4 ms·
Not a surprise. I worked on a ‘AI’ health insurance product for several years and even getting access to data was a struggle.
by Sevii 2y ago
Not a surprise. I worked on a ‘AI’ health insurance product for several years and even getting access to data was a struggle.
- dylan604 2y agoI really wish you had used "impossible" instead of "a struggle".
- deleted 2y ago[deleted]
- LifeIsBio 2y agoYep, I'm in the rare disease space. "impossible" is pretty appropriate. It's tricky. On the one hand, it's obviously not appropriate to be flippant about patient privacy. On the other, it's clearly that advancements in human health are being hindered by our current approach to (dis)allowing researchers access to data.
- AlexandrB 2y agoFor me it's a situation of "once bitten, twice shy". What are the odds the medical data intended for research will be handled correctly and not used outside of its intended purpose?
- LifeIsBio 2y agoNonzero, for sure.
- kfajdsl 2y agoWhat are the potential downsides to misuse of health data? Genuinely asking - I'm not sure what someone malicious would do with my health records, especially if it's anonymized.
- BadHumans 2y agoThere are several examples of anonymized data not being so anonymized after all and able to be traced back to the person. As far as what could someone malicious do with health records, you have a contingent of people in some states hunting down women for having abortions so that might be something you don't want getting out there. Or you might be someone in a very religious area and you don't want people finding out you're getting AIDS treatment.
- bpodgursky 2y agoI understand the theoretical concerns in these cases, but IMO it does not weigh heavily against the (conservatively) hundreds of thousands of annual deaths due to hindered medical research. It's hard to overstress enough how impossible it is to do even basic research across institutional health datasets, even you're a giant organization with a compliance team. It's soul-draining and frankly the reason a lot of smart people jump ship and work in finance or crypto or whatever, where you can accomplish something even if it's goofy.
- JTyQZSnP3cQGa8B 2y agoNitpicking but he gave you practical examples of stuff that already happened, not theoretical ones.
- bpodgursky 2y agoThose are both theoretical examples of what people might want do with re-identified medical data. They are not demonstrated harms of things that happened in real life.
- BadHumans 2y agoYou're not addressing the root concern which is that healthcare is notoriously insecure. Approaching this as "who cares if things get leaked" instead of improving security of records is why getting data is impossible.
- dylan604 2y agoIf a researcher can get the data, then so could someone else with less altruistic motives. So the good actor is slowed because of the bad actor. Unfortunately, there's very little way to prove the good is good and not crossing their fingers behind their back.
- vasco 2y agoPerhaps opening up access to data 5 years after the patient is dead would fix this.
- anitil 2y agoI'm not sure if this is relevant, but Ben Goldachre in the UK is working on how to get access to NHS patient data in a privacy-preserving manner [0]. My understanding is that you essentially submit your analysis and it is run against live data but you only recieve summary results. I'm not sure if this could be adapted to training. [0] https://assets.publishing.service.gov.uk/media/624ea0ade90e072a014d508a/goldacre-review-using-health-data-for-research-and-analysis.pdf https://assets.publishing.service.gov.uk/media/624ea0ade90e0...
- deusexml 2y agoThe problem with this approach is it is very hard to do data science with messy clinical data when you have no mechanism of investigating the data yourself.
- mandevil 2y agoI interviewed with a company that built a Electronic Medical Records system optimized for cancer treatment, licensed it for cheap, then took the data and paid for medical professionals to spend time normalizing the free-text notes data from the doctors (this was ~a decade ago, when LLM's were not really a thing, so they got trained professionals to do it instead). That was all a play to get the level of data they wanted for training AI to make new discoveries. They got acquired by a major pharmaceutical company, but I don't know of any major discoveries made from their data. Because even with real data this is a hard problem.