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Google Is Training Machines to Predict When a Patient Will Die

bloomberg.com

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Re: Google Is Training Machines to Predict When a Patient Will Die

#21

Post by dekhn »

dapearce wrote: post #14
jand wrote: post #4

I would feel quite unconfortable if every action taken (or not taken) by medic staff has to be second-guessed simply because there are financial incentives derived from this research. Customer A does not receive full medical support because "he's dying anyway"? Is there a way to ensure that such cruel use of the research is prohibited?

>Customer A does not receive full medical support because "he's dying anyway"? Unless the patient consents to stop or reduce care, this would be medical negligence, which is illegal (in the US). Medical providers are required by law to provide medical treatment with all the knowledge and skill they possess.

This is not factually correct.

Re: Google Is Training Machines to Predict When a Patient Will Die

#22

Post by Rainymood »

digitalzombie wrote: post #12

Why did they just use a logistic model instead of survival/time-to-event model? https://www.ncbi.nlm.nih.gov/pubmed/21478775 Uses cox regression model which is a survival regression model. Also the base model aka previous model they're comparing it to is a logistic regression and the link leads to a pdf about how to increase hospital efficiency it seems like. This sounds stupid and heartless. In statistic we got surv…

>I don't think people should be treated as dollar signs.

You're a bit late to the party, no? Basically mortality calculations and risk transfer is what the whole insurance business is based upon.

Re: Google Is Training Machines to Predict When a Patient Will Die

#24

Post by adrianN »

neurobashing wrote: post #20

I'm sure it's an interesting technical challenge with huge amounts of complex, nuanced debate involved, and it could have a huge impact on health care. That said, my wife is an oncology nurse, and I will bet everything that no machine will ever get better at predicting than an experienced, skilled nurse. Humans are built to read humans.

"ever" is a pretty long time though.

Re: Google Is Training Machines to Predict When a Patient Will Die

#25

Post by itschekkers »

I hate to pour cold water on this, but medical researchers have been predicting mortality for years.

For example, here's a paper from the 1980's also predicting when a patient will die, also using a couple of thousands of patients' data: http://europepmc.org/abstract/med/3816253

And, Google's paper wasn't published in Nature, it was in a new open access journal owned by Nature. In academia, that is like the difference between a really fancy porsche, and a really cheap volkswagen (two very different things, both owned by the same company).

Re: Google Is Training Machines to Predict When a Patient Will Die

#26

Post by carlmr »

itschekkers wrote: post #25

I hate to pour cold water on this, but medical researchers have been predicting mortality for years. For example, here's a paper from the 1980's also predicting when a patient will die, also using a couple of thousands of patients' data: http://europepmc.org/abstract/med/3816253 And, Google's paper wasn't published in Nature, it was in a new open access journal owned by Nature. In academia, that is like the differenc…

>In academia, that is like the difference between a really fancy porsche, and a really cheap volkswagen (two very different things, both owned by the same company).

I think you want to say Skoda or Seat. Both owned by VW and the cheap cars.

Re: Google Is Training Machines to Predict When a Patient Will Die

#28

Post by aaavl2821 »

This was a year ago so things may have changed, but a senior exec at one of the nations largest health systems told me they were looking to change their end of life care program and looked at dozens of AIs that predicted when patients would die. None of them came close to just asking doctors which patients they thought would die within 12-18 months

The point of the project was to make end of life easier for patients and families. Many patients get transferred between multiple facilities in their last few months, and few end up passing in a place and manner they'd like. This project aimed to ask patients and their families how they'd like to spend their last few months.

Initially the health system resisted this bc they wanted to keep patients in the hospital to make money off them, but then they realized these patients were in the hospital so long they weren't profitable. Then the plan was adopted quickly

Re: Google Is Training Machines to Predict When a Patient Will Die

#29

Post by chii »

joshgel wrote: post #15
baxtr wrote: post #10

Earlier quoted context omitted.

Thank you. Well, the way I understand it: her treatment history won’t be considered by any other doctor than her own. The reason for that is that she wasn’t part of a proper medical study. However, I believe there is value in her data. The last days she was treated with an experimental drug. If there was an open database on all cases with treatment history I could have looked into that and get a feeling what to expec…

This is partially true. Her data can't be used willy nilly (sp?). Hospitals and doctors offices can use this data for their internal operations, to improve efficiency, quality, etc and (honestly) profit. They can also use this data in research, but only with IRB approval for exemption from consent. Her data should be protected! Also, I would add that the data collected for routine patient care is often of significant…

> Her data should be protected!

but if it could be anonymized (i.e., the medical data such as blood tests, history of diseases etc disassociated with any names), then wouldn't it make sense to have this data be used for research?

Re: Google Is Training Machines to Predict When a Patient Will Die

#30

Post by himom »

With deep learning, actuaries were inevitably, mostly obsolete, at some point. It’s unpleasant to think, that in a way, tech can now readily disrupt nearly any arbitrary office-worker knowledge industry at will, destroying businesses and specialties and concentrate both capability and wealth in ever fewer hands. Coding isn’t a “forever” specialty either... self-coding machines will create languages, protocols and systems humans will likely be unable to understand, limit, modify, monitor or audit.
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