Mortality Risk Prediction by an Insurance Company and Long-Term Follow-Up of 62,000 Men

Background: Insurance companies use medical information to classify the mortality risk of applicants. Adding genetic tests to this assessment is currently being debated. This debate would be more meaningful, if results of present-day risk prediction were known. Therefore, we compared the predicted with the observed mortality of men who applied for life insurance, and determined the prognostic value of the risk assessment. Methods: Long-term follow-up was available for 62,334 male applicants whose mortality risk was predicted with medical evaluation and they were assigned to five groups with increasing risk from 1 to 5. We calculated all cause standardized mortality ratios relative to the Dutch population and compared groups with Cox's regression. We compared the discriminative ability of risk assessments as indicated by a concordance index (c). Results: In 844,815 person years we observed 3,433 deaths. The standardized mortality relative to the Dutch male population was 0.76 (95 percent confidence interval, 0.73 to 0.78). The standardized mortality ratios ranged from 0.54 in risk group 1 to 2.37 in group 5. A large number of risk factors and diseases were significantly associated with increased mortality. The algorithm of prediction was significantly, but only slightly better than summation of the number of disorders and risk factors (c-index, 0.64 versus 0.60, P,0.001). Conclusions: Men applying for insurance clearly had better survival relative to the general population. Readily available medical evaluation enabled accurate prediction of the mortality risk of large groups, but the deceased men could not have been identified with the applied prediction method

Obstetrical outcome valuations by patients, professionals, and laypersons: Differences within and between groups using three valuation methods

Background: Decision-making can be based on treatment preferences of the patient, the doctor, or by guidelines based on lay people's preferences. We compared valuations assigned by three groups: patients, obstetrical care professionals, and laypersons, for health states involving both mother and (unborn) child. Our aim was to compare the valuations of different groups using different valuation methods and complex obstetric health outcome vignettes that involve both maternal and neonatal ou

Insurance, genetic information and the future of industry self-regulation in the UK

This article begins by considering what the moratorium on genetic information and insurance does and how it fits with UK insurance law. I will explain how the moratorium waives the application of the much harsher ordinary insurance law on the disclosure of information to insurers. The second section examines the view that the UK’s moratorium is a credible and flexible solution to the problems of the insurance use of genetic information. I will argue that to assess credibility we need to consider two issues—industry compliance and individual enforcement mechanisms. I will argue that while there is currently a high compliance rate, this is predicated on the science remaining static. We have no good reason to assume that this will remain the case. Further, I will show that an individual has no meaningful way to enforce their position under the moratorium and thus it lacks a necessary feature of a credible solution. When considering the flexibility of the moratorium I will argue that the requirement for regular renegotiation offers only a technical flexibility, which is disadvantageous to an increasingly large minority of the population. In short, I argue that the moratorium is insufficiently credible or flexible to amount to an appropriate regulatory response to the problems of the insurance use of predictive genetic test information. The final section places the moratorium in the context of insurance law reform in the UK, and considers what the current approach to insurance law reform may mean for the future of the moratorium. I argue that the preference for self-regulation has left the UK with an outdated insurance law which is extremely harsh towards consumers. However, with the Law Commission’s recent success in getting the Consumer Insurance (Disclosure and Representations) Act 2012 onto the statute book, it is at least possible that bigger changes are on the horizon that might bode well for a new approach to insurance and predictive genetic information