at well less than one million.  Nothing to sneeze at, but not the 3.1 million claimed.

By the way, in case you mistrust the National Bureau of Economic Research, take a look at the work of the Employee Benefit Research Institute.  It too found that some young adults were substituting parental coverage for coverage they might have had to pay for through their jobs.  It too found that the ACA had increased the number of young adults with health insurance coverage, but not nearly to the same extent as the claim of 3.1 million made by these bloggers.

The ACA has also caused people to lose coverage

Marshall and Klein may be good at adding fake numbers, but they appear to have forgotten about subtraction (or how to add negative numbers).  There are a number of people who have lost health insurance coverage as a result of the ACA. There are likely to be a yet larger number who lose it when small business has to renew policies later in 2014 and finds those policies considerably more expensive. (I’ll be talking about this issue more in the next month or two). No one knows exactly how many people have lost coverage so far or how many will lose it in “the second wave.” Estimates of the first number range from half a million and up and I have estimated the second number as being many millions.  One would think an honest assessment of the effects of the ACA would not just ignore these negative consequences.  Even President Obama, by giving at least some of those people, a (possibly unlawful) exemption from the individual mandate has not gone that far.

And finally …

The Affordable Care Act can not be defended with the glib “it’s worth it if even just one person got health care coverage as a result.” There are a lot of ways to give people health care coverage and to improve people’s health. How that’s done can determine how much money it costs the government and what sort of a burden it places on individuals and businesses. That’s why it does in fact matter how many people are helped by the ACA and how they are helped.  That’s why it galls me that the grossly exaggerated 10 million figure is likely to get considerable play. If it were true, the figure would matter.  The problem is that it is neither true nor calculated in a way likely to get at the truth. So, when we assess the ACA, could we please stop the nonsense, add up real numbers, and remember about subtraction!

[Note: Following the publication of this blog entry, the Washington Post rated the assertion that 9 million people have gained coverage through the ACA a “Two Pinnochio lie.” It reserved the right to adjust (upwards, I presume) the number of Pinnochios, however, if it turns out that the 4 million Medicaid number isn’t right either.  I believe Sean Trende’s analysis (see above) makes pretty darned clear that the 4 million figure is a serious exaggeration.  I thus expect no fewer than “Three Pinnochios” being attached to the assertion by the time all is said and done.]

[Note: I just checked (February 5, 2014) and darned if the Washington Post didn’t upgrade the lie to Three Pinnochio status — “Significant factual error and/or obvious contradictions.”  See here and here. Good for the Washington Post!]

In fairness …

There are, actually, two things I like about the Marshall/Klein blog entries. The first is that Marshall points readers to the “Gaba spreadsheet.” This is one of several attempts to actually track enrollments under the Affordable Care Act.  It is a useful resource that, in conjunction with other data, should help people speak objectively about the ACA.  The second is their point that the decrease in the number of uninsured would be a lot higher if all states had agreed to expand Medicaid.  Yes, Medicaid would have cost a lot more for the federal government and, possibly, a bit more for the states, and, yes, there are ways other than provision of insurance to give people access to medical care or improve their health,  but the reduction in the number of the uninsured caused by the refusal to expand Medicaid is a point opponents of the ACA need to deal with.  I have this wish that people could stop treating the ACA as this monolith that is either all wonderful or all awful. Disentangling it may prove impossible and improving it may prove very difficult and/or very expensive, but, in the long run, misleading presentations of the facts do not help anyone’s health.

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Three questions for President Obama this afternoon

President Obama is holding a press conference this afternoon before he leaves on vacation.  Here are three questions I would put to him.

1. A number of small businesses will receive cancellation notices sometime this year because their plans no longer conform with the Affordable Care Act. There’s some controversy about how many such notices will go out, but clearly millions of people will be affected. Will the protections you have now afforded to individuals who had their plans cancelled this year such as exemption from the individual mandate and the ability to uncancel their policy likewise apply to small employers and those insured by them?

2. Your Solicitor General argued to the Supreme Court that the individual mandate, what you called the minimum coverage provision, was crucial to the Affordable Care Act, that it, unlike other provisions of the ACA were inseverable.  Here are quotes from pages 46 and 47 of the brief filed by your Solicitor General:

It is evident that Congress would not have intended the guaranteed-issue and community-rating reforms to stand if the minimum coverage provision that it twice described as essential to their success were held unconstitutional.

It is well known that community-rating and guaranteed issue coupled with voluntary insurance tends to lead to a death spiral of individual insurance.

Given the arguments made on your behalf, which may well have been correct, why are you not concerned that exempting more individuals from the individual mandate will not, as the insurance industry is complaining, destabilize the insurance markets and threaten the success of your legislation?

3. Are you concerned that while things are going better in some states such as New York, in many states such Oregon, Maryland, Texas there are a very low number of people enrolling in plans on the individual Exchanges so that even the most massive surge will not correct the situation before coverage begins January 1 or perhaps even before the end of March. Everyone agrees that low enrollment increases the risk that the markets in these states will become unstable?  If that risk materializes, what is Plan B?  What plans do you have to address the situation in those states?

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Rhode Island and Nevada data suggests many “enrollees” are not purchasing policies

Under intense pressure from the Obama administration to do so, the America’s Health Insurance Plans’ (AHIP) Board of Directors announced yesterday that health plans are “voluntarily” extending the deadline yet again for consumers to pay their first month’s premium. So long as the individual selects a plan by December 23, 2013, the individual will apparently have until January 10, 2014, to pay their first month premium and get coverage retroactive to January 1. Some states with their own Exchanges may impose different deadlines; the AHIP announcement is not binding on them.

The decision may boost the number of persons who end up with actual coverage in January but encourages people to play games with their insurance. It also further corrupts any meaning that might be accorded to the current metric of ACA success: the number of people putting a plan in their shopping cart.  With the extension of the deadline until past the coverage date and the potential for retroactive coverage, it now makes sense for virtually every American to enroll in the ACA.  This is true even of people who think the odds are extremely slim that they will ever actually purchase a policy. One just selects a plan free of charge before December 23  — personally I might pick a lavish Platinum one — but then decides whether to pay the premium and obtain retroactive coverage if and only if their health goes bad between January 1 and January 10 (or they would otherwise have purchased the policy).  Expect anecdotes of people paying their insurance premiums for retroactive coverage right after they get the bill from the doctor or hospital.

Why would the Obama administration facilitate games with health insurance purchases?

One reason the Obama administration may have taken the unusual step of permitting people to purchase health insurance retroactively is that it is concerned about its ability to handle large amounts of payments between now and the original deadline.  Recall that the back end of healthcare.gov is not functioning ideally. Data from Nevada and Rhode Island hints, however, at another reason that the Obama administration might have made this unusual request of insurance companies. These are the only two states that I can find that have released information on both the number of people who have selected a plan and the number of people who have actually paid so far for coverage.

The conversion rate in Rhode Island is 61%; the conversion rate in Nevada is a miserable 23%.

If these two states are representative of others on which the Obama administration indeed has secret data, perhaps more than a third of those counted as “enrolled” by virtue of putting a plan in their shopping carts may not have actually committed to pay for them. That figure could easily be as low as one half. It would then be yet less surprising that (a) the Obama administration has selected shopping cart placement of the metric for success and (b) keeps repeatedly extending the deadline people have to pay their premium bills.

Rhode Island

The data released by Rhode Island on December 13, 2013, covering the period through the end of November, 2013, shows that of the 2,649 it reported as having selected a plan, just 1,611 had accompanied that selection with a premium payment, a 61% conversion ratio. In other words, 39% of the enrollments are provisional.

Nevada

The data from Nevada from an earlier time is potentially worse.  November 12 Tweet shown below from Nevada HealthLink shows that at that time, when about 2,000 Nevadans had selected a plan, only 513 had paid for it. This is a conversion rate of roughly 26%, 74% would not have paid for the policy.

Data more recently reported in The Las Vegas Review Journal suggests that the low conversion rate may be getting even worse in Nevada. It reported today as follows:

The exchange didn’t release new sign-up numbers by press time, but it said on Dec. 10 that 6,629 consumers had selected qualified health plans, including 1,800 in the first week of December alone. It also told the Review-Journal on Friday that 1,537 people had actually paid for premiums.

If, so, even with the passage of time, the conversion rate is now just 23.2%.  This figure is consistent with reports from some inside the insurance industry. To be sure, this data is still early. And surely an additional number of those who selected after December 10  have now paid along with those who selected a plan after that date. But unless a lot of people are getting out their credit cards to pay health insurance premiums this holiday season, the conversion number in Nevada is rather frightening. Nevadans are likely experts in gaming, and the Obama administration’s pressuring of an acquiescing insurance industry to permit retroactive coverage gives them and gamblers everywhere an additional opportunity to beat the house.

 

Fun question for lawyers and law students

Why isn’t this collaborative extension of an offer to contract a violation of section 1 of the Sherman Antitrust Act? Hint is here.

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