4 ms·

Medicine has problems that aren't even spelled right theoretically. EHR portability is just a symptom of that issue. Clever solutions like MYCIN, a decision tr

Medicine has problems that aren't even spelled right theoretically. EHR portability is just a symptom of that issue. Clever solutions like MYCIN, a decision tree mapping symptoms and conditions to possible diagnoses, are largely ignored because it is more profitable to maintain a facade and saddle increasingly siloed clinicians with debt.

Animats 4y ago
MYCIN, the rule-based system from the 1980s? It was once touted as "AI", but, like most knowledge based systems, it just takes a set of hand-coded rules and interprets them in a rather simple way.
- SoftTalker 4y ago
  Most of what you learn in medical school is a set of hand-coded rules. It has a fancier legal name, "standard of care" but that's pretty much what it is.
  - Retric 4y ago
    Only for routine cases. Medicine is full of one of uncertainty, edge cases, and new research. The difficulty is identifying what’s novel vs routine, think of the first few COVID cases and the 2022 monkey pox outbreak. When exactly do you sound the alarm?
    - zarzavat 4y ago
      That’s completely true but doctors also miss things, or make errors, that would have been trivially caught by a deterministic rule-based system. Just look at how successful checklists have been in surgery (or air transport), that’s a very simple rule-based system that has saved countless lives. Helping doctors to diagnose effectively requires someone to ask them the right questions. All too often the job of asking questions is left to the patient.
      - Retric 4y ago
        Checklists are great for surgery or routine care because the goal is well understood. Diagnosis is more complicated though I agree a deterministic rule-based system can be useful for first responders and emergency rooms. Prescreening questions asked by a nurse and fed into a rule based system might be helpful in general medicine. The issue is when you have access to someone’s medical history that extremely useful information doesn’t fit well with rule based diagnosis. Similarly a comprehensive and deterministic system would need to include questions for an insane number of edge cases making it difficult to use. Do you really add an option for actually blue skin because of these people: https://en.wikipedia.org/wiki/Blue_Fugates https://en.wikipedia.org/wiki/Blue_Fugates I could see an AI that that recommends medical tests or diagnosis could be useful, rule based systems just seem overly limited.
        mindslight 4y ago
        From my programmer perspective, the point of automating deterministic rule-based systems is so that the humans involved can/will move on to applying non-deterministic intuition-based reasoning - what I would call "intelligence". It feels like most doctors I've met informally run the deterministic rules in their head (as they've been doing for N decades), and then mostly consider themselves having done their job. This makes for a nice and easy job for the common cases, but ends up dropping the uncommon cases on the floor.
        DigDugDude 4y ago
        As I said above, there is widespread use of clinical decision support systems already. They do things like flag patients that the program determines might have sepsis in the hospital. The issue is, even these relatively simple programs generate large numbers of false positives and negatives. Now, let's say someone has an uncommon cause of epigrastric pain. Epigastric pain is a very non-specific symptom to begin with. So, the amount of rule based work up you can do on that information alone even for common causes is very small. Nevermind the uncommon causes. Accurately diagnosing and following up on each patient that walks through your door over the course of an entire 80 year medical history is infinitely more complex than getting a plane from point A to point B. And, the problem of people giving up after having worked through algorithms isn't necessarily solved by more and more formal algorithms. Airline safety is actually a perfect example of why that is the case. Plenty of cases of pilots getting fixated on what the auto pilot is telling them.
curiousllama 4y ago
Diagnostic systems aren’t used because they aren’t useful. Doctors observe-investigate-record; diagnosing a condition from the last step isn’t helpful because in order to get there, a doc has to have already acted on a hunch.
- DigDugDude 4y ago
  This. They act well as warning systems in case you may have missed something, but they don't solve the issue very well of who to work up in the first place or how to do it.
- JPLeRouzic 4y ago
  > diagnosing a condition from the last step isn’t helpful because in order to get there, a doc has to have already acted on a hunch. Half of cancers are only detected in stage IV. https://www.theguardian.com/society/2014/sep/22/cancer-late-diagnosis-half-patients https://www.theguardian.com/society/2014/sep/22/cancer-late-...
  - TaupeRanger 4y ago
    And the systems in question don't improve that situation at all, so what's your point?
    - JPLeRouzic 4y ago
      > the systems in question don't improve that situation I don't think that's true. Look at statistics or ask patients, doctors are very inefficient to detect cancer. On contrary medical imaging technologies are very efficient. Even a simple phone camera & app can automatically detect things like carcinoma or melanoma, when most general practitioners are not able to recognize them for what they are. Another statistical tip is that not all doctors are equals. Depending where you live in country side or big town you do not have the same odds of survival. In Europe simply crossing a border would mean that survival could vary by 20% for the same type of cancer. Eight years ago I designed a simple low cost (~$100) tool to detect heart failure [0] by using resources from Physionet [1]. Physionet competition is motivated by the fact that 1/3 of doctors were shown to be unable to detect heart failure with stethoscope. Competitors show that automatic tools can detect it nearly 100% times. This does not mean the end of general practitioners, they simply will use other methods, more scientific (no more hunch), and anyway more specialists will be needed to operate those smart tools. [0] https://github.com/Hjertesvikt/Hjerte https://github.com/Hjertesvikt/Hjerte [1] https://physionet.org https://physionet.org
DigDugDude 4y ago
Actually, there is widespread use of what are called clinical decision support systems (CDSS). But, one of the primary problems with these systems is they generate a large number of false positives and negatives depending on the context. You still need a physician/nurse/pharmacist to "hand fly the plane". In my own practice, they have been useful to an extent, but they are light years away from automating away clinicians.
- meltyness 4y ago
  Medical education is largely qualitative, overwhelming physicians with basically word associations that approximate a top-5 causes and effects for each body system. Thankfully, I assume most can look things up effectively. This becomes the route, and I'd argue from my experience as a patient that treatment pathways in those CDSSes bias towards the simplest condition-treatment decision calculus, so you can largely strike - in depth history - change over time - transient conditions not needing treatment - drug and non-drug treatment combinations - side effects, long term effects - therapy duration - a clear risk benefit analysis - novel monitoring and feedback mechanisms Doctors burdened with tremendously ineffective EMR systems will miss these things even presented on a silver platter, and you report that the CDSSes do the same thing. Even better - how are they constructed? Voting. In the EU care standards go to a congress of sorts, largely if x then y conditional universal facts are slapped onto a document and supposed to be adhered to. Or in the US (God knows how poisoned these are by "interests") guilds of doctors construct detailed decision trees by committee. That's before we even jam it into some software. It's tough, I understand, but I'm personally a bit inflamed about the matter. And what of CV/ML-based radiological interpretation? ... similarly, how is it that psychiatry doesn't identify cures?
  - DigDugDude 4y ago
    I appreciate your frustration as a patient. Myself, I am both a patient and a clinician. I do think you're missing some things about the way things work "behind the curtain", and I was hoping to offer some insight. I'm not an expert in medical education, but insofar as it is similar to nursing education, a good one is actually taught from "first principles" of anatomy, physiology, chemistry,physics, etc etc, and you diagnose from there with the assistance of heuristics. To the extent that medical education is qualitative, that is because human beings experience things in very qualitative ways. You're treating patients and not fixing servers. Hope this helps. Doing medicine is extremely hard, and automating it is an equally difficult task. You won't have an argument from me about difficult to use EMR systems.

Animats 4y ago

MYCIN, the rule-based system from the 1980s? It was once touted as "AI", but, like most knowledge based systems, it just takes a set of hand-coded rules and interprets them in a rather simple way.

SoftTalker 4y ago
Most of what you learn in medical school is a set of hand-coded rules. It has a fancier legal name, "standard of care" but that's pretty much what it is.
- Retric 4y ago
  Only for routine cases. Medicine is full of one of uncertainty, edge cases, and new research. The difficulty is identifying what’s novel vs routine, think of the first few COVID cases and the 2022 monkey pox outbreak. When exactly do you sound the alarm?
  - zarzavat 4y ago
    That’s completely true but doctors also miss things, or make errors, that would have been trivially caught by a deterministic rule-based system. Just look at how successful checklists have been in surgery (or air transport), that’s a very simple rule-based system that has saved countless lives. Helping doctors to diagnose effectively requires someone to ask them the right questions. All too often the job of asking questions is left to the patient.
    - Retric 4y ago
      Checklists are great for surgery or routine care because the goal is well understood. Diagnosis is more complicated though I agree a deterministic rule-based system can be useful for first responders and emergency rooms. Prescreening questions asked by a nurse and fed into a rule based system might be helpful in general medicine. The issue is when you have access to someone’s medical history that extremely useful information doesn’t fit well with rule based diagnosis. Similarly a comprehensive and deterministic system would need to include questions for an insane number of edge cases making it difficult to use. Do you really add an option for actually blue skin because of these people: https://en.wikipedia.org/wiki/Blue_Fugates https://en.wikipedia.org/wiki/Blue_Fugates I could see an AI that that recommends medical tests or diagnosis could be useful, rule based systems just seem overly limited.
      - mindslight 4y ago
        From my programmer perspective, the point of automating deterministic rule-based systems is so that the humans involved can/will move on to applying non-deterministic intuition-based reasoning - what I would call "intelligence". It feels like most doctors I've met informally run the deterministic rules in their head (as they've been doing for N decades), and then mostly consider themselves having done their job. This makes for a nice and easy job for the common cases, but ends up dropping the uncommon cases on the floor.
        DigDugDude 4y ago
        As I said above, there is widespread use of clinical decision support systems already. They do things like flag patients that the program determines might have sepsis in the hospital. The issue is, even these relatively simple programs generate large numbers of false positives and negatives. Now, let's say someone has an uncommon cause of epigrastric pain. Epigastric pain is a very non-specific symptom to begin with. So, the amount of rule based work up you can do on that information alone even for common causes is very small. Nevermind the uncommon causes. Accurately diagnosing and following up on each patient that walks through your door over the course of an entire 80 year medical history is infinitely more complex than getting a plane from point A to point B. And, the problem of people giving up after having worked through algorithms isn't necessarily solved by more and more formal algorithms. Airline safety is actually a perfect example of why that is the case. Plenty of cases of pilots getting fixated on what the auto pilot is telling them.

curiousllama 4y ago

Diagnostic systems aren’t used because they aren’t useful. Doctors observe-investigate-record; diagnosing a condition from the last step isn’t helpful because in order to get there, a doc has to have already acted on a hunch.

DigDugDude 4y ago
This. They act well as warning systems in case you may have missed something, but they don't solve the issue very well of who to work up in the first place or how to do it.
JPLeRouzic 4y ago
> diagnosing a condition from the last step isn’t helpful because in order to get there, a doc has to have already acted on a hunch. Half of cancers are only detected in stage IV. https://www.theguardian.com/society/2014/sep/22/cancer-late-diagnosis-half-patients https://www.theguardian.com/society/2014/sep/22/cancer-late-...
- TaupeRanger 4y ago
  And the systems in question don't improve that situation at all, so what's your point?
  - JPLeRouzic 4y ago
    > the systems in question don't improve that situation I don't think that's true. Look at statistics or ask patients, doctors are very inefficient to detect cancer. On contrary medical imaging technologies are very efficient. Even a simple phone camera & app can automatically detect things like carcinoma or melanoma, when most general practitioners are not able to recognize them for what they are. Another statistical tip is that not all doctors are equals. Depending where you live in country side or big town you do not have the same odds of survival. In Europe simply crossing a border would mean that survival could vary by 20% for the same type of cancer. Eight years ago I designed a simple low cost (~$100) tool to detect heart failure [0] by using resources from Physionet [1]. Physionet competition is motivated by the fact that 1/3 of doctors were shown to be unable to detect heart failure with stethoscope. Competitors show that automatic tools can detect it nearly 100% times. This does not mean the end of general practitioners, they simply will use other methods, more scientific (no more hunch), and anyway more specialists will be needed to operate those smart tools. [0] https://github.com/Hjertesvikt/Hjerte https://github.com/Hjertesvikt/Hjerte [1] https://physionet.org https://physionet.org

DigDugDude 4y ago

Actually, there is widespread use of what are called clinical decision support systems (CDSS). But, one of the primary problems with these systems is they generate a large number of false positives and negatives depending on the context. You still need a physician/nurse/pharmacist to "hand fly the plane". In my own practice, they have been useful to an extent, but they are light years away from automating away clinicians.

meltyness 4y ago
Medical education is largely qualitative, overwhelming physicians with basically word associations that approximate a top-5 causes and effects for each body system. Thankfully, I assume most can look things up effectively. This becomes the route, and I'd argue from my experience as a patient that treatment pathways in those CDSSes bias towards the simplest condition-treatment decision calculus, so you can largely strike - in depth history - change over time - transient conditions not needing treatment - drug and non-drug treatment combinations - side effects, long term effects - therapy duration - a clear risk benefit analysis - novel monitoring and feedback mechanisms Doctors burdened with tremendously ineffective EMR systems will miss these things even presented on a silver platter, and you report that the CDSSes do the same thing. Even better - how are they constructed? Voting. In the EU care standards go to a congress of sorts, largely if x then y conditional universal facts are slapped onto a document and supposed to be adhered to. Or in the US (God knows how poisoned these are by "interests") guilds of doctors construct detailed decision trees by committee. That's before we even jam it into some software. It's tough, I understand, but I'm personally a bit inflamed about the matter. And what of CV/ML-based radiological interpretation? ... similarly, how is it that psychiatry doesn't identify cures?
- DigDugDude 4y ago
  I appreciate your frustration as a patient. Myself, I am both a patient and a clinician. I do think you're missing some things about the way things work "behind the curtain", and I was hoping to offer some insight. I'm not an expert in medical education, but insofar as it is similar to nursing education, a good one is actually taught from "first principles" of anatomy, physiology, chemistry,physics, etc etc, and you diagnose from there with the assistance of heuristics. To the extent that medical education is qualitative, that is because human beings experience things in very qualitative ways. You're treating patients and not fixing servers. Hope this helps. Doing medicine is extremely hard, and automating it is an equally difficult task. You won't have an argument from me about difficult to use EMR systems.