
For Preventing Disease, Data Are the New Drugs - dnetesn
http://nautil.us/issue/21/information/for-preventing-disease-data-are-the-new-drugs-rp
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Mz
Poorly titled article. I am disappointed and only skimmed. I was hoping for
something about actually improving health using data.

A few random thoughts:

Genetics is probably the wrong place to look for explanations of the dramatic
increase in premature births. Environment and lifestyle changes are probably a
better place to look. If it were genetic, it should not be a sudden new thing
-- unless it involves genetic damage, which can happen from envirinmental
issues, which brings is back to environmental causes.

Genetic information can be amazingly empowering, but it is like a blueprint
for how to build the body. Ignoring how throughputs interact with that
information misses a big piece of the puzzle. Genetics are not destiny. They
are code and how that code behaves depends on what it is given to work with.

Insurance companies will have to change how they work. Insurance is about risk
management -- i.e. betting the odds. When the information you have about risks
changes dramatically, you have to bet differently. The current model cannot
survive in the face of emerging data of this sort. It will have to adapt or
die.

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blacksmith_tb
The bulk of this article seems to be concerned with potential privacy
implications of widespread sequencing of patients. Which is a worthwhile
topic, but not what you might expect from its headline. Some of the scenarios
seem tired to me, like the idea that insurers might penalize you for having
increased odds of expensive conditions (already against the law in the US;
also, why not imagine that they would give most of their customers discounts
for not having those risks?)

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navait
> “You don’t have to worry about having a hypothesis, a conclusion,
> beforehand.”

Sadly, in my world of biology and this has been a factor in the epidemic of
bad papers and unreproducible results. Most of this is due to the treatment of
p-values as a magic. If you run 20 hypotheses over p < .05, one is going to
show up as true, regardless of the data. Keeping your experiments in narrowly
defined scopes is still important to producing good science.

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gmarx
Didn't finish the article so maybe they eventually mentioned- didn't congress
pass a law against using genetic info to set insurance rates?

