Doctors protect themselves from technology changes by forcing themselves to be included in any technology change. Get blood tests? You can't get the results until a doctor looks at it. MRI? Same. ML will provide another batch of tests for them to order, and if they work better, that's great for the patient, but you'll still need to make an appointment with the doctor for ordering test, and another for diagnosis.
Whether this is a good thing or not is open to interpretation. Doctors make mistakes, but people often catastrophize their test results.
Unfortunately, most of our tests aren't all the good and in and of themselves the results are pretty meaningless.
Back in medical school we were taught that 80% of the diagnosis comes from the history, 10% from the physical examination and 10% from the investigations. Or something like that, it's the idea, not the numbers that matter.
As a young computer nerd, this didn't sit well with me, but the more I practice medicine the more I understand it.
My teachers didn't realise at the time, but I think they were actually talking about Bayesian probability.
I think we are talking about this more and more in medicine, but unfortunately not all specialities have embraced it.
There are lots of likelihood ratios published and good statistics available to help with diagnosis, but we don't use them effectively. There are some online tools and apps available to help navigate the literature, but I'm not really sure why we don't use them more.
i think the law in California requires that a physician or health care practitioner give the order to the lab. i don't think the average patient in California is allowed to order their own medical lab tests.
The primary reason why there wasn't much automation in the past was the combination of doctors being conservative (which is a good thing) and lack of competition among established medical companies (the ones conservative doctors depend on). You can see how the two couple stifling innovation not through any conspiracy but just preferences.
Both of those aspects are being relaxed today. Doctors are become tech-oriented and more diagnostic companies (run by first-rate medical/engineering teams) are starting up that may upend more established medical companies. We will see a rapid change in the diagnostics landscape in the next decade. This may also add some risk to the diagnostic field, but the benefits far outweigh the risks.
I saw an asthmatic woman in A+E today, all her blood tests were in the 'normal' range, does that mean she's well?
No, she was very unwell. However the test results would either be normal in someone regardless of the severity of their asthma, or would be expected to be 'abnormal' in someone with mild asthma, and 'normal' in someone with severe asthma. The ability to interpret those test results, and take a history and examine the patient is important.
Similarly, we used the latest evidence-based guidelines to assess the patient's asthma severity, and based on several objective criteria (breathing rate, oxygenation of blood, peak flow, etc) the guidelines determined she had moderate-severe asthma
However we called the ICU doctors to see her. The ICU consultant, with many decades of experience managing acutely unwell asthmatics, simply looked at the patient for two minutes, observing how her chest moved during breathing, and the sounds and respiratory effort she was making, and decided to take her to ICU. This was a good decision as she ended up deteriorating and requiring very aggressive treatment. Whilst guidelines can make a suggestion based on the interpretation of some objective data points, the ability to assess a patient as a whole, based on history and examination, is still an important skill, and one which it is hard to automate
The test results list the 95% confidence interval range for the population the sample they used to calibrate the test is theoretically representative of. That's not the same thing as normal.
Tests are usually done for a clinical purpose, not just to find out what your result is. What do the numbers mean to you?
Many straightforward tests people can do and interpret themselves, like people with diabetes on insulin (measuring BSL). They're not all so straightforward.
Whether this is a good thing or not is open to interpretation. Doctors make mistakes, but people often catastrophize their test results.