آزمایش ژنتیک زمانی که ترکیبی از بیمه سلامت اجباری و داوطلبانه وجود دارد
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|24188||2002||18 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Health Economics, Volume 21, Issue 2, March 2002, Pages 253–270
When the insurer has access to information about test status, genetic insurance can handle the negative effects of genetic testing on insurance coverage and income distribution. Hence, efficient testing is promoted. When information about prevention and test status is private, two types of social inefficiencies may occur; genetic testing may not be done when it is socially efficient and genetic testing may be done although it is socially inefficient. The first type of inefficiency is shown to be likely for consumers with compulsory insurance only, while the second type of inefficiency is more likely for those who have supplemented the compulsory insurance with substantial voluntary insurance. This second type of inefficiency is more important the less effective prevention is. It is therefore a puzzle that many countries have imposed strict regulation on the genetic information insurers have access to. A reason may be that genetic insurance is not yet a political issue, and the advantage of shared genetic information is therefore not transparent.
On 26 June 2000, the leaders of both the publicly and the privately funded human genome projects announced that a draft of the human genome has been made. During the next few years, this knowledge is likely to be applied in the development of predictive tests for many diseases. The tests will be able to distinguish between high- and low-risk individuals at a pre-symptomatic stage of disease. Presently, tests for over 800 diseases are offered,1 including tests for Huntington’s disease and cystic fibrosis. Two important breast cancer genes (BRCA1 and BRCA2) have been identified, and the US Food and Drug Administration has approved a gene-based test that may help to predict the recurrence of breast cancer. The number of tests is expected to increase rapidly in a few years, in parallel to the mapping of the human genes. For instance, tests for genes that imply an elevated risk of several types of cancer, cardiovascular diseases, and Alzheimer’s disease are already available or are expected to be available in the near future. The information from gene-based tests may be important for initiating measures for postponement and prevention of disease. Genetic tests are also expected to have an important impact on the organization of health systems and, in particular, health insurance. There is a concern that insurers can make use of information to deny coverage for individuals with an increased risk of disease or require them to pay prohibitively high insurance premiums. Regulation of the access to, and the use of information from, genetic testing is therefore an important health policy issue in many countries, and the regulations imposed vary between countries. In the US, a majority of the states have banned the use of genetic information by insurers. The Congress in 1996 passed legislation that forbids group health organizations from denying coverage on the basis of genetic information. Efforts are also being made to extend the prohibition to all health insurers and to ban insurers from raising premiums based on genetic data (Schwartz, 1998). Recently (February 2001), a bill to prohibit discrimination on the basis of genetic information with respect to health insurance was introduced in the US Senate and referred to the Committee on the Health, Education, Labor, and Pensions. In Europe, there is mixed attitude. For instance, the Council of Europe, recommends (R(92)3 and R(97)5) that predictive genetic tests should not be used when the terms of insurance is decided. Among European countries,2 Belgium, Denmark, France, The Netherlands, Norway and Austria have approved restrictive laws while other countries have less formal regulation and might prepare regulation by law. In Finland, France, Germany, Sweden, Switzerland and The Netherlands insurance companies have chosen to impose a moratorium. In Norway, the majority of a public commission (Ministry of Health and Social Affairs, 2000) has suggested that insurance companies should have the right to require information about health status, including genetic information, for life insurance contracts exceeding a certain amount. The suggestion has led to much public debate and no support among political parties. Recently, also the Norwegian Biotechnology Advisory Board advised the government to turn down the commission’s suggestion. In the UK, the Genetics and Insurance Committee (GAIC) has been established by the Department of Health to give advice related to the use of genetic test results in insurance risk assessment. The Association of British Insurers (ABI) has given an assurance that if tests are not approved by the GAIC then their member companies will cease to use the results of the test and will retrospectively recalculate any insurance premiums affected. In September 2000 GAIC approved the use of genetic test results for Huntington’s disease in the underwriting of life insurance. GAIC (2000) expect that they in the near future will review all ten tests currently approved by the ABI.3 Given these conflicting trends of international policy, the challenge emerges whether economics has something to offer concerning the regulation of the insurance industry’s access to information from genetic tests. In particular, an important question is whether some institutions are better suited than others to reap the benefits and avoid the costs of genetic testing. Benefits accrue from testing as a precondition for prevention and postponement of disease, while social costs are both related to inefficient testing (as defined below) and less insurance coverage (due to adverse selection). In addition, testing may imply a premium risk and hence, an increased cost of insurance for high-risk persons. The purpose of this paper is to put together and apply central elements of economics to shed light on these questions. The focus is on two regulatory issues. Firstly, there is the regulation of access to information about a person’s test status. If access is restricted to the person concerned, we denote information as private. We denote information as public if the insurer has access to as much information relevant for risk assessment of a potential policy-holder as the policy-holder has himself. Notice that in this case the existence of private or public information is a policy issue, while in many other situations it is a characteristic of the market. Secondly, there is the regulation of the insurance market and especially the mix of compulsory and voluntary insurance.4 In particular, we are interested in the extent to which possible inefficiencies depend on the mix of compulsory and voluntary insurance in a system of health insurance.5 Two types of inefficiencies may occur. Firstly, tests may not be undertaken when testing is socially efficient, in the sense that testing implies a Pareto-improvement. Secondly, tests may be undertaken when testing is socially inefficient. We show that the first type of inefficiency is likely for systems with a high proportion of compulsory insurance, while the second type of inefficiency is likely for systems with substantial voluntary supplementary insurance. We show that inefficiencies are more likely to occur when information about a person’s test status is private than it is when the information is public. In relation to these results it is a puzzle that the legislation in many countries emphasizes the privacy of information. The paper draws on previous literature on this and related topics. Section 2 introduces the basic insurance model and Section 3 defines genetic testing and the main assumptions to be used in the analysis. Tabarrok (1994) offers a discussion of the potential benefits and costs related to genetic testing. He proposes a compulsory insurance against the consequences of being identified as a high-risk person through genetic testing. We derive Tabarrok’s main conclusion in Section 4 of this paper, and use the full information case as a benchmark for our further analysis. In Section 5 we assume private information of costs of prevention. In accordance with initiatives in many countries, we also impose the institutional constraint that insurers have no access to genetic information. Our analysis makes use of results from Doherty and Thistle (1996). In contrast to what is assumed in most of the literature, Doherty and Thistle (1996) assume that a consumer’s information about his risk status is endogenous. A consumer decides whether or not he wishes to obtain the information from testing. The optimal decision from the consumer’s point of view is shown to depend on the insurer’s access to information about test status and result. In this paper we take the analysis further by introducing the following two new features. 1. Prevention An important motive for testing is the prospects of a reduction in risk of disease by means of prevention. The effect of self-protection technologies on social welfare under alternative assumptions of access to information is studied by Hoy (1989). Hoy assumes that the consumers’ information about their risk status is exogenous. In the present paper the information is made endogenous by the consumer’s decision about whether to be tested or not. 2. The compulsory/voluntary mix of health insurance Everyone is assumed to have compulsory insurance, with everybody paying the same premium. In addition, a person may have voluntary insurance, with a premium adjusted to individual risk of illness. The mix of compulsory and voluntary insurance is an important health policy issue in most countries. It is highly relevant for policy makers to know whether the availability of genetic testing is likely to influence the properties of alternative systems. An important distinction is whether voluntary insurance is considered to be a supplement or an alternative to compulsory insurance. A few examples may clarify the distinction. A person with symptoms of disease is likely to make use of the compulsory insurance in the first contact with a physician. The visit may result in diagnosis and treatment or a referral to a specialist for further diagnostics and treatment. A referral may be accompanied by a waiting time before a specialist can be seen. The waiting time may be shortened by means of privately funded provision of health services. A privately funded specialist is then an alternative to a publicly funded. Once a diagnosis is made, treatment may or may not be provided by the public sector. For instance, expensive treatment may be rationed and some patients with treatment indications may be turned down. The private sector may then be a supplement for those patients experiencing rationing in the public sector. Also, a waiting time for publicly funded treatment may occur. The waiting list may be bypassed by means of privately funded treatment. In this case private care is an alternative to the publicly funded care. Hence, we see that some parts of privately funded health services may be considered an alternative to publicly funded services, while others may be considered a supplement. For instance, Besley et al. (1998) consider UK private health insurance to be somewhere between the two stylized alternatives. Section 6 discusses implications for public policy. A high degree of compulsory insurance seems to imply a disincentive to socially beneficial testing and prevention, in particular with private information about prevention. On the other hand, full insurance with premium independent of risk status is achieved. A high degree of voluntary insurance seems to imply an incentive to beneficial testing and prevention under public information and genetic insurance, and under private information also without genetic insurance. On the other hand, with private information there is also an incentive to undertake testing that is socially inefficient. Given the unfavorable effects of private information about test status, it is a puzzle that the policy of international organizations and individual countries referred to earlier are against making the information from genetic tests open to insurers. An important reason behind the privacy of information is that a person has a right not to know his genetic make-up. We show the incentive to undergo genetic testing is in fact greater with private information than with public information. Hence, the right not to know seems to be better protected with public information about test status than with private information. Hence, the British decision of using the genetic test result for Huntington’s disease in the underwriting of life insurance, may in fact be less threatening to the right not to know than if privacy of information had been imposed. Another matter is that this specific test is not socially beneficial, as defined in Section 3, since no effective prevention for Huntington’s disease is known. In the concluding remarks we suggest that an inefficiently high level of testing is likely to occur in the coming years, since genetic therapy is likely to lag behind the development of genetic diagnostics, and hence, limit the scope for effective prevention. Limitations of the analysis and suggestions for future research are also given. In particular, we argue that the analysis should be extended to incorporate group health insurance and health maintenance organizations, which are major institutions in the US.
نتیجه گیری انگلیسی
If we, despite of what is said above, take for granted that the privacy of information is a concern that health policy must adhere to, then a high degree of compulsory insurance has a virtue regarding both income distribution and access to comprehensive insurance. However, a high degree of compulsory insurance makes it less likely that socially efficient testing is done. On the other hand, a low degree of compulsory insurance makes it more likely that also socially inefficient testing is initiated due to incentives for risk sorting. The optimal mix of compulsory and voluntary insurance therefore depends on the kind of mistakes one is most eager to avoid. The second type of inefficiency is likely to be more important with ineffective prevention. Genetic tests are likely to be offered before effective treatment of genetic disorders are available (see for instance, Schwartz, 1998). The test for Huntington’s disease is an example. The potential social inefficiency attached to this uneven development of technologies is likely to be more prevalent the less compulsory insurance that a system contains. Among observers opinions differ regarding the importance of the issues that this paper has raised. The Economist (2000) argues that because of adverse selection the existence of insurance markets requires that genetic information be shared. The government is said to have a role to play in compensating the unfortunate in the lottery of the gene pool. On the other hand, Watts (1999) and Bonn (2000), refer to geneticists who argue that the fears of the impact of genetic testing on insurance are unfounded. The predictive power of genetics is said to be exaggerated. Although there are some useful predictive genetic factors for multi-factorial diseases, the associated risks are said to be too difficult to assess for underwriting purposes. This paper contains assumptions that should be modified and explored in future research. As described in Section 1, some parts of privately funded health services may be considered an alternative to publicly funded services, while others may be considered a supplement. We assumed that voluntary insurance is a supplement to compulsory insurance. It should be studied whether it makes any difference for our conclusions if voluntary insurance is assumed to be an alternative. We also considered the level of compulsory insurance as exogenously determined. An interesting extension would be to allow for an interaction between the level of voluntary insurance and compulsory insurance. For instance, the decision to buy voluntary insurance may have an impact on the level of compulsory insurance a consumer prefers and hence, on his voting behavior. We also assumed that all consumers consider their health risk to be average prior to genetic testing. As mentioned above in connection with the possibility of insurance against the financial consequences of testing, this is not quite realistic. For instance, family history may be used to distinguish between high- and low-risk individuals. An important modification is then to allow for consumers to have some ex ante information of their risk type. We assumed no preferences for good health, per se. The motivation for good health was confined to preferences for income. The consequences of including health as a separate argument in the utility function should be explored in future work. Hence, the introduction of state dependent utility functions, as in Strohmenger and Wambach (2000), will be an important analytic tool in future work. Finally, the type of voluntary insurance was confined to individual contracts. Hence, we disregarded group contracts, which is the main type of health insurance for employees in the US and also constitute a considerable proportion of voluntary insurance in Europe. Group insurance has some similarities with compulsory insurance, since the premium is often related to average risk. On the other hand, the insurance is often voluntary in the sense that employees are not forced to join. Research challenges involve the study of possible interactions genetic testing and simultaneous employment and insurance decision. Also, the specific functioning of health maintenance organizations, where insurance and provision of health services are integrated, should be further explored in this context.