Genetics, Alzheimer’s Disease, and Long-Term Care Insurance

Macdonald, Angus S.; Pritchard, D

doi:10.1080/10920277.2001.10595985

Cited by 20 publications

(29 citation statements)

References 9 publications

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“…This is not true of the markets for health and long-term care insurance, and it is possible that the conclusions in respect of them would be different. A recent study into long-term care insurance, Alzheimer's Disease and the ApoE gene is Macdonald & Pritchard (2000, 2001, and in the remainder of the paper we discuss that model.…”

Section: Heterogeneitymentioning

confidence: 99%

“…This point is not too important for comparing relative costs among ApoE genotypes, but it would matter in practice. Table 3 shows approximate underwriting ratings by genotype for applicants at ages 60, 65, 70 and 75 (from Macdonald & Pritchard (2001)). The model only gives AD-related costs, in other words, the single premium that would provide for care if AD occurred but not otherwise.…”

Section: Application To Long-term Care Insurancementioning

confidence: 99%

“…We shall see some examples from this, by way of introducing models for adverse selection. Later work has concentrated on measuring the impact of specific genes, including Lemaire et al (2000), , Macdonald, Waters & Wekwete (2003a, 2003b, Pokorski & Ohlmer (2000) on the BRCA1 and BRCA2 genes linked to familial breast and ovarian cancer; Smith (1998) on Huntington's disease; and Macdonald & Pritchard (2000, 2001 and Warren et al (1999) on Alzheimer's disease. Surprisingly, this short list includes most of the quantitative financial work on genetics and insurance.…”

Section: Human Genetics and Insurancementioning

confidence: 99%

“…The simple approximation of total LTC costs as a multiple of AD-related LTC costs is crude, and a great improvement has been obtained by Pritchard (2002), using a model of disability based on ADLs. Macdonald & Pritchard (2001) also looked at the possibility of adverse selection, assuming applicants might know their ApoE genotype but the insurer would not. Since they considered applicants at a fixed age, the cost of adverse selection depends on the proportion of each genotype who apply.…”

Section: Application To Long-term Care Insurancementioning

confidence: 99%

“…, for benefits increasing continuously (δ b = 0.05) and commencing on institutionalisation. Source: Macdonald & Pritchard (2001 epidemiology, which follows the discovery of the gene, which follows the discovery of a familial association; in the case of ApoE and AD, the elapsed time has been about ten years -rather longer than the media are accustomed to. The simple approximation of total LTC costs as a multiple of AD-related LTC costs is crude, and a great improvement has been obtained by Pritchard (2002), using a model of disability based on ADLs.…”

Section: Application To Long-term Care Insurancementioning

confidence: 99%

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Genetics and health costs: some actuarial models

Macdonald¹

2002

Law, Probability and Risk

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Concerns have been raised about the implications of genetics for insurance and care costs, both from the public's and the insurance industry's points of view. Insurers worry that applicants might have increasingly precise knowledge of their own risks, which will lead to adverse selection. Public worries focus on the creation of a "genetic underclass" that cannot get access to insurance or essential services. The most striking feature about this, often heated, debate is the almost total absence of numerical estimates of the cost implications.Actuarial modelling is beginning to provide such numerical estimates, in the first instance to the question of the costs of adverse selection if life insurers did not know genetic test results. The answers point to a sharp distinction between dominant single-gene disorders and multifactorial disorders. The former are rare enough that solutions outwith the free market should be sought, and (with some exceptions) the latter probably will not provide clear and reliable estimates of lifetime risk, distinguishable from lifestyle and environmental factors; they might therefore not meet criteria of accuracy and reliability such as those that govern discriminatory pricing in respect of disability.Health and long-term care insurance present more difficult problems, however. Genetical research itself is only beginning to unravel the complex influences on molecular pathways leading to disability, and epidemiological research on large populations has to follow. In this paper, we choose one disorder -Alzheimer's disease (AD) -for which a susceptibility gene is known, called ApoE. We discuss a mathematical model for AD and payments depending on AD, and illustrate the heterogeneity that might be introduced to risk pools by the ApoE gene. We give examples of the possible impact on long-term care insurance underwriting, of adverse selection in the insurance pool, and of AD-related care costs in the U.K..

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Section: Heterogeneitymentioning

confidence: 99%

Section: Application To Long-term Care Insurancementioning

confidence: 99%

Section: Human Genetics and Insurancementioning

confidence: 99%

Section: Application To Long-term Care Insurancementioning

confidence: 99%

Section: Application To Long-term Care Insurancementioning

confidence: 99%

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Genetics and health costs: some actuarial models

Macdonald¹

2002

Law, Probability and Risk

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Genetics and Insurance

Macdonald

2004

Encyclopedia of Actuarial Science

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Most actuarial modeling has concentrated on single‐gene disorders, because it necessarily relies on genetic epidemiology to parameterize any models, and that is where the epidemiology is most advanced. We can identify two broad approaches. A top‐down approach treats whole classes of genetic disorder as if they were homogeneous. This avoids the need to model individual disorders in detail, which in the case of multifactorial disorders may be impossible just now anyway. If, under extremely adverse assumptions, either extra premiums or the costs of adverse selection are small, this is a useful general conclusion; see for examples. In the long run, this approach is limited. A bottom‐up approach involves detailed modeling of individual disorders, and estimating the overall premium increases or costs of adverse selection by aggregation. Examples include models of breast cancer and ovarian cancer, Huntington's Disease, early‐onset Alzheimer's Disease, adult polycystic kidney disease and Alzheimer's Disease.

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Genetic Factors in Life Insurance: Actuarial Basis

Macdonald

2009

Encyclopedia of Life Sciences

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Insurance risk assessment is based on probabilistic models of the timing and severity of the event insured against. In the presence of genetic risk factors, the problem is similar to estimating age‐related penetrance and survival rates. There are no data from insurers’ past experience; all studies rely on the medical literature. Most actuarial research relates to severe single‐gene disorders, whose impact on insurance may be limited because of their rarity. Very little research has been done in respect of multifactorial disorders, but it may tentatively be concluded that they will have little relevance for life insurance. Key Concepts: There is concern that life insurers will use genetic test results to charge higher premiums to persons at increased risk, leading to an uninsurable ‘genetic underclass’. Insurers are vulnerable to adverse selection if applicants are able to conceal information relevant to the risk. Severe, dominantly inherited, late‐onset single‐gene disorders do lead to significantly higher premiums, but are sufficiently rare that it seems unlikely that adverse selection is a material risk. The genetic contribution to complex multifactorial disorders is not likely to be more important than that of other, well understood, risk factors.

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Genetics, Alzheimer’s Disease, and Long-Term Care Insurance

Cited by 20 publications

References 9 publications

Genetics and health costs: some actuarial models

Genetics and health costs: some actuarial models

Genetics and Insurance

Genetic Factors in Life Insurance: Actuarial Basis

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