Genetic testing is here, and getting cheaper by the month. But the fundamental problem with their application isn’t technical, but cognitive: most people are very bad at dealing with odds.
The first sequencing of the human genome — and, more relevantly, the rapidly falling costs of each subsequent one — hasn’t yet had the overwhelming impact on medicine predicted by early prognosticators. This has more to do with the dangers of journalistic metaphors than with any failure of science. All biologists, but few commentators, were already well aware than the distance between sequencing the genome and revolutionizing medicine is even greater than the distance between discovering a buried stone tablet inscribed in an unknown language and publishing a translated and annotated critical edition of its poetry.
Still, one area in which the availability of genetic information has made possible rapid progress is the statistical linkage of certain patterns in genetic markers and the risk of various diseases. But even in this application, marketing and hope run ahead of scientific understanding and technological possibility. The diagnosis of an existing disease can be definite, but genetic data, except for rare well-understood conditions, can give at best an educated guess about a person facing higher or lower odds of a disease than the relevant general population.
It’s easy to overlook the importance of this for public health. Mitigating the burden of disease on large populations is essentially a problem of resource allocation. Having more precise information about disease risks makes possible the more efficient use of an existing public health budget, with overall benefits for society.
But for individuals the benefit is less clear. It’s true that there has been some legislation enacted against discrimination — e.g., by insurance companies — based on the results of genetic tests, but even assuming that this legislation will prove effective (and the number of anti-discrimination laws that coexist with empirical discrimination is not small), poorly understood risk information can be very damaging to the psychological or even physical health of an individual. How should an individual react to the knowledge that he or she has an increased risk of developing Alzheimer? There is, after all, a huge difference between that result and a diagnosis. And correspondingly, a “clean bill of health” from a genetic test only means that disease risks are less than some baseline; pretending that it implies immunity against certain diseases will only lead to reckless behaviors and perhaps very much larger odds of developing those same diseases.
The problem goes beyond health issues, and comes from a fundamental inequality in modern society: most otherwise well-educated and prepared individuals are very bad at dealing with odds. The human brain is just not very good at probabilistic reasoning, and thus mathematically irrational phenomena like lotteries, not wearing seat belts, and panics about spectacular but very low-probability risks are regular features of our society.
Even worse, the very organizations that had made their business to understand and manage complex risk, the financial institutions, have put themselves in a position of certain disrepute, to say the least. Aside from many other reasons, this is unfortunate because theirs is precisely the know-how and advice individuals need if they are going to take advantage of the new barrage of health information coming from both research and their own genetic tests. Results are highly probabilistic in nature, and both medical choices and the financial scaffolding supporting them needs to properly take them into account. Even something as common as retirement planning needs to be based on a proper understanding of risks and costs, and of how new diagnostic and risk assessment technologies can influence them.
A competitive, transparent, and efficient health insurance industry would have been the natural framework for these undeniably necessary services to be offered. As the situation stands, it remains to be seen who will take over the role of helping people navigate the ever more complex labyrinth of health in the 21st century, and the precise form their business model will take.
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