That's rarely (if ever) a 1:1 ratio. That attending physician is almost certainly juggling multiple patients. Same with the rest of the care team. There's a reason why the first thing one does when approaching a patient bed is to look at the chart.
> Some things can be documented in the patient chart but there are always gaps.
Then those gaps need closed, stat. Once those gaps are closed...
> Clinical decision support systems for partially automating diagnosis could potentially be helpful in some limited circumstances but the ones built so far mostly don't work very well.
...then this will improve considerably. Garbage in, garbage out.
And in most routine cases the diagnosis is the easy part. The hard stuff is actually working with patients and doing the hands-on procedures, which won't be significantly automated in our lifetimes.
Pattern recognition algorithms do have some promise for computer assisted interpretation of things like medical images and ECG waveforms where the input data is already in digital form. We can't rely exclusively on algorithms for patient care, but if the physician reaches a conclusion different from the human physician, then it's probably worth taking a deeper look and getting a second opinion.
...which is why we shouldn't be wasting such valuable resources (people with an aptitude for medicine) on doing such an easy, routine task all day long, no? It'd be like if chefs spent most of their time hand-grinding spices rather than cooking.
> A skilled, experienced clinician can intuit a great deal from subtle signs like skin color, breathe sounds, tone of voice, small movements, etc. / Pattern recognition algorithms do have some promise for computer assisted interpretation of things like medical images and ECG waveforms where the input data is already in digital form.
You're seemingly contradicting yourself here: you're saying that the places where ML shows the most promise, are exactly with the tasks that would best replace the things doctors are doing. The only reason that ML can't do those things, is that people aren't putting data like "a video exam of the patient by a nurse" into the chart where the diagnostic algorithm can see it / be trained on it.
This is incorrect. Doctors are assigned to patients, and if there is a complication any time or day or night the doctor is contacted to decide what to do. The entire point is so that there is one person who is familiar with the patient, who is also responsible if anything goes wrong. I don't know how malpractice would work with an AI, but given the number of malpractice cases yearly in the US it'd either be sued out of viability or have to be provided with legal immunity(possibly the worst scenario IMO)
Yes, of course, hospital care would be better in many ways if we did have somebody who statefully understood particular patients’ needs.
But what I’m saying is, the GPs in hospitals could be replaced with stateless diagnostic AI without making hospital care any worse than it is now. And hospital care is a large part of the medical system, so only replacing diagnostics there (while leaving primary-care GPs alone) would still be a major optimization, freeing many doctors to provide better care, go into specialties, etc.