The other side is that I have witnessed doctors making mistakes personally on medical files. They are overworked and only see you for 15 minutes and in a rush to kick you out and so of course they make errors. It would be interesting to compare whether transcription software or humans make the most mistakes. Guessing the answer will be very nuanced such as transcription software failing for accents not trained on, how over worked the clinic is etc.
There's another option, which is to have the consultation recorded and then transcribed by a third person, or at least have the transcript reviewed while listening to the recording. I think for medical situations it's more than reasonable to put in the labor to ensure correctness.
I am not an AI evangelist by any means, but it does serve a purpose when used correctly.
I feel like if you asked any half-intelligent AI "please review these notes and flag points we should review for correctness, or check with the patient?"
I'm pretty sure it would pick up a huge chunk of issues?
I think we need to keep in mind that medical and pharmacy mistakes are still extremely common
Recently my partner received a prescription with instructions that were over the LD50 (we caught it as it was obviously too high). We reported it but it was likely the case of the clerk simply hitting the wrong button and not double checking the resulting sticker
I’d be interested to see the AI transcription failure rate compared with existing medical/pharmacy rates
EHRs and other electronic prescription applications pretty much all have automated alerts for inappropriate dosages (like mg versus mcg) as well as allergies and harmful drug-drug interactions. The prescribing clinician likely had to dismiss at least one alert in making that error.
Not only did the AI apparently hallucinate psilocybin consumption, but the doctor then hallucinated internal bleeding as a risk, which is not a known risk of such mushrooms.
But this seems a bit click baity.
You can challenge your medical record, and presumably an AI transcription service would be in there. Unless .au is special in that way.
The doctor probably didn’t even read it and there’s a good chance the AI program wrote the bit about bleeding too. Source: am physician who has tried these programs and doesn’t use them.
Psychedelics do tend to cause dehydration as the body tries to filter them out, and if you don't have a steady fluid intake you can dry out pretty badly before it's done. (Source: I take LSD frequently)
I'd be hesitant to connect that to internal bleeding right off the bat though. Definitely would not trust claims that internal bleeding is a first-order effect of the drug.
It's easy to bring down the hammer of scope insensitivity by vividly describing a single person's struggle. The question is how AI affects error rates.
This response always comes up but I think it's not the whole story and gives "AI" a pass.
If I report a bug in (for example) Slack that loses messages and cost me a lot of time and headaches, is it an appropriate response to say "but Teams has even more bugs" or "sure, but if you had that conversation face to face you might miss something too"?
The question is how AI affects error rates and error recovery rates!
My experience dealing with ai-mediated processes is that the error recovery paths often simply don't exist, presumably because eliminating the personel that dealt with oddball and errors was the supposed benefit of having the AI deal with it in the first place.
Yeah, but also, if we can make AI do the same work cheaper than doctors, we can probably reduce the wages of doctors and save a bunch of money, which will both increase profits for health companies and reduce costs for patients. At some point, sufficient savings is better for patients than more doctors.
A friend recently had a drug test added to their blood draw for an unrelated health check at a hospital. When she questioned the nurse about it turned out the doctors make notes that are transcribed by AI. And in this case the AI had mistakenly transcribed that she was on fentanyl patches.
"the nurse who was trying to be very nice said in a less sweet tone that the doctor is supposed to review the notes so this does not happen. And that she is very glad I caught it and the doctor will be glad too. I do not know if this was something Very Serious or an ongoing problem or what."
Given this threads story is the second incident of this I've heard in a week it seems like it is a common error with very serious consequences.
Yes. Perhaps pushing sophisticated models that require validation, on users who most definitely won't (and the whole premise of the model itself is that it spares them work) was a bad idea...
Validation will measure accuracy, and even if you require and get > 99.9% accuracy (and they should! don't get me wrong), it won't change that there will be anecdotes of patients getting wrong results given that millions of people go to the doctor a year.
In fact, there will be MORE of those stories because it is shocking and strange, and clickworthy! The readers demand stories! But the reality is that there is no world where a story like this meaningfully informs the public about the accuracy of the services in question and the tradeoffs involved.
> even if you require and get > 99.9% accuracy [...] there will be anecdotes of patients getting wrong results given that millions of people go to the doctor a year.
This is known as the long tail problem in ML, and it's a reality in almost every field. It's also why we don't officially have self driving cars, despite there being thousands of videos out there with cars driving autonomously for hours without any errors. But every now and then, there will be cases where the system doesn't work.
There are two interesting aspects here. One, we don't actually have quantitative data on how often this happens in the same field when human errors don't get caught. In a perfect world we'd have that, plus a long study for the "AI" systems, and we'd get to compare the two. Secondly, even if we'd have that data, people would still act out against "the machine" in the (ideally fewer) cases where it errors out, compared to a doctor. It's part human nature, part (manufactured) rage against the machines.
I also agree with your second paragraph. Case in point, when a waymo hit a cat, we got a shit ton of articles, riled up communities, and so on. Or every time that other car hits something we get plenty of press, even if some of the "accidents" are fender benders that likely wouldn't get reported otherwise.
There are estimated hundreds of millions of medical transcription errors per year without AI. 42.4% of finalized medical notes still contained at least one error.
Prior to AI it would be about voice to text. Prior to that it would be some transcriber in India. Prior to that it would be the doctor themselves
The important question with any AI-related news story is what is the counterfactual.
Sure, it sucks if your self driving car gets in a crash or your AI scribe incorrectly transcribes something to your medical record. This is news now. What isn't news is humans getting into crashes or doctors making poor medical decisions as a result of low quality or missing notes.
I feel like if you asked any half-intelligent AI "please review these notes and flag points we should review for correctness, or check with the patient?"
I'm pretty sure it would pick up a huge chunk of issues?
Recently my partner received a prescription with instructions that were over the LD50 (we caught it as it was obviously too high). We reported it but it was likely the case of the clerk simply hitting the wrong button and not double checking the resulting sticker
I’d be interested to see the AI transcription failure rate compared with existing medical/pharmacy rates
But this seems a bit click baity.
You can challenge your medical record, and presumably an AI transcription service would be in there. Unless .au is special in that way.
I'd be hesitant to connect that to internal bleeding right off the bat though. Definitely would not trust claims that internal bleeding is a first-order effect of the drug.
If I report a bug in (for example) Slack that loses messages and cost me a lot of time and headaches, is it an appropriate response to say "but Teams has even more bugs" or "sure, but if you had that conversation face to face you might miss something too"?
My experience dealing with ai-mediated processes is that the error recovery paths often simply don't exist, presumably because eliminating the personel that dealt with oddball and errors was the supposed benefit of having the AI deal with it in the first place.
"the nurse who was trying to be very nice said in a less sweet tone that the doctor is supposed to review the notes so this does not happen. And that she is very glad I caught it and the doctor will be glad too. I do not know if this was something Very Serious or an ongoing problem or what."
Given this threads story is the second incident of this I've heard in a week it seems like it is a common error with very serious consequences.
So even the doctor forgot what they had talked about, and assumed the transcription was right? Crikey.
In fact, there will be MORE of those stories because it is shocking and strange, and clickworthy! The readers demand stories! But the reality is that there is no world where a story like this meaningfully informs the public about the accuracy of the services in question and the tradeoffs involved.
This is known as the long tail problem in ML, and it's a reality in almost every field. It's also why we don't officially have self driving cars, despite there being thousands of videos out there with cars driving autonomously for hours without any errors. But every now and then, there will be cases where the system doesn't work.
There are two interesting aspects here. One, we don't actually have quantitative data on how often this happens in the same field when human errors don't get caught. In a perfect world we'd have that, plus a long study for the "AI" systems, and we'd get to compare the two. Secondly, even if we'd have that data, people would still act out against "the machine" in the (ideally fewer) cases where it errors out, compared to a doctor. It's part human nature, part (manufactured) rage against the machines.
I also agree with your second paragraph. Case in point, when a waymo hit a cat, we got a shit ton of articles, riled up communities, and so on. Or every time that other car hits something we get plenty of press, even if some of the "accidents" are fender benders that likely wouldn't get reported otherwise.
The relevant information is the rate for each.
There are estimated hundreds of millions of medical transcription errors per year without AI. 42.4% of finalized medical notes still contained at least one error.
Prior to AI it would be about voice to text. Prior to that it would be some transcriber in India. Prior to that it would be the doctor themselves
Sure, it sucks if your self driving car gets in a crash or your AI scribe incorrectly transcribes something to your medical record. This is news now. What isn't news is humans getting into crashes or doctors making poor medical decisions as a result of low quality or missing notes.