There are a lot of current doctor work which involves. "Any issues with the medication your on, ok, can I see your bloodwork, no red values, here is your prescription."
Which really should be the job of a nurse or physician's assistant. Doctors should be reserved for the cases that requires the ~10 years of training they receive.
Most people probably only need a yearly-visit to the physician's assistant or a nurse for bloodworks. There shouldn't be a need to see an actual doctor on a regular basis (unless you have some chronic ailment that nurses / physician assistants can't handle).
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The prescription is probably the only part of that routine that requires a doctor.
We know how to replace doctors with nurses. It works well, in many cases.
It's really a political problem.
People don't seem to have enough motivation to politically fight to replace doctors with nurses, and doctors have a lot of power and motivation to keep their jobs.
And what about powerful actors from inside the system ? Hospitals, Insurers, etc ? In general, everyone gets a share of revenue. So why bother reducing that ?
Entirely accurate. It's the AMA/doctor lobby (purposely constraining supply to keep wages high) that is preventing nurses and nurse practitioners from filling this role. My prescriptions and bloodwork are already in an EHR/EMR (EPIC) and shared with Apple Health, machine intelligence should be doing as much heavy lifting as possible.
This question might be out of place, but why should I trust ML algorithms for my health? To be a doctor you need at least a decade of education and training, as well as licensing and adherence to a code of ethics. To be a tech bro you just need to get hired. You don't even need a degree. You could come to work stoned and as long as your boss doesn't notice, you're fine and can continue to write the code that my health could rely on.
I'd expect the development of healthcare related machine intelligence/assistance technologies to be heavily regulated, in the same way medical devices are by the FDA.
50% of doctors graduate in the lower half of their class each year. Lots of low hanging fruit with ML if implemented properly (big if, I know).
Comparing the bottom 50% of people that graduate from medical school to "low hanging fruit" is hilariously snide.
Like, if there is a problem with their performance, it is a problem that they are graduating. And then look at the group that is admitted. It isn't a low bar.
My point is not meant to be inflammatory, nor derogatory. My understanding is that medicine is very hard as a domain (correct me if I'm wrong! i am not a medical practitioner). I am not proposing these people are stupid, nor that they are incompetent, but that humans have human failings and that is what leaning on technology is for. Medicine is hard enough without help. I am proposing more help, just as autopilot is to aircraft pilots. Commercial air travel is very safe, but still has humans making decisions.
The majority of diagnoses are extremely simple. It's a small portion that are difficult. We don't need a complicated computer system to help with the simple ones, we need more people that are allowed to indicate the care they know is needed.
Ay, there's the rub. Oftentimes, it is discerning the difficult in a multitude of simples, hearing the zebra hoofbeats when the sound is clearly a horse. Miss the exotic and a patient could die, no repeats. It haunts a physician for the rest of their days.
And 50% of nurses, nurse practitioners, and PAs graduate in the bottom half of their class too. Why do you think they are not the ones whose jobs are going to be automated away? If an AI can handle the easy cases, it won't be the doctors, who are able to deal with the complicated cases, who will lose their jobs.
How much of an average doctor's day is really appointments like this where they just check you lab values and ask you if you're doing okay on your medication and send you on your way? A large number of these cases are already handled by nurse practitioners and PAs. Doctors in my experience spend more time seeing the sicker patients with many chronic medical conditions where the more in depth knowledge of pathology and pharmacology that they spend those years of training acquiring inform the questions they ask, the tests the order, and the physical exam they preform.
I don't think the large majority of PAs and NPs really want to step into the same role as physicians. The number of PAs and NPs who were rejected from medical school and then chose to take either of those routes is probably very small compared to the number who chose to become a PA or NP because they wanted that role and not a doctor's.
Doctor time is most of expensive. It makes the most sense to automate away their mundane or lower value work first, vs NPs, RNs, or CNAs (who all do more hands on work compared to an MD, but also have lower costs per unit of time). It is silly to continue to have humans do low value work if it can be automated. Save that time for higher value work.
This is not about replacing people wholesale, but giving them better tools.
Time and effort? ML already finds lung cancer better than human radiologists, so it’s clear there are datasets that are of sufficient quality. We continue to improve datasets wherever possible.
In a word: no. Machines can find a spot on an image better than a radiologist when it is known that there might be one.
Unfortunately, that is of very little use to the clinician. The big hype is a consequence of a big misunderstanding of the practical constraints of healthcare.
Time and effort don't fix bad data and bad statisticians.
I'm sold. Now try to convince the people who are important to convince and have a good laugh. Reliable data collection is the biggest challenge for modern medicine. A challenge far greater than getting better statistical models.
Might be some sort of liability aspect to this, where the doctor has to certify in case something goes wrong. Do nurses/PAs have to carry malpractice insurance? Not super clear on this myself.