In this issue, Foster et al.1 argue that the utility of personal genomic information and the level of evidence that is required to document utility depend on the context and audience. Similarly, others have suggested that the utility of genomic information be considered from three perspectives: the public health perspective, which emphasizes health improvements on a population level; the clinical perspective, which emphasizes the use of genomic information in diagnostic thinking and therapeutic choice; and the personal perspective, which may consider genomic information as having potential value per se, positive or negative, regardless of its clinical use or health outcomes.2
Foster et al.1 suggest that personal utility can be measured and used to identify which individuals are most likely to benefit from or be harmed by personal genomic information. In the clinical setting, patient decision aids provide individuals and clinicians with tools for assessing potential benefits and harms of clinical treatment options. For example, a number of decision aids have been developed to help individuals considering genetic testing for hereditary breast cancer assess the probabilities and importance of medical and nonmedical consequences.3 No one doubts that there will be challenges to developing decision aids to help consumers assess the potential benefits and risks of genomic information associated with slight elevations in risk of disease.
Foster et al.1 also propose that measures of personal utility be combined with measures of utility in terms of health outcomes to generate aggregate estimates of benefits. However, they do not provide practical advice on how to do so. The subjective and multidimensional nature of utility makes it challenging to measure, as has been true in the case of metrics of quality of life (QOL). Measures of health-related QOL, both