unsrsly

You're making some very interesting and valid points. You've correctly identified that when receiving bundled services you lose the ability to negotiate or comparison shop on the basis of price. This is unfairly combined with a legal presumption that when the healthcare system generates a bill, the bill is valid until proven otherwise. Now, although we probably need more physicians, I don't think the limited supply of physicians is the primary reason for this situation - it's more due to increasing market concentration of health insurers on one side and hospital systems on the other, leading to regional monopolies that don't compete on price. In fact, with the decline of private practices and the rise of hospital systems, physicians receive less than 10% of all healthcare revenue. I can see that you'd like to unbundle your healthcare and regain control over prices, and I think that's a very reasonable thing to want.

There's a lot to unpack here! In the USA, the ABR regulates human radiologists via board certification. Medical technology is traditionally regulated by the 510K, PMA, and de novo pathways at the FDA. Of course, these products still have to demonstrate value in order for major stakeholders (hospitals, radiology practices) to purchase them. And using these products does not absolve the ordering doctor, the radiologist, or the hospital of legal liability for misdiagnosis. In fact, IANAL and this is a somewhat novel area of the law, but any AI product that functions as a drop-in replacement for a radiologist might be held liable for misdiagnosis that leads to harm. These liabilities could become quite large for a product deployed at scale (a single misdiagnosis causing death can lead to a settlement in excess of 10 million dollars). In summary, there's quite a bit more to the issue than simple "gatekeeping." It might be appealing to blame radiologists for these issues, but there's a much larger system at work that's designed to ensure quality and safety for patients. This is not AdTech - lives are at stake and people can get hurt. Now, this definitely comes with a cost to innovation, but it's going to take more than just a few MD's to reinvent the economics and law of computers practicing medicine on people.

> Still, I'm thinking that as it improves, it's going to show that doctors are not that good at their job on average, and that's going to be fun to watch.

Medical AI is trained on labels generated by doctors. Can you explain how it will exceed the performance of doctors on average? Are you assuming that the labels will be generated by the "top x%" of doctors? If so, how will you identify those individuals? Or is there some other mechanism you're expecting to improve the performance?

Interesting, how would the standards of the Board of Computational Radiology be set? Is the implication that the current standards are too high?

There is zero chance the software allowed the radiologists to work 10x faster... what?

Interesting, can you give an example of a radiologist hindering progress? You make an interesting point about radiologists setting practice standards - what alternative do you propose? You may also want to consider that radiologists don't determine practice standards in a vacuum - they have to serve the needs and expectations of their clinical colleagues.

That must have been scary, but I'm glad she had a good outcome.

I respect your experience, and I'll concede that fMRI for pre-surgical planning in neurooncology is used at only some centers. If you worked mainly in neurooncology you may have missed some of the uses of fMRI for epilepsy surgery. Thanks for the discussion.

Awake cortical mapping has much better resolution than fMRI, and it avoids image registration issues, but it requires a great deal of planning and patient motivation. If it turns out that the language center is on the opposite side from the area of the surgery, then awake mapping might not even be necessary. This is why fMRI is often used as a planning step before awake cortical mapping during the actual surgery.