Health Insurance and the Net

Individuals are risk averse. We buy insurance to mitigate our personal risks. One of the most important expenses in an individual's budget, whether it be out of pocket or as an employment benefit, is health care insurance. With health care costs rising, estimates place the the total amount spent on health care in the United States to reach 20% of GDP by 2017 (See NCHC Report), the importance of health insurance is rapidly increasing.

The value of available health insurance policies may be diminishing because of activity on the net. Activities, such as net browsing, filling out health surveys, and use of internet medical advise sites, are invaluable resources for insurance companies when designing policies. If insurance companies begin to data mine the net activity of an individual before offering an insurance policy, there will be a significant effect on the type and price of policies available to individuals. Two factors play into this change. First, the insurance company is making less of a "bet" on each individual as they have far more information on each person applying for health care insurance. Second, the use of data mining could expand the insurance companies' ability to exclude specific coverage due to pre-existing conditions. Neither of these issues are simply solved, but the importance of health care makes this an issue worth investigating.

More information = more accurate actuarial assessment

Although there are many problems with the ways insurance companies operate today, they are theoretically a system to improve social welfare. Insurance companies are useful because they pool the risks of individuals so those individuals are not responsible for large immediate costs. Most people end up paying more in premiums than the insurance company pays out in claims, but some pay less. Even if insurance companies paid for all legitimate claims, they would still be designed to make a profit off the difference between premiums paid in and claims paid out. This is a socially desirable result for a risk averse populace because they pay risk premiums so as to not be subjugated to the risk of a catastrophic charge.

With the increase in information an insurance company has regarding an individual, there will be a decrease in risk pooling. Through data mining, an insurance company can learn invaluable information about its potential subscribers. It can learn how well an individual takes care of himself, how often he feels sick, any significant indicators for future health risks, and close to anything else it would possibly want to know. What this leads to is a more accurate actuarial assessment of how much the insurance company will have to pay out for each individual. While this helps low risk individuals (insurance companies will be able to offer lower rates to low risk individuals), it will increase the price of insurance for high risk individuals, likely making that insurance to expensive to be purchased. Thus, through information gathering, insurance companies will account for risks through more accurate risk assessments rather than risk pooling.

This decrease in risk pooling will drastically reduce the social welfare of the country. High risk individuals will not be able to access many necessary health care services until much too late. Emergency departments, which are places of last resort, will become primary care providers for more individuals. As this occurs, not only has the health of those individuals become significantly worse, but the rest of the country has to pay for this health care through taxes. Instead of having risk pooling where low risk individuals pay slightly more for their health insurance than it will cost in the aggregate and allowing high risk individuals to access care when they need it, low risk individuals will end up paying far greater sums to support the government's provision of medical care and high risk individuals will be in much worse health.

The expansion of pre-existing conditions

One way insurance companies limit the coverage they provide is through pre-existing condition exclusions. Insurance companies will not cover health conditions that an individual had prior to enrolling with the health insurance company. This is limited by federal and state law to be a condition for which an individual has received medical advice or treatment in the past 6-12 months, and for which the individual did not have previous insurance coverage during that period.

With an increasing amount of available medical advice in the net, this protection against pre-existing condition exclusions disappears. Often the first action a person will take when feeling a certain way will be an internet search. Does the availability of medical advice in the net make this search the "receiving of medical advice/treatment"? It is unclear at this point, but if it is, then we may see a large reduction in coverage because many of our ails will be considered pre-existing conditions.

The problems with an expansion of pre-existing condition exclusions are the same as the problems mentioned above. Those individuals who need coverage the most will either not be able to afford the policies they need, or will not be able purchase those policies due to lack of availability. Once again, the burden will be upon the state, and thus tax payers, to pay for the health care of these individuals, and these costs will be greater because the care will be applied retroactively, which is a larger sum than if preemptive care were administered.

Solutions?

We run into a problem trying to prevent these negative effects by not allowing insurance companies to perform this data mining. We encourage the freedom to learn, and a prevention of data mining directly opposes this ideal. One way to limit the consequences would be separating identifying information from these net activities. This will make the actuarial assessments for insurance companies come from pool of risk, rather than an individual's risk, and will make it so information solicited in the net cannot be used to define a pre-existing condition.

This decoupling is a difficult task. Anonymity is not easy to come by in today's net, and this is especially true when the vast majority of individuals using the net are not interested or willing to put in the required work to be anonymous. If the protection is not on the user side, it will have to come from regulation. We could require all data acquired by insurance companies to be aggregated and disconnected from identifying information before being mined. This seems like a possibility as it allows insurance companies to still take the information and make their policies more accurately account for the risks of the population, while disallowing specific information on individuals applying for insurance.

Health insurance is an important enough element of our social welfare that we must account for these considerations. Regardless of what a perfect health insurance scheme may look like, we have to examine the current situation and at least guarantee that the insurance available not deteriorate.

-- MattDavisRatner - 12 May 2009