Asymmetric Information in the Healthcare Insurance Market Essay

If you think your health insurance expenses are high now, just wait. A couple of weeks ago I did my grocery shopping at a local Vons that is conveniently within walking distance of my apartment. I was getting used to seeing a barren parking lot; chased away by the union thugs. Just when I was about to enter the store, a picketer stepped into my path and gruffly gave me an unlimatum to shop at Stater Brothers. I politely smiled and told the picketer “I came to shop here.” These low skilled workers are fighting for their healthcare packages. Having worked on the actuaraial side of healthcare for the past few years, I empathize with the management.

Vons employees aren’t aware of what an amazing healthcare package they are blessed with. Grocery store union workers, before the strike, paid nothing for their copay and only $5 for a doctor visit/prescription medication. This truly is unheard of today. To begin with, the majority of Americans do not have privatized healthcare insurance and rely on state assisted programs. However, greater part of employees with privatized healthcare pay a share of their healthcare costs – now grocery store employees are being asked to do the same. It is apparent that the members of the UFCW (united food and commercial workers) union remain determined to keep their premium health care coverage at any cost, even if it is a benefit few workers emjoy.

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Costs for many workers are set to soar as employers remove the last key feature that helped hold down expenses for many consumers in the past two decades: lower out-of-pocket charges for such things as office visits, hospital care and prescription drugs.

Members of the United Food and Commercial Workers union who work in the Southern California grocery stores say they remain determined to keep their premium health care coverage, even if it’s a benefit few other workers enjoy.

“We work hard for what we get,” said Rodden Eltanal, 27, who works at a Ralphs supermarket in Los Angeles.

He said his co-workers fear that if they agree to start paying for their health insurance, the companies will only try to raise their costs in the future.

“Once they get you, they’re going to get you again,” he said.

Grocery employees make $15 an hour on average. The companies want them to pay a weekly premium for health care — $5 for an individual employee, $15 to cover an employee and his or her family, Calderon said.

The more than 3,000 Kroger Grocery workers on strike in the Midwest and South claim they would have to pay up to $100 more per week under the terms of the company’s pre-strike contract offer.

The chains say they must cut health care costs to compete with superstores that offer groceries and other retail items. Their fiercest competition is coming from Wal-Mart Stores Inc., which has opened Supercenters throughout the country.

Union leaders maintain the grocery chains are making enough money to continue the premium health benefits.

“They’re trying to shift these costs because they believe they can, not because they have to,” said the AFL-CIO’s Blackwell.

The Union blames management. Management blames Wall-Mart. How did Wall-Mart get involved? Wall-Mart recently announced their intentions to start opening grocery stores. Wall-Mart pays significantly less, does not hire union workers, and does not give good benefits. Vons (and the rest) position is that they need to lower their wages and benefits to compete. So who’s fault is it? The Union? Vons? Wall-Mart?

Background:

Symmetrical knowledge in the health care industry is non-existent. Insurance companies are plagued with deceptive consumers who masquerade as low risk buyers when in actuality, their indifference diagram suits that of a high risk individual. This creates a major problem for healthcare insurers and makes it nearly impossible to discriminate and provide actuarially thorough and just insurance premiums. The question at hand is how can this be done? Is there a different way to allocate healthcare? One way to bring the equilibrium closer to the pareto-optimality is by genetic testing. If mandatory genetic testing and disclosure were used in assigning health care coverage to consumers, economically speaking, it would be an effective method of ridding the asymmetries of adverse selection. However, one must also weigh the social consequences of such a program as mandatory genetic testing.

Introduction:

Asymmetric information in the healthcare insurance market creates insurmountable inefficiencies. To completely understand the concept of asymmetric information, I must first clarify the concept of adverse selection – a concept that stems from asymmetric information. The idea of adverse selection in the health care industry is made clear by thinking of two counterparts to a contract, each one having different amounts of information available to them regarding the buyer’s risk profile. This means that the issuer of the insurance is at an incredible disadvantage concerning the amount of information available that is needed to accurately calculate purchaser premiums. For instance, when looking to buy auto insurance, you know exactly how skilled of a driver you are – the insurance company has limited access to the majority of this information. They do have the ability to see infractions on your driving record, however, they are unaware of your carelessness. The insurance company has no idea that you committed for several hit and run accidents this past month or that you refuse to buckle your seatbelt. With health insurance, applicants have superior knowledge regarding their own health status and family medical history.

Given this shortcoming in the system, it is apparent that averse selection reveals that it is nearly impossible for the health insurance industry to predict consumer behaviour. Therefore, to hedge their risk, many insurers use the pooling equilibrium method to calculate forward rates for buyers. In the pooling equilibrium model, both high and low risk buyers are grouped together with a common premium and coverage. The insurer will then offer a coverage and price level that is somewhere between the demands of high and low risk demanders. This break-even strategy used by insurance providers to hedge their risk against the risky consumers. However, one issue stemming from the pooling equilibrium method of premium calculation is that the low risk utilizers are overcharged for their insurance relative to their risk tendencies. Given that low risk demanders are getting overcharged for their medical care, they will therefore drop out of the risk pool, which in turn will cause the average risk in the pool to increase, thus resulting in significantly higher premiums for the other remaining members.

Another method of premium calculation used to hedge risk is that of separating equilibrium. In separating equilibrium, the insurance agent will provide separate contracts to high and low risk individuals. Due to the problem of asymmetric information, it is possible for the higher risk individuals to pretend to be a low risk consumer, in so doing they are able to take advantage of a lower premiums. The outcome of separating equilibrium is that insurance provider loses considerably as high risk consumers claim on a regular basis, yet pay a premium that does not accurately cover these uncertainties and risks efficiently.

Mandatory genetic testing would eliminate information asymmetries. Inefficiencies and adverse selection would disappear, low risk purchasers receive the limited medical care they need at a fair and just premium. In the end, both high and low risk buyers are able to maximize their utility given their budget constraints. Thus, risk adverse consumers are satisfied and medical care is available at a reasonable price when ill. Technologically speaking, medicine will advance with early detection of diseases and disorders, eventually leading to the eradication of such illnesses. Sadly, currently genetic tests are expensive, which result in higher premiums. Test results may only give an indication of future illness without providing probability of occurrence. High-risk individuals could leave the market due to large premiums. Also genetic testing does not reflect income and implied health. It is quite clear that genetic testing is indeed economically desirable. Nevertheless, social and ethical ramifications should not be overlooked.

In the case of health insurance applicants have superior knowledge regarding their own health status. For example the previous family medical history will only be known by the individual. Alternatively genetic tests will indicate if a person has any genetic dispositions. In the near future self-genetic testing kits could be on sale indicating the probability of developing heart disease and obesity1. This information may not be disclosed and remain unknown to insurance firms. Hence individuals have greater knowledge but are not necessarily better off. Asymmetry of information leads to adverse selection problem.

Insurance modelling:

The model of insurance markets used in this essay is based on Ray Rees representation2. The probability of getting ill is p with (1-p) the probability of being well. Expected value line (EV) represents all combinations of wealth when well (w1) and ill (w2), such that the expected value of wealth equals endowment (w0).

EV = (1-p) w1 + pw2 = w0

E0 is interpreted as a budget line. Full insurance occurs if loss in earnings equals compensation. Fair insurance consists of paying a fair premium equal to the expected value of compensation.

Complete information:

Mandatory genetic testing and disclosure of its results means that health insurance companies will have exactly the same information as their applicants. Depending on the outcome of the genetic test, individuals will be placed into high or low risk pools. High risk buyers have a probability pH of contracting an illness, which is greater than the probability associated with low risk demanders pL.

In the graph above, it can be seen that both types of consumers are presented with a just and non-discriminatory contract. Both demanders are able to maximize their utilities given their individual budget constraints, since by definitions – indifference curves are tangent to their budget lines. In this diagram, a stable separating equilibrium is possible because of the genetic testing. However, high risk consumers desire the same contrat as low risk buyers because of the lower premiums. If genetic testing was not mandatory, then high risk buyers would lie and purchase the low risk contract, subsequently accessing a higher indifference curve.

Asymmetric information:

We have established that with asymmetric information the high riskers would be able to access the low risk health insurance due to the fact that insurers are unable to calculate and predict inherent risk. The probability of getting sick or suffering from an injury escalates while premiums and coverage stay constant. As a result of asymmetric information, halth insurance companies incur dramatic losses. This problem is called adverse selection. If genetic testing were not required, then in order to circumvent adverse selection, the pooled insurance method or the option of providing limited coverage for the low risk demanders are the two methods that insurers currently implement to reduce loss.

Pooled insurance:

The above graph shows that pooling the risks of both the high and low demanders is possiblity, but it is also inefficient and unstable. Since there are separating plans with lower premiums available to low risk individuals, low risk buyers will most likelyl not enroll in a plan where premiums are calculated using pooling. Consequently, low risk individuals opt-out of insurance coverage and will therefore not be covered in the even that the unexpected does actually happens. Additionally, the effect of low risk individuals exiting the risk pool will produce a higher claims mean and thus instigate higher premium for those remaining buyers. A domino effect will result as people drop out as premiums exceed the low risk demander’s willingness to pay.

Eventually, those who will remain in the insurance pool are the high risk individuals who from their utilization habits and lofty claims, must face higher premiums that they will not be able to afford, as they too will be uninsurable. Skyrocketing premiums and shrinking insurance risk pools will foment instability. Thus, the separating equilibrium, similar to the one under full information is the best alternative to seeking an insurance equilibrium. In order to discourage high risk individuals from masquerading as low risk, insurance companies may opt to have co-payments (pay x amount per visit), deductibles (pay x% per visit), or force purchasers to pay higher premiums if consistent illness occurs. However, with a sufficient number of low risk individuals, insurance companies who offer a lower premium or lower deductibles have a profit to make by targeting specific contracts for these individuals. Asymmetries of information have led to low risk people who can no longer get full insurance coverage or insurance contracts not targeting the right individuals. Some argue, genetic testing is the new wave to ending asymmetries of information and allowing for perfect information and full and fair premiums to reign.

Separating equilibrium:

The separating equilibrium method presents the option of partial coverage (at a fair premium) to the low-riskers and this method of partial coverage also discourages the high-riskers from purchasing the same health insurance. High risk demanders desire full coverage due to the fact that their chances illness or injury is far greater. As a result, full medical coverage is offered to the risky population at a larger premium. If the percentage of low riskers in the population is high, then E1 is the pooled expected value line. A health insurance carrier could offer a health plan represented by the shaded region that pools both types for buyers and makes still is able to make a profit. However, No equilibrium prevails, neither separating nor pooling just interchanging between separate and pooling contracts3. If percentage of low riskers in the population is low so that expected value line is below E* , then separating equilibrium is possible.

In support of Genetic Testing:

As previously stated, asymmetric information results in inefficiency since less than full insurance is offered to the low risk. Despite the fact that some of the low risk buyers desire full coverage and will thus pay higher premiums. They are unable obtain their most favored contract since their indifference curve is not tangent to the low risk expected value line. The highest possible utility level is not reached given the budget constraint.

Genetic testing overcomes the problem of adverse selection. Both risk types get full and fair insurance and have indifference curves tangent to their expected value lines. Insurance markets can prevent high risk from purchasing health insurance tailored for the low risk. Separation equilibrium can prevail, which will remain stable regardless of the percentage of low riskers in the population. All individuals have optimum contracts and they therefore have the ability to maximize personal utility given their probability of illness.

If the percentage of low riskers in the population is sufficiently large, the case for genetic testing is solidified do to the fact that there may not be equilibrium. If there were no equilibrium, as a result interchanging will occur between separate and pooled contracts. This would be incredibly costly for heath care insurers, especially in regards to administration and advertising expenses. .

Insurance markets provide an important means of wealth distribution. Insurance is needed to transfer wealth endowments that are uncertain (w1, w2) into specified levels. Most individuals don’t have an extreme preference for wealth when ill or well. They would prefer an equal distribution of wealth between the two states. Risk aversion is satisfied by insurance and guarantees a reasonable level of wealth when ill.

The pooling method is unfair to low risk buyers because they were paying a premium higher than their individual medical needs. If health care companies were to implement mandatory genetic screening, the chance of firms incurring major losses is reduced significantly. Also, an added benefit is that high risk demanders are unable to scam the system by lying about their state of health.

Genetic testing at a young age can lead to the prevention of genetic disorders. For instance, many families are predisposed to high cholesterol — which is a significant factor in coronary artery disease. Thus, with genetic testing, prevention is possible and premature death is avoided4. In addition, consumers are able to make informed decision, such as whether or not to have children, as severe genetic diseases could be passed on to the next generation.

Opposition to genetic testing:

In social context, genetic screening is struggling to justify itself. Putting the obvious right to privacy aside (HIPPA), “The vast majority of disease-related genes are only weakly predictive of whether someone will in fact develop the disease. Many other factors, including the individuals remaining genetic makeup and his or her lifestyle, are involved.” Diseases are linked to multiple genetic factors and in reality, only about 100 genes associated with late-onset conditions exist, half of which can be currently tested for. Furthermore, the early detection of those certain diseases and preventive measures available are being threatened by mandatory disclosure laws. For instance, although females who test positive for the BRCA gene (linked to causing breast cancer) can expect to live fewer than 9 years on average in comparison to females who do not carry this deadly gene, due to the threat of raised insurance premiums, situations such as will cause demanders to opt-out of testing altogether. The burden of knowledge is feared to trigger despondency among people who would otherwise not have tested and perhaps might even be used as a means of population control. Some opponents to genetic screening go so far as to say that mandatory testing will result in the existence of “an underclass of genetic unfortunates.” Further fears arise from the implications that the information from genetic testing might be used outside the health insurance industry in ways never expected (i.e. to deny people mortgages).

The current system used by some health insurers is a mandatory medical check-up for applicants prior to applying for a health insurance plan. With a required medical check-up, the asymmetry of information is reduced considerably. Also, some insurers require that new applicants and applicants switching providers grant access to past medical history. Although, given this stipulation, high risk demanders have an incentive to leave out relevant information on their applications. Opponents to genetic testing believe that it is an unreasonable invasion of privacy and individual rights. Thus, they advocate that this type of medical information remain strictly confidential between the doctor and the patient; no saleable reasons should over shadow this.

Conclusion:

It may seem as if genetic testing is the solution to adverse selection in the health care marketplace and should be made mandatory by allk insurers. The economic gains of efficiency are desirable. Everyone has full insurance and is maximizing their utility given budget constraints. However society’s tolerance towards genetic testing is debatable. However, genetic screening does not reflect income and implied health. Grossman’s study of demand for health has revealed that some of the health inequalities observed are due to income inequalities. Lower socio-economic groups have an inferior health level9. No one can control the genes they inherit so it is not justified to discriminate on the grounds of differing genes. Unnecessary distress is caused for people who have no serious defects.

Mandatory testing and disclosure is a huge infringement on personal privacy. Most people are already willing to perform medicals and truthfully report their health status. Some genetic diseases are more prominent in certain races. Thus, the issue of racial discrimination is another factor that stands against genetic testing. Although informed family planning is advantageous genetic testing could result in eugenics. This occurs when people refuse to have children with a certain partner due to them carrying mutated genes. This is already practiced in Greece, Turketyvand Cyprus10. Those of very high risk could become non-insured due to extortionately high premiums. When faced with illness they will struggle to live off their wealth and pay treatment bills. Mandatory testing would solve the economic problems of asymmetric information – but it could instigate just as many social problems for society.

Refrences

1. New Controls on Gentic Tests, Wednesday 5th February 2003 http://news.bbc.co.uk/1/hi/health/2723579.stm

2. Rees, Ray. Uncertainty, information and insurance, in Current Issues in Microeconomics.

3. Harris, Rodney. The Health of the Nation. The British medical Journal,1991

4. Donaldson ; Gerard. Economics of Health Care Financing, 1993. Chapter 3 ; 4

5. Wagstaff, 1986, The Demand for Health, Journal of Epidemiology and Community Health

6. Altman, Daniel.. “Genetics and Insurance.” The Economist. (April 2001) 1-6

7. Anonymous. “Leaders: Insurance in the Genetic Age.” The Economist. 3:57 (21 October 2000) 1-2

8. Bolger, Andrew ; Clive Cookson. “The Risks of Gene Testing: Advances Could Deny Medical Insurance to Many.” Financial Times. (7 April 2001) 1-2

9. Doherty, Neel. ; Leesa. L. Posey. “On the Value of A Checkup: Adverse Selection, Moral Hazard, and the Value of Information.” The Journal of Risk and Insurance. 65:2 (June 1998) 189-211

10. McPake, Barbra, Kumaranayake, Lilani, ; Charles Normand. Health Economics: An International Perspective, London: Routeledge, 2002.

1 Source: New controls on genetic tests, Wednesday 5th February 2003. http://news.bbc.co.uk/1/hi/health/2723579.stm

2 Source: Ray Rees, Uncertainty, information and insurance, in Current Issues in Microeconomics. Macmillan, edited by J.D. Hey, 1989.

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