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Google had created a tool that could forecast a host of patient outcomes, including how long people may stay in hospitals, their odds of re-admission and chances they will soon die.

That reminds me of something we covered in a Robust Engineering Green Belt course. That was similar to 6-Sigma Green Belt courses leading to a Black Belt certification, but more focused on Taguchi's work for robust design.

One case study was the analysis of the best way to assess if a patient that arrived at the emergency room with heart attack symptoms was really having a heart attack, or it it was something else. Hospitals ran tons of tests and used many patient factors in the determination. It turned out that you could get the most accurate assessment by using two tests and the interaction between those tests (that is, the results of the two tests, plus a calculation based on the two tests combined) than all the other stuff. It was odd that patient weight didn't matter. (I suppose obesity may increase your chance of getting a heart attack some day, but was not significant in determining if you are having one right now.)

So a computer program can use factors that have mattered in the past, and not use things that don't matter but people still consider because they seem like they *should* matter.
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