Adverse selection in health insurance is the proclivity of insureds who accurately perceive themselves to be of higher than average risk to purchase insurance with greater frequency and, where possible, with higher benefits, than those who accurately perceive themselves to be of lower than average risk. Unchecked adverse selection can greatly restrict the amount of risk that can be transferred through an insurance market and cause a true loss to society. Insurers normally attempt to reduce adverse selection by “underwriting,” i.e. offering different contract terms based upon the insurer’s hopefully unbiased assessment of risk. Settings in which such underwriting is impracticable or unlawful create a serious impediment to optimal risk transfer.
The Affordable Care Act (a/k/a Obamacare) creates a risk of severe adverse selection by prohibiting medical underwriting in the sale of health insurance. One of the ways it attempts to palliate the contraction of the market that would otherwise occur is by subsidizing insurers in rough proportion to the riskiness of their insurance pool. Thus, although the high risk insured does not pay the insurer more for insurance than the low risk insured (except in limited ways for age, tobacco use and geographic location), the insurer ends up getting more for enrolling high risk insureds due to transfer payments made under the Risk Adjustment provisions codified in 18 U.S.C. § 18063. To establish this system, the government, among other things had to estimate the true “demographic risk” of individuals. By demographic risk, one means risk of medical claims independent of “ICD-9 diagnosable” medical conditions that the individual may have. This demographic risk is revealed in part by the age and gender of the insured but also by their selection from amongst four (or five) levels of expected benefits known as “actuarial value.” Persons purchasing policies with high actuarial value and thus having lower deductible and copay requirements, tend to be riskier than those purchasing policies with low actuarial value and thus having higher deductible and copay requirements.
The government data collected in this effort to implement Risk Adjustment under 18 U.S.C. § 18063 and placed in the Federal Register (78 F.R. 15409, 15422 (March 11, 2013)) gives us a rare opportunity to really see adverse selection in action not just as a matter of theory but as an empirical proposition. The interactive element below shows this clearly. It presents a graph showing for each gender and adult age level for which insurance through a private insurer is likely obtained, the relationship between the actuarial value of the plan selected and the risk factor posed. (Do not concern yourself with the units in which risk is measured). What one can see is that there is a definite correlation for all ages and genders between the actuarial value of the plan selected and the risk factor of the individual. The line turns pink when females are selected for examination, blue when males are selected for examination. If you see a picture but no interactive elements, you need to download the free CDF player available here.
[WolframCDF source=”http://mathlaw.org/wp-content/uploads/2013/04/a-picture-of-adverse-selection.cdf” CDFwidth=”600″ CDFheight=”400″ altimage=”http://mathlaw.org/wp-content/uploads/2013/04/a-picture-of-adverse-selection1.png”]
We can also show the relationship in which risk factor appears on the x-axis and the actuarial value of the plan purchased appears on the y-axis.
[WolframCDF source=”http://mathlaw.org/wp-content/uploads/2013/04/a-picture-of-adverse-selection-2.cdf” CDFwidth=”600″ CDFheight=”500″ altimage=”http://mathlaw.org/wp-content/uploads/2013/04/a-picture-of-adverse-selection2.png”]
One of the many interesting features of this visualization is that the data is independent of the insured’s knowledge of disease. Disease is dealt with separately by the regulations implementing the Risk Adjustment provisions of the Affordable Care Act. It is also apparently independent of moral hazard — the proclivity of insureds with higher levels of coverage to more frequently incur events covered by the insurance policy. In this context, moral hazard would mean the proclivity of people with, say, platinum policies that have low cost sharing, to visit medical professionals more frequently and provide less resistance to proposed expensive medical procedures than people with, say, bronze policies. That tendency is addressed in the modeling embodied in the Risk Adjustment regulations, but is addressed as a separate “Induced Demand” factor. Thus, not only do we get a well researched estimate of the actual extent of adverse selection, but we get its effects disentangled from those of moral hazard — at least if the government has done it right and I am reading the document correctly.
The picture also gives rise to a question. The Affordable Care Act permits insurers to price health insurance based on age. So, is provision of transfer payments that includes age in the mix “double counting”? Why does government need to subsidize that for which insurers already are compensated? Is it an effort to address the fact that the statute constrains the extent to which age counts, limiting the pricing ratio to 3:1 from most expensive age level to least expensive age level? I don’t know the answer to this question and welcome comments.