4th year medical student. AI is not ready to be making any diagnostic or therapeutic decisions. What I do think we're just about ready for is simply making notes faster to write. Discharge summaries especially, could be the first real step AI takes into healthcare. For those unaware, a discharge summary is a chronological description of all the major events in a patient's hospitalization that explain why they presented, how they were diagnosed, any complications that arose, and how they were treated. They are just summaries of all of the previous daily notes that were written by the patient's doctors. An AI could feasibly only pull data from these notes, rephrasing for clarity and succinctness, and save doctors 10-20 minutes of writing on every discharge they do.
Also in general - summaries are just a strong suit of LLMs right now, and even if the technology doesn’t advance further (which I’m quite skeptical of) it is still an extremely useful tool which will drastically impact so much.
This is how most of the tech industry thinks -- looking at the existing process and trying to see which parts can be automated -- but I'd argue that it's actually not that great of a framework for finding good uses for technology. It's an artifact of a VC-funded industry, which sees technology primarily as a way to save costs on labor.
In this particular case, I do think LLMs would be great at lowering labor costs associated with writing summaries, but you'd end up with a lot of cluttered, mediocre summaries clogging up your notes, just like all the other bloatware that most of our jobs now force us to deal with.
4th year medical student. AI is not ready to be making any diagnostic or therapeutic decisions. What I do think we're just about ready for is simply making notes faster to write. Discharge summaries especially, could be the first real step AI takes into healthcare. For those unaware, a discharge summary is a chronological description of all the major events in a patient's hospitalization that explain why they presented, how they were diagnosed, any complications that arose, and how they were treated. They are just summaries of all of the previous daily notes that were written by the patient's doctors. An AI could feasibly only pull data from these notes, rephrasing for clarity and succinctness, and save doctors 10-20 minutes of writing on every discharge they do.
Also in general - summaries are just a strong suit of LLMs right now, and even if the technology doesn’t advance further (which I’m quite skeptical of) it is still an extremely useful tool which will drastically impact so much.
This is how most of the tech industry thinks -- looking at the existing process and trying to see which parts can be automated -- but I'd argue that it's actually not that great of a framework for finding good uses for technology. It's an artifact of a VC-funded industry, which sees technology primarily as a way to save costs on labor.
In this particular case, I do think LLMs would be great at lowering labor costs associated with writing summaries, but you'd end up with a lot of cluttered, mediocre summaries clogging up your notes, just like all the other bloatware that most of our jobs now force us to deal with.