Recently, my dad was sick with a pretty bad cough. Like, so bad that he couldn't speak without coughing. He fainted twice from minute long coughing fits, one of those times hitting his head his head on the stove on the way down, leaving a deep cut and blood everywhere.

He went to at least three different doctors. He got a scan of his chest. Everything looked clear, and all of the doctors were stumped. Things were pretty bad.

I mentioned this to a UCSF resident friend, and her immediate response was "Oh, is he on <some blood pressure medication I forget the name of>?" I was like, uh, let me see. Called my mom, she checked, and, lo and behold, he was on it. So his doctors took him off it and within a week he was better.

This coughing wasn't some obscure side effect of the medication she knew through sheer brilliance: it's a side effect that's been widely known since the 1970's. Hell, it was on the drug's Wikipedia page.

So there's a couple morals you could take from this. One would be, wow, doctors are smart to be able to diagnose an issue based on a single symptom and some reasonable assumptions about a patient's background! The other is that the median doctor is pretty worthless; spending tens of thousands of dollars gives you no guarantee you'll see someone competent; and that a medical system that relies on you grabbing drinks with a UCSF resident to get good results is fundamentally broken.

Machine learning and expert systems don't have to be as awesome as the best doctors to be valuable. They don't need to be better than competent doctors, even. They just need to provide a bare level of competence to provide a huge amount of value.

ALWAYS READ EVERYTHING YOU CAN ABOUT DRUGS YOU ARE PRESCRIBED!

Sorry for all caps, but it is super important. Not that your dad is in the wrong, lots of people have justified (to a degree) trust in their doctors. However doctors are people and just by that alone aren't perfect.

A few years ago my doctor prescribed me an antibiotic for an ongoing illness I had. I read the entire pamphlet for it and did some reading online about it. All before taking it. Turns out it can cause seizures if it interacts with polypropylene glycol, one of the main ingredients in e-cig juice, which I use daily. I had told my doctor I use an e-cig.

Really I cannot stress how important it is to be knowledgeable about the drugs you are taking.

I'm not trying to undermine your point entirely, but there is a flip side.

I can't tell you how many times I have seen a patient start a medication, then come back to the office within 48 hours because they coincidentally have every side effect that is listed in the pharmacy's information sheet or that they looked up online. The vast majority of these side effects are benign, present with next to no pertinent physical exam findings, and can't be definitively tied to the new med (like upset stomach, fatigue, headache, etc.).

Then they will start listing that medication as one of their "allergies", and if the nurse/doctor documenting doesn't dutifully probe what type of "allergic reaction" they had, they may end up not being prescribed that med in the future when it really is the drug of choice. A little nausea is a small price to pay if it kills a potentially life-threatening infection.

Also, I'm skeptical about the seizure risk. The thing about side effects is that they are supposed to be stratified according to risk. Doctors are typically aware of these risks, but patients aren't. So if your drug is listed as causing "headache, nausea, and seizures", there may have only been one patient out of millions who had a seizure while 50% experienced headache, yet the handout probably won't tell you that.

But even if it is a notable risk, I would be surprised if the propylene glycol you inhale from an e-cig could accumulate to a high enough level in the bloodstream to cause drug interactions, although I admit adequate research on the subject is lacking.

My advice would be trust your doctor first. If you don't trust your doctor, start seeing a doctor that you do trust. Then if you have a significant adverse reaction to a medication, talk to your doctor about it. Quite often they know something that you are not going to find by spending a few minutes on the internet.

As a side note, a good history includes asking about many habits. A lot of healthcare providers are guilty of simply asking "Do you smoke, drink, or use drugs?", but ideally the smoking aspect should be phrased as "Do you use any tobacco or nicotine products?". Patients usually won't read your mind and volunteer that kind of information. They will tend to give yes/no answers, so direct and specific questions are important.

Odd, here in Norway that's exactly the kind of information I expect to see on a leaflet inside the packet, not only on prescription drugs but also over the counter pain killers like paracetamol. Roughly translated from the Norwegian it says:

Rare side effects (more than one in ten thousand but fewer than one in one thousand patients) include: over sensitivity, allergic skin reaction/rash, reduced white blood count, anaemia, disturbed liver function. Very rare side effects include serious skin reactions. Liver function can be affected by paracetamol and alcohol abuse.

That seems like a major problem. Is there any reason that more detailed information can't be included? Mathematical literacy may be a problem, but that doesn't mean that there aren't millions upon millions of mathematically and scientifically literate consumers who could use this information effectively.

I'm not trying to justify any of this, but that's how it is.

Not sure if it will be helpful in the future, but I can tell you that descriptors used with side effects follow a standard convention:

    very common: > 10% 
    common: 1%-10%
    uncommon: 0.1% - 1% 
    rare: 0.01% - 0.1% 
    very rare: < 0.01%

Once you view your GP as a mechanic, you can make much better decisions. Sure, their "cars" are more complex, but the role they play is similar. If you want your body to function well, you are responsible for it, not the doctors. They just help you out.

The system is built on rent seeking behavior. If I don't treat it immediately then the patient will come back again and I can charge him/her a subscription.

Health care in America is very inefficient. Mostly because of insurance lobbying and govt that can't make a firm long term decision.

I would love to see most common problems be self diagniosable with kits and AI.

ACE-inhibitors are well-known to cause a cough but not like the one you're describing.

If I was to guess I'd say he had a respiratory tract infection that magically disappeared (as they do) not long after ceasing the medication. This is a common type of scenario where lay people get confused about correlation and causation, and is one of the reasons you need doctors to help you.

Even if it was the medication, like I said, this sounds like a somewhat unusual case.

You'll probably spend the rest of your life thinking the doctors didn't know what they were talking about, but in my experience with doctors (I have a lot of that since I'm a doctor myself), even the "median" ones are far better at diagnosing things than lay people.

For any given complaint, most will just tell you that your test results are in the normal range (don't get me started on this "normal range") and tell you there's nothing they can do.

I live in the bay area and have had a few GPs over the years, some from well known institutions.

Doctor's seem to put in the minimal amount of effort to get you out of their office in the allotted 20 minutes so that they can move on to the next patient.

I have multiple anecdotes similar to OP's - times where if it weren't for my insisting or my own inkling to visit a specialist I just would never have been helped.

Are there goood GP's? I'm sure there are - but to casually dismiss OP's statement is a bit ironic - since casually dismissing is part of the biggest problems as far as my own experience with doctors.

I responded to OP's statement. Dismissing is quite different.

The doctor, after number 3 in my list and less than 15 minutes into the appointment said "Are you done?" After item 4 a couple minutes later he said "Is that it?" In a condescending manner.

Needless to say, I was pissed.

But, the thing is, it's not the doctors fault. He's working in a system that values throughput over all else...and this is Kaiser, a vertically integrated provider where you would think that would be less of an issue. So he was late to my appointment and saw my long appointment as a way to get back on schedule to ensure he saw the 40 patients he had to see that day.

The whole system is broken.

This is not meant to sounds harsh, all I am saying that from any business you can't buy a product they aren't in the business of selling.

Comparing this business model to McDonalds is a bit ridiculous. Maybe compare to a lawyer booking double time, or thousands of other professionals. But don't make the unnecessary jump to a fast food chain.

Are you in US? Is double consult something insurance/government pays for twice for you? Or are you are talking about a different billing code? Or self-pay?

Doctors still often go over time.

So given that, a patient is likely getting the most expensive product a given doctor will deliver already. To get a better product simple options are specialists (much higher reimbursements, selection bias for more complex cases) and specialists at major teaching hospitals (even more of the above).

There are effective ways for a patient to hack the system by doing lots of work themselves (e.g. by maintaining his own clinical summary) but they are beyond what most patients will do.

It's a lot like YC office hours actually. Though doctors have less time than YC partners. And doctors get paid per appointment.

In general, it's not useful to think of doctors as engineers. The line doctors work is much more tech support - lots of similar highly repeatable cases, with a well understood script. The ones that are more like engineers are doing research in research hospitals and writing that script. They still see some patients as part of their work, but appointment reimbursements are not a profit center for them, but part of their research.

Then again, my previous GP said he had 7 minutes per consultation.

(FWIW, I’m in the Netherlands).

We aren't comparing doctors to "lay people" - we're comparing them to machine learning algorithms. I'd prefer the machine to many of the arrogant, but mediocre, doctors I've seen in my life.

Edit: It seems "UCSF resident friend" is American for doctor. I suppose my statement was actually out of context then.

Separate from that, I've had similar experiences. The median doctor I've interacted with isn't able to put in effort to really understand an individual case, and it's very easy to get overlooked or ignored. I've run into a few exceptions but that is the general rule. Source: wife had pregnancy with complications, young children.

I've had the dubious honor of spending quality time in a few hospitals with sick relatives in the last year. The nurses rock, and PAs and NPs seem to do what residents used to do.

The residents in particular seem to be clueless. With electronic records, they can't look at the chart as easily and aren't situationally aware.

It's a common fallacy to want an older, experienced physician vs. a resident or fellow. There are exceptions like specialized surgical procedures. Generally speaking though, when physicians leave the academic environment they rarely get better. Residents and fellows (and physicians who stay in academia) spend a huge amount of time on education - it's built into every day they're at work. Things like case conferences, morning reports, and Morbidity and Mortality reviews.

When you enter private practice it is completely up to you to stay educated and current. Sure, you may attend SGIM once a year and read monthly journals, but that is nothing compared to the structured learning environment they left behind.

I will take a good resident at a county hospital over a private hospitalist any day. Even at exceptional Tier one hospitals the level of dumb shot that happens with lazy private physicians can be jaw dropping.

The private hospitalist is going to order some labs and consults, round on you once a day (maybe) and that's about it.

A good resident will discuss your case at length with their interns, co-residents, fellows, and attendings.

A this point, in a lot of schools, PAs and MDs get about the same amount of in-class training, for example (especially when you consider that PA prereqs are often stricter than MD prereqs in terms of prior coursework and experience). A PA with 2 years of experience is at about the same experience as an MD just out of school. The discrepancies with specialists (e.g., optometrists, dentists, psychologists, and so forth) is even greater.

I don't think MDs are incompetent, but I think our healthcare model is basically wrong, in that people just aren't able to juggle everything in their heads, regardless of how smart they are, and someone focused on their problem, with access to the internet, just might be able to get more traction than the person trying to remember 1 out of 10000 things in their head. I think this is also why there's been a push toward specialists: it's just easier that way, even if the problem isn't that specialized, because the specialists only have to remember 1 out of 20 things.

The basic healthcare model, with MDs at the top, followed immediately by PAs and nurses, needs to change, to be more decentralized. There's a role for those training backgrounds, to be sure, but many of the same tasks could be accomplished in different ways, and many things are maybe done more efficiently and less expensively through different routes (by relying more on pharmacists, for example, or expanding training and practice for optometrists, psychologists, and so forth).

Maybe if a pharmacist had been consulted, for example--maybe if there was less of an expectation that you start with an MD, or rely on an MD to provide all the answers, or expect them to know everything--the side effect of that med would have been confirmed earlier.

This is the one silver lining that I might hope for in a renewed healthcare debate, which is a restructuring of care systems to increase competition and decrease costs. So far everything has focused on how to pay. That's not to say I agree with moving away from a single-payer system, or that the current government will lead anywhere productive, or that I've seen anything innovative from them in that area, but it's something that hasn't been done yet.

This seems fairly disrespectful. I suppose you mean that the median doctor isn't perfect, but do you have any idea how many hours residents put in? You might think carefully before calling the median one worthless, and ask whether they're really, truly wasting their lives in the service of others.

Less emotionally, I find it hard to believe that half of doctors proved essentially no benefit.

> it's a side effect that's been widely known since the 1970's

Guess how many side effects have been widely known since the 1970's?

For clarity: I am 100% in favor of thinking critically about a doctor's advice, having received contradictory diagnoses before.

Or, if you want to search the transcript for it, "So, given a choice between two doctors, let’s say — one fresh out of medical school and the other with fifteen years’ experience, which one do you go for?"

It's a good listen or read.

Tl;dl: Anupam Jena [2], "And we can basically see what happens if a patient happens to be treated by a doctor who is 20 years out of residency versus 5 years out of residency. And what we find is that if you happen to be treated by a doctor who is 10 years or 15 years out of residency, your mortality within thirty days of being hospitalized is higher." [Note: surgeons were one of the specializations that did not follow this correlation]

Side note: the medical profession is really terrible at keeping statistics on outcomes, outside of actual trials.

[1] http://freakonomics.com/podcast/bad-medicine-part-3-death-di...

[2] https://www.ncbi.nlm.nih.gov/pubmed/?term=Jena+AB%5BAuthor%5...

Does this make it fine not to expect a doctor to inspect the list of known side effects for drugs his patients are taking?

I've heard this very story a few times already, perhaps the sources of data widely accepted by doctors are not up to par with what non-doctors consider as accurate, in some cases anyway.

Absolutely the accuracy of doctors should be improved, but the bar is not "are you as good as a UCSF resident?" (one of the best programs nationally) but "are you better than nothing?"

It just seems crazy to me to suggest that the median doctor, i.e. at least half, is worthless.

I have similar crappy experiences like most people here, and tended to hate all medical personnel uniformly. Then I started dating a young doctor - still can't wrap my head around how overworked over-stressed and underpaid piece of shit work that is.

Bear in mind that we're talking about biggest university hospital in Switzerland. Working ridiculous amount of hours (normal shift can be 10-13 hours, overtime unpaid), night shifts that will just mess you up mentally, crazy and dangerous patients, drug addicts, very real danger of contracting stuff like HIV or hepatititis C by single tiny mistake, or actually killing somebody by overlooking some tiny fact about N-th patient that night. You can end your career for life and end up in jail and/or with lifelong debt by one mistake. ONE. Even after directly saving life of 500 other people.

Compared to my comfy corporate job, where I earn much more, did get mistake or two in production over last 5 years (nothing critical like making loss, but still), well... We should be thankful that anybody clever is actually still doing that job. Most of them could earn more and have actually a life someplace else. Blame how system is setup much more than individuals forced to exist in it.

This is why, if I were an MD, I would be latching on to ML as quickly as I possibly could. There is a TON of money to be made here, sadly, I do not have the domain expertise to make it, though I am picking it up pretty quickly.

I'll bet the farm it was lisinopril, or another ACE inhibitor. The ACEI cough is notorious enough that any 1st year medical student probably should have been able to piece this together.

The problem is not that those doctors were ignorant. It's more likely that they did not ask the right questions to get a proper history. You should ask every patient to list their medical problems and medications unless it is a routine follow-up when nothing has changed.

Something else that can happen is patient ignorance (and I am not insinuating your dad was guilty of this, or making a value judgment on people who are).

Often times you can't get a proper past medical history or medication list unless the patient brings all of their prescription bottles to the office. E.g.:

>"What medications are you on?"

>"Well, I'm on a sugar pill, a water pill, a cholesterol pill, a stomach pill, and some allergy medicines."

>"Ok, do you know the name of that sugar pill?"

>"It's a little white pill. I think it starts with an 'F'. No wait, I'm thinking of my water pill."

or

>"Do you have any medical problems?"

>"No."

>[glances at meds list] "Ok, so why do you take metformin, hydrochlorothiazide, atorvastatin, omeprazole, cetirizine..."

While I think you might be overreacting a bit here, I have a similar story. I had an irritated, gunky eye for the better part of a year. Was bounced around multiple doctors, including one specialist, and had all sorts of really annoying treatments I was supposed to do. Finally got bounced to a specialist at a major teaching hospital. Took him five minutes to correctly diagnose me, and the major part of the fix involved instantly stopping all of the things recommended by the other doctors. (The rest of the fix was simply to make sure my eye was protected while sleeping.)

So yeah, I think there is a lot of value that might be added by an expert system that is familiar with the slightly more exotic things that can go wrong with your health.

Your dad's case is like complaining about constant nosebleeds while taking Aspirin every day. It's a bit obvious, to be honest.

For example, I am a radiologist. Probably 90% of my cases are mundane and are either normal or have 'easy' pathology that I can readily detect and quickly report. Another 9% is a mixed bag of things that take a lot more time--something I need to reference or think a bit more about or possibly show a colleague. And then there's the 1% that is truly a 'make' or 'break' case. My sub-specialty training and experience can really shine in these situations and I can easily dispense a diagnosis or make a 'tough call' where another might equivocate or defer to more imaging or a follow-up. I like to think I'm not being paid for that 90%... I'm being paid for the other 9+1% That's where I truly add value in the system. But how would I measure my 'success' rate when even the best eventually make mistakes given a long enough time and there is often not a gold standard for diagnosis or even long term follow-up/resolution to many of the tough cases I've seen.

Studies have been done where experts review a sampling of cases and that's essentially what we do now for quality control--we randomly review a few prior exams for a case we are reading and then submit feedback based on our opinion on the same case. In these studies, trained radiologists do very well and make clinically significant mistakes only rarely.

But here's the problem. Let's say we use machine learning to interpret a scan, something like a CT of the chest to look for a pulmonary embolus. On that scan, the machine may see an incidental pulmonary nodule. Well that's fine, we have good data on how to follow-up on those and what to recommend. Well, what about an anterior mediastinal lesion? Now it's not as clear. The differential is wide and dependent on age, sex, symptoms, history, etc. Let's say we build that logic tree, let the machine learn from 1000 anterior mediastinal mass cases with tissue diagnosis. Well guess what, we do those studies all the time and it turns out that NOTHING is 100% sensitive AND 100% specific. You have to sacrifice one for the other... it's a balance. So, you would need to build ROC curves for every possible finding on every scan and decide that 1% of the time you will miss a cancer to save having to biopsy an extra 20 people... or maybe you want to miss cancer only 0.1% of the time, but that means you'll have to biopsy an extra 200 people and one will have to be hospitalized from complications. You think they will be happy knowing you made that decision? Guess what, we are already doing that with Mammography. The screening guidelines that the different societies and agencies argue about are this very rationale... how many women should be allowed to die to prevent those extra biopsies, false positive workups and all the things that come with that. I welcome machine learning into medicine. Guess what, it's destined to be mired in the same ethical dilemmas we face everyday.

I have a feeling I'll make it to retirement.

For example, let's say you could--you can't--but let's say you could without a shadow of a doubt predict that the pulmonary nodule in your lung is not a cancer with 98% certainty. Well if you are 40, that's not that good actually.... that means 2 out of 100 people in a very productive time of their lives may have a cancer go completely ignored! So should I tell every patient in my report, "There is a 2% chance that this is malignant, but I won't recommend biopsy because there are chances of complications from that and we can save a lot of money by letting a few slip through the cracks--it will cost the healthcare system too much. Thanks for your understanding."

Remember, statistics predict population outcomes... not individual outcomes. I can tell someone that something very rare might happen.. but guess what, when it happens... the idea that it was a rare possibility doesn't assuage any negative feelings about it.

There is no right answer. Some people are illiterate! Even educated people don't understand statistics... how am I going to quantify that kind of risk/benefit analysis in a way that ensures a patient truly understands the implications. What if that risk were 1%, or what if the patient was 70 years old? Should either of those affect my recommendation? Who am I to decide who should be recommended one thing vs another... it's a value judgement! But if I leave it solely to the patient, a lot of times they will ask me, "What would you do?" Probably the most common thing asked after a long discussion like that. The answer is, "I don't know."

Bottom line: We can do 'strong' recommendations for things that are well studied like breast cancer and pulmonary nodules, but we don't have data to support recommendations in many other areas of everyday practice. A machine learning system would need data that just isn't available yet to make recommendations.

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.

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.

We're already seeing a significant rise in the role of nurse practitioners at the front line of medicine. Today, they gather the data and hand it to an MD, so handing it off to an ML system would be straightforward.

No, I am quite confident in that ML will really take off when data fed to those systems will be automatically gathered.

https://www.statisticsdonewrong.com/

If your comment was a book, I'd lovingly put it on the shelf next to Reinhart's masterpiece ("revised and expanded ... with three times as many statistical errors and examples!"). Unlike Shakespeare, it appears nonfiction is well within the capabilities of the Interwebs (asterisk).

(asterisk) For many years, it was believed that millions of monkeys hitting millions of keyboards would eventually recreate the works of Shakespeare. Now, thanks to the Internet, we know this to be false.

News flash, dermatologists don't just look at moles and oncologists don't just do differentials... let's see how these isolated systems deal with cleaning up TKI- and IST-related gastric bleeds, C. diff code browns, and timing chemo around liver resections for sepsis. All in a day at County...

My bet is that clinicians who use AI to amplify their own abilities will come to run the system. Errybody else gets to be a glorified NP, at best, or (worse) administrative ;-)

I hope that, as you said, it will allow doctors to focus on more difficult problems that we did not even think would be possible to tackle.

https://www.cato.org/publications/policy-analysis/medical-mo...

Certainly, the medical industry does not face the same competitive pressure from outside, but that is the nature of industry in general.

Rather than calling medicine a monopoly, it is more accurate to accuse heal care providers and practitioners of colluding to ensure prices are high. Monopolies by definition cannot collude since there would be nobody to collude with.

In the grand scheme of things, I believe medical costs are accurately priced and it is people's wages that are not adjusting correctly.

http://www.economist.com/blogs/freeexchange/2007/09/a_spoonf...

Not so, as the number of medical residents is de facto set by Congress (due to how the funding system works), thereby limiting the number of doctors in each specialty.

The critical difference is that there's no limit on the number of people who can get standard driver's licenses, but there is on medical licenses.

It's not just the AMA directly, though. Residencies are funded federally, I believe. I'm pretty sure the numbers per specialty are centrally controlled, but I'm not certain how the process works. And I don't know who limits the medical school slots, but I'm under the impression medical schools can't just increase the number of students at will.

All that being said, keeping the supply artificially low probably has some benefits.

...if drivers got to set the test standard and pass rate.

But I'm not sure opening up the gates is exactly what we want either. There are countless examples of charlatans trying to push the line here, and as a consumer, it would be too difficult, especially while fighting a serious disease, to tell who can really help me and who just wants my money.

There are better ways to make healthcare more affordable and more effective than to throw away the idea of proper certification.

For instance, some states (like the one in which I live) have granted more powers to nurse practitioners. I support this move.

There's even a big sign at the doctors office that says "only one health issue per appointment". Why? So they can scam the system for more cash.

Do you have any experience with the US medical system? I lived in Alberta for 7 years and in Quebec for 3 (important to note because it is hard to take you seriously since you did not even mention that healthcare is provincially administered in Canada).

> I have to book one appt to get referred for a blood test, another to take the blood, and then another appt to get the results!

Here is an alternative explanation to "doctors are incompetent scammers": you need a referral for a specialist so that specialists are not overwhelmed with requests from hypochondriacs who read something on the Internet. Once the test results come back the doctor wants to see you to explain the results and recommend further treatment. That saves everyone time and money and is the opposite of "scam[ming] the system for more cash."

The "one health issue per appointment" is not a government policy, it is a policy that some physicians have so that they can see more patients each day.

Great use of logic.

I still do not understand why you are blaming the general practitioner clinic for referring you to a specialist. If you want same-day STD testing there are a lot of private test centers in Canada. For example, top Google search result: https://www.stdcheck.com/canada/

That's been available here/US and it has come in handy.

If you look at the average earnings, Canadian physicians make ~320K gross salary [1], but they need to pay expenses out of that (reception staff, office, etc.). They do well, but they are not in strata of hedge fund managers.

We should probably just pay them a flat rate, but on the balance the Canadian system is much more cost effective than the US free market system.

[1] http://globalnews.ca/news/2898641/how-much-is-your-doctor-ma...

https://www.youtube.com/user/davidbelk46/videos

I guess doctors don't believe in the free market.

That said, I do agree that we likely won't see the full potential of replacing doctors with machines in the near term simply due to the political and regulatory hurdles, as well as the need to overcome the fear of the public and address the very real and significant privacy issues.

As to anesthesiology, I've actually done some work for a startup in that space working on a system that could very easily move anesthesiologists to a more supervisory role where they would watch (say) 50 surgeries at once (surgeries being handled by software tied into all monitors, as well as EMR systems for history and physical data, and able to dispense chemicals as needed) and step in if and when there was a problem. Technically, there is not much really stopping it, but politics and regulations present significant impediments (and probably rightly so, for now).

https://www.quora.com/Why-is-machine-learning-not-more-widel...

Medical diagnosis in the general case, esp with mis- or disinformation from patients, is quite complex. The data sets available aren't that good given the built-in biases & missing data. What we're seeing is deep learning can help when it focuses on one, little thing with a ton of good data available while ignoring everything else. That's what MYCIN did back when this concept started. That's not enough to replace MD's any time soon.

What you'll find is we can at best supplement the decision-making practices of MD's by running their data through a bunch of ML systems in parallel to try to suggest things they might miss. This data will overtime feed into the ML systems to improve them. Augmented Intelligence, not Artificial Intelligence, will remain the best way to do things due to all the stuff in doctors' brains from their professional experience that's not in machine learning datasets.

It seems that the barriers to automation may be more the result of strong professional associations rather than specific complexities of the job.

Thoughts?

Let me try and give one intuitive explanation; if others would like to chime in with something better, by all means.

Let's suppose that you are classifying objects in images - say bananas and oranges, but it could be tumors or anything that you like.

So we train a classifier to predict this, and we find that of 100 classifications on a hold-out set, we get 73 of them correct. You might, quite reasonably, interpret this to mean that if we randomly select a new image of either an orange or a banana, we will have a 0.73 probability of classifying it correctly. (There are actually some subtleties in this interpretation which I'm ignoring, but they aren't so important for the point I want to make.)

Suppose, however, that we draw out an image that we want to feed into our classifier, and we look at it for a moment. Suppose further that this image contains an object that is long, thing, curved and yellow. We'd expect our classifier to classify it as a banana, and sure enough, it does. Now we draw out another image, except this one has an object that is long, but bent almost completely in a circle, and is more orange than yellow. Now, we might still expect our classifier to classify this as a banana, but should the classifier really be as certain about this prediction as it was about the previous one? Intuitively, I would say not. However, the overall classification accuracy remains unchanged, and so we can't say anything in particular about the certainty of this prediction.

So uncertainty isn't just the proportion of your results that you classify correctly.

Furthermore, it also isn't exactly equivalent to the class probability produced by your classifier, though I don't think this is the best forum for me to get into the details on that.

But you want the uncertainty conditioned to the particular observations you have made.

A ton more here:

http://mlg.eng.cam.ac.uk/yarin/blog_2248.html

I mostly agree with your post, ML has great potential to augment and assist doctors in making the right calls. Paraphrasing Jeremy Howard, "Doctors will be skeptical of these tools coming to take over their jobs at first, but will learn to trust them more and more when they see the kind of predictions they make, thereby slowly but steadily leading to their adoption (as an enhancement or tool) in many areas."

Now, I'm absolutely not saying that we can't engineer solutions in the medical field. You know more than I do about what diagnostic evaluation takes and how procedures are performed, so I don't pretend to understand that aspect perfectly. What I do know for sure is that a machine cannot and will never replicate human thought and decision making and cannot replace a doctor ever until the end of time.

Also, you bring up a good point about salaries. Doctors are important and do great work but deserve to make no more than double or triple what the lowest paid person in their society makes. It's time to bring lawyers, doctors, accountants, developers, engineers—the professional class—back down to reality with the rest of us.

I see your point and agree - if you look at ML and computing in general as a tool useful within the current context of medicine.

But I think the whole field of medicine (or a big part of it) may become obsolete - because the change will be driven by technology, not medicine.

By monitoring people's vitals in real time - think wrist bands which can do blood tests (+ urine, sweat, sperm, etc), feed that real time data to ML algorithms, train it on billions of people and you can accurately tell ahead of time when a person is getting sick. Next day the drone brings the medicine.

Doctors will still be involved of course, but their role will be mostly to confirm whatever the algorithm has decided..

So I think we'll be seeing a move to preventive medicine / real-time monitoring during the next decade or so and within our lifetime people might not be involved in medicine at all.

That is, if we have peace and things go according to plan... Which is a long bet of course.

Preventable conditions are often a combination of genes plus environment plus luck. Trouble is, the "luck" part dominates more often than we'd like. This is why preventive medicine is often accused of being tremendously arrogant.

We've got a long ways to go, and it would help to focus on the highest marginal benefit items. (We were supposed to have flying cars, and all I got was the sum total of Hunan knowledge on my phone... not a bad trade, on balance)

If your profession only relies on reading a bunch of discrete values from monitors, it's a prime candidate for automation regardless of the complex process that derives the values.

https://www.technologyreview.com/s/601141/automated-anesthes...

https://www.washingtonpost.com/business/economy/new-machine-...

The claim that this device is a replacement for an anaesthatist is similar to claiming that an automated wheel balancing machine will one day replace car mechanics. Certainly it can perform one specific component of one kind of anaesthesia, but it is far cry from the full skill set of an anaesthatist.

Once you get to general, for example, the control problem is a lot more difficult because of the required precision.

Physicians will adapt by carving out even narrower niches ("I only specialize in the LEFT eye..." ;). But I really don't see a they-took-our-jobs moment until people are allowed to file lawsuits against AI. Companies will never put out an AI M.D. in the wild unless there's a flesh and blood counterpart to shoulder the liability (+1 job right there).

Don't get me wrong though, I eagerly anticipate the day when going to the doctor/machine is not such a miserable soul-sucking experience... (I'm a physician.)

MDs are not factory workers. First you have the AMA protecting you. Second, there appears to be a very strong preference by humans for medical care to involve another human being there providing the care - in person.

There are other professions where machines are already much better than humans and the need for humans to even be there in person is debatable. Airline pilots for example. Of course, while a computer can fly a plane better than a human and planes can be flown remotely, it will take much longer for passengers to accept the idea and get on a plane without a human pilot in the cockpit.

The effect of machines for pilots already highlights risks to come. Humans still need to be there in person, but they almost never need to do anything but sit there. The job is to be a warm body and tell people to look out the window while they fly over the Rockies (seriously, take off to landing no human is really needed to fly anymore - pilots do nothing 95% of the time).

How did machines taking over the cockpit affect how the pay, benefits, competency and job satisfaction of pilots took a nosedive? Did you see the movie "Sully"? Where a human did step in over the machine, he almost got crucified even though it was the right move he only just barely was able to convince others of it.

Is it possible machines won't replace doctors very soon but could soon start to lead to lower pay, less trust, less prestige (here come the nurse practitioners at least), less need to use your brains at work and less meaningful interaction with patients...? And when a machine can't do something in those rare cases, will the doctor be ready for that? Think the best and brightest still will want to do this? Doctors already are not fans of that thing where patients come in having looked up their symptoms online, well they are about to do that 10x and be more right than you.

Total guess here: how likely is it that we see the best and brightest increasingly go into medical research instead of practice medicine? As the corporate pharma kickbacks you guys get can't make up for the low pay and shitty shit job conditions machines have created for doctors, while nurses and B-team quality doctors take over the actual physician working with patients stuff?

It's not a matter of if, its a matter of when. Greed will be the impetus, and eventually quality catching up will be the nail in the coffin for traditional medicine.

I propose that the doctors who use ai to make themselves damned near infallible (by catching the corner cases where the ai is poorly trained) will make out like bandits, just like top lawyers. The ABA is a monopoly, too, and legal cases are perfect fodder for RNNs. Yet good corporate lawyers still make money faster than they can count it.

Meanwhile, shitty lawyers are out of a job.

Lather, rinse, repeat, but with a million times more regulation and inertia.

Person checks funny looking mole on smartphone app, app with intentionally conservative algorithm says there's some risk it might be a melanoma, dermatologist gets to have a proper look at it in three dimensions (and a second opinion from the medical grade version of the ML app). Result: more people visit doctors over issues that never bothered them that much and the doctor gets assistance with their diagnosis.

And of course some of those people that wouldn't have bothered visiting the doctor under the old system actually do turn out to have a melanoma and the early diagnosis significantly improves their survival chances.

If ML unleash a global increase in diagnostics for all MDs than it's even better.

Not something I would have expected a machine to tell me after a procedure completely unrelated to my heart.

In fact complicated algorithms with so many streams of data that are probably not directly shared by specialists until it is needed may uncover new things even before traditional Doctors spot it

It seems easier to scale compute power than to scale doctors considering how long doctors take to train.

Of course, being able to get a machine to a doctor's level is not easy!

what I'm excited for with AI + medicine is how many poor people will be able to get _some_ level of healthcare where they were previously getting none. These programs aren't free, but once they exist they are cheap to run. so people in 3rd world countries can get their films read, or have an AI dematology program look at their skin.

cynically though, I worry that once these AI programs get perfected they will only exist behind the worlds toughest paywall and insurance will just charge you the same fee to see a real doctor. they'll not let it run films on poor african villagers because they have to "protect their IP" or some bs.

I'm assuming the 'data' for your condition was apparently in the EKG, thus there is no reason in the world an ML shouldnt have picked that up. Where as with humans, maybe you got a tired, new, or bad anesthesiologist.

if you said they made the determination by something other than the EKG, I would be more convinced the 'machine' would have missed it