Estimating Adverse Selection Costs from Genetic Testing for Breast and Ovarian Cancer: The Case of Life Insurance

Abstract

ABSTRACT Genetic testing is a concern for insurers if they cannot use test results in underwriting. We model adverse selection in an insurance market with genetic testing for breast and ovarian cancer. Increased forces of mortality resulting from a family history of cancer or a positive test for a BRCA mutation are calculated. Using a Markov model, we estimate costs of adverse selection, assuming various testing and insurance purchase behaviors. Adverse selection should be controllable if companies apply strict underwriting rules, requesting cancer history and onset age for all first-degree relatives. If insurers fail to correctly identify the family history of the application and use it in pricing, adverse selection costs could become unbearable. GENETIC TESTING AND THE FEAR OF ADVERSE SELECTION Adverse selection can be defined as the process by which prospective policyholders may gain financial advantage through insurance purchase decisions based on risk characteristics known to them, but unknown and not revealed to the insurer. It is a source of concern for insurance companies because it could result in underpricing. Recent developments in the Human Genome Project, while offering medical promise, have further increased insurer fears about this issue. Indeed, in many jurisdictions, insurers are not allowed to ask for results of genetic testing. Several years ago, two gene mutations that affect the likelihood of developing breast and ovarian cancer were discovered. Commercial tests to detect the presence of these mutations are now available. Women who learn through genetic tests that they are at higher risk of death for breast or ovarian cancer may purchase more life insurance, which to them looks inexpensive since it is priced at rates set for average risks. Women who learn they are at lower risk after a negative test may purchase less life insurance. These two forces combine to increase the aggregate mortality of the insurance purchasers. If insurers do not have access to the test results, they are unable to identify which women are at higher risk and which are not. They have to increase premiums for everyone, driving those at lower risk out of the pool. This creates a spiral of increasing prices and a decreasing number of policies issued, which may threaten the financial solvency of the insurer. The debate about insurer access to genetic screening information has industry representatives pointing to the risk of adverse selection. They advocate mandates that would require that all test results provided to individuals also be made available to insurers. These insurers' request for a level playing field contrasts with efforts by consumer groups to increase the privacy protection of genetic information. Consumers are concerned that test information may find its way to employers or result in employment and social discrimination. They fear that the use of genetic testing by insurers could result in the creation of a biological underclass of uninsurable individuals. The issue is highly emotional and very political. While risk classification is unchallenged in some lines of business (smokers/nonsmokers in life insurance, distance from nearest fire station in homeowners' insurance), the use of genetic tests comes into conflict with social and moral concerns of society in the 1990s. These concerns have prompted legislators to regulate the use of genetic testing. Wisconsin was the first state to introduce a genetic testing law in 1992. Thirty-four states have now enacted laws prohibiting insurers of different types from using genetic information in their underwriting decisions. As of early 1998. more than 200 bills have been proposed in various state legislatures throughout the country that try to limit insurers' access to and use of genetic information (Jones, 1999). In March 1999, Sen. Olympia Snowe (R-ME) introduced a bill, backed by President Clinton and included in the GOP Patients' Bill of Rights, that would block insurers from denying coverage or setting premiums base d on genetic information or family history (Government Relations Weekly Update, 1999). …