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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 -
by 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 agoThe 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 agoCurrent 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...