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Opening the Black Box (Part 2)Posted by Eric Schultz on December 12, 2010 7 comments
In my last blog, I explained how insurance premiums are calculated for employers having less than 51 employees and for individuals and how state regulations affect those rates. In this blog post I will provide examples that drive a:
- Premium decrease of 37%
- Premium increase of 16%
- Premium increase of 52%
…even when the medical cost trend is increasing at 10% in all three examples.
To keep the math simple, each example is based on an employer with two employees, but the same concepts are applicable to employers that have up to 50 employee lives.I also assume the customer will keep their benefits exactly the same.
For a quick review from the last post, the premium is determined by two components: the Base Rate – or the average rate for all small employers and individuals covered by an insurer – and the Rating Factors.
The Rating Factors allowed by state law are: Customer’s Industry, Customer’s Geographic Location, Size of the Customer and Percentage of its employees choosing to purchase insurance, Wellness and Tobacco Use and, most importantly, the age of the employees.
Changes in the average age of an employer’s employees can dramatically affect year over year premium changes. The age factor may increase or decrease significantly if the mix of employee ages changes. So here are three examples that are calculated using state regulated formulas that produce some surprising results:
37% Decrease: One group with 2 employees. A 60 year old and a 20 year old. If the 60 year old leaves the group, the premium renewal will be a 37% decrease.
16% Increase: Same group in the first example, but the 20 year old leaves. The group receives a premium renewal increase of 16%.
52% Increase: One group, 2 employees. A 45 year old and a 20 year old. If the 20 year old leaves the group, the premium renewal will be a 52% increase.
Intuitively, I get the first example. When an older person leaves the group, then insurance rates would go down. But the 2nd and 3rd example don’t make sense at first glance. Why would a two person group retaining the 60 year old produce an increase which is lower than when a group retains a 45 year old?
The detailed calculations are at the end of this blog, but the short answer is that state regulations require groups with younger employees to subsidize groups with older employees. In Massachusetts, the group with the oldest employees can’t be charged more than two times what the group with the youngest employees is charged, even though the true spread in medical costs is much greater.
To match the actuarial reality with the state regulations, Harvard Pilgrim first establishes rate factors for each age category. These factors range from about 0.4 to 2.4. We assign the appropriate age factor to each employee within a group and then calculate the average to determine the age factor that will be used to calculate the group’s rates. Under the regulations, the group’s factor must fall between 0.66 and 1.32. If the actual factor falls above 1.32, we assign it a factor of 1.32, resulting in a subsidy to that group. If the actual factor falls below 0.66, we assign it a 0.66, requiring that group to subsidize the pool. In our example, these rules work to limit the size of the increase for the group with the 60 year old employee (who receives a subsidy), but not for the group with the 45 year old employee (who does not).
The wide swings in premium rates that can occur have become a concern for policymakers. The Massachusetts Legislature recently enacted a new law directing the Division of Insurance to establish a so-called “bumper” or “cap” on how much any employer’s rates can increase because of changes in the average age of its employees. The good news is that this will limit the rate shock that some employers have experienced. It will, however, come at a cost. All small employers will need to pay a little bit more in order to fund the bumper. It may also have an unintended consequence of limiting choice, as an employer must stay with their existing employer to receive the benefit of the bumper. Harvard Pilgrim will continue to work with policymakers to strike the right balance when setting the bumper.
Now, for those who want to see the math on the three examples:
37% Decrease: Employer group is 20 and 60 year old. 20 year old age factor = 0.480 and 60 year old age factor = 2.016. The average age factor of this group is (0.480 + 2.016)/2 =1.248.
In year two, if the 60 year old leaves and the 20 year old remains, the employer group’s age factor would be 0.480. Since this is less than the minimum age factor of 0.66 (set by regulation), the age factor is increased to 0.66.
This produces a year over year decrease of 47% for the age factor of this employer group of (1.248 – 0.66)/1.248.
Combined with the 10% increase in the base rate produces a 37% decrease for this customer.
16% Increase: Employer group is a 20 and 60 year old. 20 year old age factor = 0.480 and 60 year old age factor = 2.016. The average age factor of this group is (0.480 + 2.016)/2 =1.248. If the 20 year old leaves and the 60 year old remains, the employer group’s age factor would be 2.016. Since this is greater than the maximum age factor of 1.32 (set by regulation), the age factor is decreased to 1.32.
This produces a year over year increase of the employer group’s age factor of 6% = (1.32 – 1.248)/1.248.
Combined with the 10% increase in the base rate produces a 16% increase for this customer.
52% Increase: Employer group is 20 and 45 year old. 20 year old age factor = 0.480 and 45 year old age factor = 1.177. The average age factor of this group is (0.480 + 1.117)/2 =0.829.
If the 20 year old leaves and the 45 year old remains, the employer group’s age factor would be 1.177. This factor is within the regulated range of 0.66 to 1.32.
This produces a year over year increase in the group’s age factor of 42% = (1.177 – 0.829)/0.829.
Combined with the 10% increase in the base rate produces a 52% increase for this customer.
I hope you see the point. Even if factors that affect a whole book lead to an average increase of 10%, specific employer groups may see very different results. When the mix of ages of its employees changes significantly, all bets are off. If young people leave the group, annual rates for the customer may increase dramatically.
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