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I think the people who automatically had a negative view of AI didn't think it through, when ChatGPT came out in Nov 2022, the realization was that something li

I think the people who automatically had a negative view of AI didn't think it through, when ChatGPT came out in Nov 2022, the realization was that something like this tutor friendly AI would be on the horizon. Personally, I am looking forward to AI enabled healthcare, my sister has been dealing with health problems and she has to wait up to a month between appointments. At the very least AI can be used to speed up all the paperwork that doctors have to complete.

mjr00 3y ago
> At the very least AI can be used to speed up all the paperwork that doctors have to complete. How much do you know about the healthcare/medical system? Where specifically in the process would AI be used to speed up paperwork?
- Aaronstotle 3y ago
  I worked with my uncles law firm and know that the process for getting medical records is a huge pain. Back then I never understood why there couldn't be some better system for getting medical records between authorized parties. Growing up, my family friend who is a trauma surgeon always told me she hated all the paperwork she had to do.
  - mjr00 3y ago
    Okay. How, specifically, does AI help with any of that?
    - wdh505 3y ago
      1) Transcript of the patient and doctor conversation. 2) Creation of possible icd10 diagnosis and treatment codes from the transcript. With suggestions of which ones are most likely to be properly processed the first time per the insurance company of this patient. 3) Quick review of the transcripts of previous visits to determine if there are any overriding concerning trends for this patient. 4) suggested additional tests to reduce uncertainty in the diagnosis and prognosis according to a pre programmed cost to benefit ratio. I could go on. The local personal health information (phi) approved ai could greatly reduce time spent on paperwork and double work like resubmitting procedure codes to billing.
      - ska 3y ago
        Eh, on the surface this seems useful but I'm not sure it makes a dent. Transcript might be useful occasionally, but they aren't going to be referred to often - things still have to be distilled in the doctors notes, including things they don't say during the visit. They already have dictation systems for this, but none of the NLP systems are good enough to do it without checking, so time is about same. Coding isn't done by the doctor anyway. Replacing a fairly low paid employee with a bot might net out but it's not obvious. Then on the diagnostic stuff, we've been working on this for decades, I think there is real promise there but it's not a quick fix either for getting the system performance good enough to deploy more widely than e.g. CAD systems, and for getting systemic uptake. They aren't nearly good enough yet, we'll see what the next decade of improvements gets us.
        wdh505 3y ago
        The key here is not "a decade of improvements" but rather "can current tech be regulatory approved". The transcript provides context which is phi and invaluable. Doctors care a lot about billing codes
        ska 3y ago
        Current tech [for reasonable versions of current] can be approved although not all configurations (basically you have to fix the model for a release cycle). It isn't good enough yet for most uses in the space you describe. Improving that state of affairs is more a data limitation than a technology one, probably, but medicine is also very conservative and will take it slowly to prove out. Doctors care about getting paid, they mostly don't care about coding per se, and they don't do it themselves. It's not at all clear that a NLP AI would be more cost effective at it than the people who do it now. Where you will probably see it is auto-rejects, from the insurance side, forcing more iterations. None of this stuff is off the radar of (at least some of ) the people who build medtech systems, they've been incorporating aspects for a long time. The idea that there is a sudden radical change to be made with todays tech is naive I think, lacking context of both the history of AI systems in medicine and the current techs' limitations...
adastra22 3y ago
I’m pretty sure paperwork isn’t the reason your sister is waiting months between appointments.
- Aaronstotle 3y ago
  Paper work no, but last week she was being told two different things from two different doctors. None of them talked to each other/between each other and she had to physically drive from one office to another to get her own medical records.
prophesi 3y ago
The industry tried using AI to help with that last year, and it was quickly shut down[0] after UnitedHealth / Humana were sued for using blatantly flawed AI projections. It could definitely be used to improve aspects of healthcare, but the profit motive will be at odds with this goal in most cases. [0] https://arstechnica.com/science/2024/02/ai-cannot-be-used-to-deny-health-care-coverage-feds-clarify-to-insurers/ https://arstechnica.com/science/2024/02/ai-cannot-be-used-to...
ska 3y ago
Versions of this have been in use since the 90s, but haven't really made a dent in the systemic issues that cause these delays. What do you think has changed to make that different now?

mjr00 3y ago

> At the very least AI can be used to speed up all the paperwork that doctors have to complete. How much do you know about the healthcare/medical system? Where specifically in the process would AI be used to speed up paperwork?

Aaronstotle 3y ago
I worked with my uncles law firm and know that the process for getting medical records is a huge pain. Back then I never understood why there couldn't be some better system for getting medical records between authorized parties. Growing up, my family friend who is a trauma surgeon always told me she hated all the paperwork she had to do.
- mjr00 3y ago
  Okay. How, specifically, does AI help with any of that?
  - wdh505 3y ago
    1) Transcript of the patient and doctor conversation. 2) Creation of possible icd10 diagnosis and treatment codes from the transcript. With suggestions of which ones are most likely to be properly processed the first time per the insurance company of this patient. 3) Quick review of the transcripts of previous visits to determine if there are any overriding concerning trends for this patient. 4) suggested additional tests to reduce uncertainty in the diagnosis and prognosis according to a pre programmed cost to benefit ratio. I could go on. The local personal health information (phi) approved ai could greatly reduce time spent on paperwork and double work like resubmitting procedure codes to billing.
    - ska 3y ago
      Eh, on the surface this seems useful but I'm not sure it makes a dent. Transcript might be useful occasionally, but they aren't going to be referred to often - things still have to be distilled in the doctors notes, including things they don't say during the visit. They already have dictation systems for this, but none of the NLP systems are good enough to do it without checking, so time is about same. Coding isn't done by the doctor anyway. Replacing a fairly low paid employee with a bot might net out but it's not obvious. Then on the diagnostic stuff, we've been working on this for decades, I think there is real promise there but it's not a quick fix either for getting the system performance good enough to deploy more widely than e.g. CAD systems, and for getting systemic uptake. They aren't nearly good enough yet, we'll see what the next decade of improvements gets us.
      - wdh505 3y ago
        The key here is not "a decade of improvements" but rather "can current tech be regulatory approved". The transcript provides context which is phi and invaluable. Doctors care a lot about billing codes
        ska 3y ago
        Current tech [for reasonable versions of current] can be approved although not all configurations (basically you have to fix the model for a release cycle). It isn't good enough yet for most uses in the space you describe. Improving that state of affairs is more a data limitation than a technology one, probably, but medicine is also very conservative and will take it slowly to prove out. Doctors care about getting paid, they mostly don't care about coding per se, and they don't do it themselves. It's not at all clear that a NLP AI would be more cost effective at it than the people who do it now. Where you will probably see it is auto-rejects, from the insurance side, forcing more iterations. None of this stuff is off the radar of (at least some of ) the people who build medtech systems, they've been incorporating aspects for a long time. The idea that there is a sudden radical change to be made with todays tech is naive I think, lacking context of both the history of AI systems in medicine and the current techs' limitations...

adastra22 3y ago

I’m pretty sure paperwork isn’t the reason your sister is waiting months between appointments.

Aaronstotle 3y ago
Paper work no, but last week she was being told two different things from two different doctors. None of them talked to each other/between each other and she had to physically drive from one office to another to get her own medical records.

prophesi 3y ago

The industry tried using AI to help with that last year, and it was quickly shut down[0] after UnitedHealth / Humana were sued for using blatantly flawed AI projections. It could definitely be used to improve aspects of healthcare, but the profit motive will be at odds with this goal in most cases. [0] https://arstechnica.com/science/2024/02/ai-cannot-be-used-to-deny-health-care-coverage-feds-clarify-to-insurers/ https://arstechnica.com/science/2024/02/ai-cannot-be-used-to...

ska 3y ago

Versions of this have been in use since the 90s, but haven't really made a dent in the systemic issues that cause these delays. What do you think has changed to make that different now?