7 ms·
Scalable and accurate deep learning for electronic health records
- deleted 9y ago[deleted]
- fwdpropaganda 9y agoHow did they get this data?
- oh_sigh 9y agoFrom the third sentence in the article: > To conduct the study, Google obtained de-identified data of 216,221 adults, with more than 46 billion data points between them. The data span 11 combined years at two hospitals, University of California San Francisco Medical Center (from 2012-2016) and University of Chicago Medicine (2009-2016). I know I'm not supposed to say 'Did you read the article?', so I won't say that.
- fwdpropaganda 9y agoIt was rhetorical. As in: They're not supposed to have this, why are hospitals giving Google our data?
- Thriptic 9y agoIf you deidentify the data, you're allowed to use it for R&D purposes.
- epmaybe 9y agoOn top of this, getting access to this data surely required ethical approval from multiple institutions (IRB). I am getting pictures from a few patients and I had to have a whole security audit on how the information would be stored and secured, along with who would have access.
- deleted 9y ago[deleted]
- Thriptic 9y agoYes, the approval of at least one IRB is also required.
- amsully 9y agode-identified is the key word here. That's how they attained the data in a HIPAA compliant way. Yes there are problems with combining that data with other datasets to re-identify. Google would be in a rather good place to do that.
- Sir_Substance 9y agoEven without googles abilities, it turns out that, to the surprise of no one, the medical field doesn't the level of information security expertise we might all wish they did: http://www.zdnet.com/article/re-identification-possible-with-australian-de-identified-medicare-and-pbs-open-data/ http://www.zdnet.com/article/re-identification-possible-with...
- mtgx 9y agoThat de-identification is probably the absolute minimum they have to do to achieve compliance, but don't mistake it and think that the data is actually anonymous. We've seen many studies show that 90%+ of the people can be re-identified from such datasets. Unless Google starts using fully homomorphic encryption or something similar, then you should consider that data non-anonymous. And until that happens, Google and national healthcare agencies should also require consent from the patients before giving the data to Google or any other company for such studies. Otherwise, I hope class action lawsuits will be started against both.
- quickben 9y agoI'm not sure why you are downvoted about this. I've went through 10 research papers on this very subject last week, all from 2016-2017, and this is a huge problem. Just because google does it, people assume it's infallible, where in reality there are bunch of methods to deanonymize data, from machine learning to pure mathematical models on binary vs categorical inputs and such. In this day and age, somebody will publish the deanonymized, cross-referenced (from voting registry or whatever) set online for free searching. Then again, most people are fine with this, as long as their names aren't on the list, so considering it's 200k sample out of 323M population, at most 0.7% will be really outraged. Which may explain the down votes he's receiving. 99.3% names aren't on the list, and from that set they want the scoop on the rest of their neighbors.
- lalaland1125 9y agoHomomorphic encryption currently doesn't exist in any useful sense. So you are asking for the impossible. If we followed your advice, medical record research would be impossible. All research comes with risks. Society is all about balancing those risks with there potential benefits. Come back with your criticisms when you have actual evidence of Google mishandling data or misleading the IRB boards.
- jnbiche 9y ago> All research comes with risks. And the core foundation of medical ethics is that the patient gets to decide if/how much of that risk to take.
- tzm 9y ago> Google obtained de-identified data of 216,221 adults... How much did this data cost?
- codefined 9y agoI imagine the cost of the data, in this case, is negligible when compared to the cost of salaries and benefits for employees working on it. Considering they have the ability to pick from thousands of hospitals and universities (the latter being where they actually got the data) they probably have a fairly large amount of leverage to keep the costs low.
- kprybol 9y agoHaving been privy to some of the contractual details of deals that Google has made with other medical centers, I’m betting that they probably got it for ”free”, as in they didn’t directly pay a set fee to the universities. Google most likely provided funding in the form of donations (tax write off), free cloud compute resources and/or cloud storage (write off), and the opportunity for university researchers to co-author high impact publications (everybody wins). Also, 200k patients is actually kind of small. Granted this dataset is far more granular/robust than what you’d typically find in commercially available healthcare datasets, but to give you some frame of reference, the healthcare datasets I work with contain > 20 million individuals (again, with orders of magnitude fewer features).
- dqpb 9y agoAs one of the apparently few remaining people on HN who like Google and are excited about the technology they're producing, I applaud this effort. I've had multiple doctors in my life who were worse for my health than seeing no doctor at all. Two of them outright looked up my symptoms (in a book in one case, and some shitty intranet in the other) to tell me what I already knew from googling it myself. We can do better than that. This is the way forward.
- brucephillips 9y agoAgreed. I've had a doctor google my symptoms in front of me.
- throwaway2048 9y agountil you realize its going to be people like insurance companies using this data to deny coverage and other stuff aimed soley at profiting on the people its harvested from. How much benefit does the average person get from being profiled like crazy across the web? Besides the (dubious) benefit of free services, there isnt much positive you can point to from such activity, and a shitload of really scummy exploitative crap. I dont see how such medical analysis is really going to pan out much differently at scale.
- Numberwang 9y agoHere in socialized Europe it will be very beneficial. Our health system focuses on solving problems, not selling us stuff. So this will be another great tool assisting with making us aware of what options we have in improving health outcomes.
- throwaway2048 9y agoPlenty of private for profit providers in europe too.
- PeterisP 9y agoYes, but since the mainstay of the financing isn't really based on private insurance coverage, the main objection doesn't apply. Really, denying insurance is pretty much the only legal-but-bad use case for such information. All other legitimate uses are good for the patient, balanced by an increased risk of crime and loss of confidentiality that may be embarassing but not profitable for anyone (well, except if there's some blackmail case).
- deleted 9y ago[deleted]
- Thriptic 9y agoI have very little hope for this succeeding, although I hope it does. I say this because this problem is vastly more complicated than people believe for the following reasons: * A substantial amount of data about patients is encapsulated in clinical notes which are free text. There is no standard format for notes; notes wildly vary in terms of quality, detail, and accuracy; and notes are full of non-standard abbreviations and clinical shorthand. * A large amount of the data in an EHR is incomplete or incorrect. Information may be out of date or recorded incorrectly. Patient medication lists are a great example of this, and they frequently cannot be trusted by physicians even during the course of a single hospital stay (medications are started or discontinued without being properly recorded). Then there is the issue of non-adherence: patients frequently claim to be adherent to treatment regimens that they are not actually adherent to which is going to distort outcome data. In fact, the majority of people are non-adherent for many different treatment regimens. More generally, diagnoses may have been incorrectly determined and data may be incorrectly labeled or missing. * Data exists all over the place even within an EHR, let alone across facilities. I myself have been to at least 5-10 hospitals and more outpatient clinics over my life, none of whom share data with each other. No one entity has all the relevant data about a patient, including insurers, specific care teams, or the hospital systems they got this data from. * Data placed into a EHR may be intentionally falsified for simplicity or to get insurance coverage. It is not uncommon for physicians to intentionally misdiagnose a patient so their insurance will cover a diagnostic / treatment / procedure, or to input a less specific diagnostic code to save time when a more specific one is available. Trying to train with data sets this fucked up is an enormous challenge.
- codefined 9y agoI feel like Google have the power behind them to try to at the very least data mine the free text data for information. Possibly they even have enough sway to convince doctors and other individuals towards a form that is far less random, or at least to provide a platform to share information between patients. Note that NLP seems to have come a long way in five years, who knows where we'll be in a decade or more. In terms of incorrect records, I'm not sure this would be a major problem over a large dataset. Making this up, but I imagine the range of errors is fairly random across all fields and with enough data you can always identify an approach that appears to save a life more than some other approach, even if the diagnosis is incorrect. Although I totally agree with you that this is going to be an enormous challenge for Google, I feel like it would be underestimating them to assume this has very little hope of succeeding.
- siculars 9y agoThe veracity of any analyses is directly correlated to the quality of the input. I have no doubt that Google's methods are state of the art. My concern is with the input those methods were fed. Sample size needs to be much, much larger on a patient population basis.
- tremendulo 9y agoElectronic bureaucracy has been developed to replace 1 or 2 brains plus paper records. However, put simply, it doesn't work. (e.g. I had to give my address three times to the same outfit last month just to get a flu jab.) But we can't go back to paper records so we'll try building a giant brain (AI) to try to decipher and manage millions of electronic records. Trouble is that that brain still won't have written the records or talked with the people they're about. So I doubt it will work.
- dang 9y agoThis is a case where discussion will likely be better if HN points to the paper rather than an information-poor popular treatment. We changed the URL from https://qz.com/1189730/google-is-using-46-billion-data-points-to-predict-the-medical-outcomes-of-hospital-patients/ https://qz.com/1189730/google-is-using-46-billion-data-point....
- jijji 9y agoIf this is for personalized recommendations about the Diagnosis or Plan for a particular patient based on past medical record history on that patient, this might be something that a hospital would want integrated into their current environment. If this, however, is something that takes multiple patients records into consideration, this would most likely never see the light of day. Most hospitals don't want anyone knowing that, for instance, their city has the highest number of leukemia related deaths per capita than any other city in the US.
- ci5er 9y agoDoesn't the CDC know that anyway?