The story points to new research, published in the American Journal of Public Health, researchers at the Department of Veterans Affairs and the National Institutes of Health described a database they have created to identify veterans with a high likelihood of suicide, as the Times story (Fri, Jun 12, 2015, p A17) points out, " in much the same way consumer data is used to predict shopping habits."
The researchers set up a half a database that comprised variables associated somewhat with suicide cases between 2008 and 2011. They ran what I assume to be a machine learning algorithm on that. They then tried to predict what would happen with the remaining half of the database population. They then concluded that predictive modeling can identify high risk patients no identified on clinical grounds.
But predicting suicide is not like predicting likelihood one might buy a Metallica song, is it? How does the doctor sell the prognosis? "A machine told us you are likely to commit suicide."? Certainly some more delicate alternatives will evolve. A lot of the variables – prior suicide attempts, drug abuse – seem patent. Maybe doctors have just been more likely to guess on the side of life. If the Chinese government hacks the database, and sells the data, will the chance of suicide follow you like an albatross, and fulfill itself ?
Like so much in the big data game, the advance carries a quandary on its shoulder.
Related
http://www.nytimes.com/2015/06/12/us/database-may-help-identify-veterans-likely-to-commit-suicide.html
http://ajph.aphapublications.org/doi/pdf/10.2105/AJPH.2015.302737
http://ajph.aphapublications.org/doi/abs/10.2105/AJPH.2015.302737
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