I've never seen a doctor shun technology to keep themselves relevant (I've no doubt it will become a thing more in the future).
Per my interaction, the best doctors will do whatever it takes to improve their efficiency. Their biggest problem is the sheer volume of patients. Everyone wants to go to the best doc, and word spreads pretty fast. If you start doing good, very soon you are swarmed with patients 24/7. So any tool that can speed up their patient handling time is welcome. This is not a scheduling problem. People built a ton of scheduling tools and those tools have done next to nothing to move the efficiency needle.
What's needed is, what you said, a diagnostic tool with automated feedback from patient's activities and dramatic physiological changes. The best doctors that I know will take it up in a heart beat.
I'd argue that the answer to this is, "Sorry, but we're full up on appointments that day/week/etc". And if you start needing to book your normal clients too far out, you stop taking new patients. The fact that people want to see a doctor doesn't mean they get to see that doctor. The answer is not to take more patients but give each one less time, resulting in sub-par treatment.
And if you start needing to book your normal clients too far out, you stop taking new patients
What's a normal client ? Do you mean repeat clients ?
People sue doctors, too, but I'd put money on the proposition they'll be more willing to sue a company than the individual they met who seemed like he had their best interests at heart.
Most doctors don't work in hospitals, they work in family practices and most definitely are making the decisions about how their practices operate. Most of us don't go to hospitals to see our doctors, we go our doctors private office.
Specialists still seem to work from private offices, but my experience is that most doctors work for large medical groups where they do not make the technology decisions.
They have more data than most other networks, and more resources to invest in R&D.
Whether this is a good thing or not is open to interpretation. Doctors make mistakes, but people often catastrophize their test results.
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.
http://www.healthtestingcenters.com/lab-locations/georgia/bl...
https://www.cdph.ca.gov/programs/lfs/Documents/LFS-OrderTest...
in this particular area, one might argue that Georgia is more enlightened than California.
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.
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
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.
Even the concept of electronic medical records has been resisted, and is currently poorly implemented. The gov't had to literally bribe doctors to convert to electronic systems and most seemed to go out and get the least poorly built products on the market.
I'm not trying to paint them as evil. Heck, even NASA scientists were suspicious of computers taking their jobs. I see this in other fields all the time.
Seeing the potential and seeing the current state of affairs kind of makes me sad. I want to live in the world where a balance has been reached. Where my medical record is a salient form of AI that checks if I lost those 10 pounds I promised and loops in the doctor when my flu symptoms linger too long. I want it to eliminate the hassle for doctors, hospitals, insurance companies as well as patients, and I think in the process it can drive costs down and raise quality of life.