Genetics, insurance, and cardiomyopathies : a case study of hypertrophic cardiomyopathy

Abstract

The economic impact of genetic information on life insurance has been discussed since DNA-based genetic testing became available in the 1990s. Macdonald & Yu (2011) estimated the highest increases in life insurance premium rates were about 0.6% if genetic test results were undisclosed to the insurers. Howard (2014) concluded that premium increases could be as high as 12% if the insurers were unable to access genetic test results. Although these two studies used different methodologies, the differences in their conclusions were due to the inclusion of cardiomyopathies (inherited heart muscle disorders), which were absent in the first of these studies. Hypertrophic Cardiomyopathy (HCM) is the most common of these disorders with a prevalence rate estimated to be 0.2% in the general population. We identify a mathematical model of the impact of genetic testing in HCM in a life insurance market under adverse selection. Then, we estimate the necessary premium increases to meet adverse selection costs and survey significant factors leading to increases and decreases in adverse selection costs. A novel feature of our model is that it includes ‘cascade genetic testing’, which is the form of genetic testing that is the most associated with HCM, in nuclear families. We conclude that the range of possible adverse selection costs is large, but the costs with the most reasonable assumptions are small and consistent with Macdonald & Yu (2011). Much higher costs depend on ‘adverse selectors’ treating life insurance as a financial investment and taking out extremely large sums insured, and also disregard selection and ascertainment biases in the epidemiological literature.