Women Die More from Heart Attacks Than Men Unless ER Doc Is Female(scientificamerican.com)
scientificamerican.com
Women Die More from Heart Attacks Than Men Unless ER Doc Is Female
https://www.scientificamerican.com/article/women-die-more-from-heart-attacks-than-men-unless-er-doc-is-female/
173 comments
In the new study everyone was more likely to survive if they saw a female physician
Now that's worth noting. And I'm not surprised.
Now that's worth noting. And I'm not surprised.
Did they control for hand size?
There is a case where test animals in laboratories have more stress when a male human is there, compared to female humans.
https://www.nature.com/articles/nmeth.2935
https://www.nature.com/articles/nmeth.2935
Interesting. Could it be pheromones? Or maybe the combination of men sweating more (I actually don't know if that's true, maybe it's just my bias, as I'm a male and men generally smell worse to me than women) and women having a better sense of smell. Or maybe men are more prone to stress (I don't necessarily mean negative stress, men also seem to prefer positive stress, i.e. adrenaline-filled activities), and animals/humans smell that...
In my experience male chickens act more aggressively to male humans than female humans. I think they are aware of our sex.
My brother's African Gray parrot was always friendly to him and an asshole to his wife. Maybe it was sex, but maybe it was just height. I'm given to understand that bird hierarchy is pretty concerned with elevation.
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I absolutely believe that male doctors (in America, anyway, the only place I have experience) may be less receptive to hearing patients' symptoms and issues, but:
"...about 11.9 percent of the time overall—but the research team found women with heart attacks will die about 12.4 percent of the time if their cases are handled by male doctors"
My first thought on reading that was, 0.5 percent is not a huge number, and is the kind of "difference" that could easily fail to replicate.
I feel like our impressions might be slightly thrown off by the fact that the two numbers are percentages. It's a difference of 0.4 percentage points, but that works out to a 4.2% increase in mortality, which seems a bit more substantial.
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The preceding sentence says "If a heart attack patient is a woman and her emergency physician is a man, he says, her risk of death suddenly rises by about 12 percent."
The 11.9 percent mentioned in your quote refers to probability of death for the population (i.e. a random person where the gender of the patient and the doctor is unknown).
The 12.4 percent refers to probability of death for a woman given a male doctor. If that is 12 percent higher, as the quote above says, then the probability of death for a woman given a female doctor is about 11.07%
So its an increase of 1.3 percentage points. The article kind of obfuscates that though.
The 11.9 percent mentioned in your quote refers to probability of death for the population (i.e. a random person where the gender of the patient and the doctor is unknown).
The 12.4 percent refers to probability of death for a woman given a male doctor. If that is 12 percent higher, as the quote above says, then the probability of death for a woman given a female doctor is about 11.07%
So its an increase of 1.3 percentage points. The article kind of obfuscates that though.
I am willing to bet once you account for other things, such as geography, the effect goes away.
Look at the map at the end. It clearly shows women being higher percentage in areas that have better mortality rates for heart disease which are both heavily influenced by access (response time) to medical care and other socioeconomic factors
this is not perfect, but it shows that other factors are probably more likely to be the reason other than jumping to conclusions about which sex is a better doctor.
https://www.kff.org/other/state-indicator/medical-school-gra...
Look at the map at the end. It clearly shows women being higher percentage in areas that have better mortality rates for heart disease which are both heavily influenced by access (response time) to medical care and other socioeconomic factors
this is not perfect, but it shows that other factors are probably more likely to be the reason other than jumping to conclusions about which sex is a better doctor.
https://www.kff.org/other/state-indicator/medical-school-gra...
> jumping to conclusions about which sex is a better doctor.
I don't believe that many people are even suggesting this conclusion.
I don't believe that many people are even suggesting this conclusion.
Unfortunately, outside of more rational circles, I believe a significant number of people will in fact draw some kind of inaccurate and superficial conclusion from this data.
The other interpretation of those stats is that women with male doctors are 4% more likely to die (0.5/11.9), which looks like a pretty meaningful difference. And the sample size is pretty huge especially by medical study standards at over 500k patients.
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A small difference can still be statistically significant.
0.5% difference seems a little questionable to draw conclusions. Agreed.
Why? With a sufficient sample size you can demonstrate even low power effects. The magnitude of the difference does not prevent good scientific analysis at all.
The discussion behind the discussion here is that nobody ever reports confidence intervals... When you don't have them you just have to guess what they are based on what's usual for the field. We're having this entire discussion here but unless the error bars show up it all ought to conclude nothing.
> nobody ever reports confidence intervals
But the article[0], in PNAS, has confidence intervals.
[0] http://www.pnas.org/content/early/2018/07/31/1800097115
But the article[0], in PNAS, has confidence intervals.
[0] http://www.pnas.org/content/early/2018/07/31/1800097115
They don't report it in their abstract, which is all the majority of HN has access to. As a result any conclusions reached will be unfounded. (Unless someone gets the paper and tells us what it said, which is what the linked article's authors were supposed to be doing...)
Edit: The thing is that in the abstract no form of statistical indicator was reported. That plus its absence from the linked article means that unless someone here can get access to the paper our discussion is in vain.
Edit: The thing is that in the abstract no form of statistical indicator was reported. That plus its absence from the linked article means that unless someone here can get access to the paper our discussion is in vain.
As much as people like to talk about how P values are not useful and debate what values we should use, I don't think there's an especially compelling reason to choose confidence intervals over P values, or complain that one is appropriate and the other is not. They both measure the relationship between statistical likelihood and parameter values. P values fix the parameter values and measure the statistical likelihood, confidence intervals fix the statistical likelihood and measure the parameter values. So if you ask for confidence intervals and they give you a P-value, well you have a confidence interval it just won't be a nice round number like 95% or 99%.
It's kind of like complaining that you ordered 1 kg of water but were delivered 1 l, and insisting that everyone measure water by weight rather than volume. Don't read too much into that analogy, but the relationship between P values and confidence intervals is of a broadly similar nature.
It's kind of like complaining that you ordered 1 kg of water but were delivered 1 l, and insisting that everyone measure water by weight rather than volume. Don't read too much into that analogy, but the relationship between P values and confidence intervals is of a broadly similar nature.
Knowing there are over 500k patients in the sample, you can calculate the error bars.
Well, ideally you would know more than just the number of patients. The roughest estimate would be to compute the expected variance of a binomial distribution with N=120e3 and P=0.12, which gives a standard deviation of 0.00094, so a difference of 0.5% is well over 5 standard deviations out. Not quite good enough for particle physics, but you're damn right it's good enough for medicine.
Now you just have to look at group sizes, possible confounding factors, etc...
Now you just have to look at group sizes, possible confounding factors, etc...
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0.5% is not irrelevant when you talk about deaths.
Statistically if you consider the sample size and significance (P = 0.001) it actually looks very non questionable. https://jamanetwork.com/journals/jamainternalmedicine/fullar...
Not clear whether the slight death-rate difference while in ER carries over to the 5-year survival rate, which favors men over women by a large factor.
This is really fascinating (and troubling) statistics, but I can imagine what the explanations can be? Some of the possible explanations suggested in the article does not seem to correspond to the result. For example, if female doctors are better in general, then it should also affect the survival rate of male patients. If current medical research favors male patients, then it should affect the survival rate regardless of the gender of the doctor. If you are better at treating your own gender, then it should also affect women doctors treating men.
The article does provide a explanation that would seem to correspond to the result.
> Still, she adds, the study raises many troubling questions about the treatment of women in the ER, “like the concern there’s a systematic bias where male physicians are not listening to female patients’ complaints as readily as [those of] a man.”
Simply put, if social conditioning causes men to take the concerns of male patients more seriously than female patients (OR inversely, social conditioning makes female patients less likely to share potentially relevant information with male doctors in the first place), it would explain the difference pretty easily.
Personally, I always prefer to have a female doctor when given the option. My theory is that even if only 0.1% of male doctors harbor a bias against female patients, and even if it's only a mild bias in most cases, I can avoid that chance pretty much completely by going to a female doctor. I guess it's possible for female doctors to be sexist against women, but it seems very unlikely given that most female doctors themselves would have experienced sexism against women at some point and thus would be more aware of it and more invested in overcoming it.
> Still, she adds, the study raises many troubling questions about the treatment of women in the ER, “like the concern there’s a systematic bias where male physicians are not listening to female patients’ complaints as readily as [those of] a man.”
Simply put, if social conditioning causes men to take the concerns of male patients more seriously than female patients (OR inversely, social conditioning makes female patients less likely to share potentially relevant information with male doctors in the first place), it would explain the difference pretty easily.
Personally, I always prefer to have a female doctor when given the option. My theory is that even if only 0.1% of male doctors harbor a bias against female patients, and even if it's only a mild bias in most cases, I can avoid that chance pretty much completely by going to a female doctor. I guess it's possible for female doctors to be sexist against women, but it seems very unlikely given that most female doctors themselves would have experienced sexism against women at some point and thus would be more aware of it and more invested in overcoming it.
"Simply put, if social conditioning causes men to take the concerns of male patients more seriously than female patients (OR inversely, social conditioning makes female patients less likely to share potentially relevant information with male doctors in the first place), it would explain the difference pretty easily."
But given the opprobrium currently attached to labeling someone "SEXIST" in our society, personally I'd like to see a bit more evidence, and some alternate explanations explored and ruled out, before we start wheeling that one out and tarring people with it.
The other problem with that is more practical... if it "truly is" sexism, then you also foreclose any chance of fixing it, because there's just no way you're going to go to doctors and make them precisely 10% less sexist than they are now. But if it is in fact something else, it may be fixable. (Or illusory.)
But given the opprobrium currently attached to labeling someone "SEXIST" in our society, personally I'd like to see a bit more evidence, and some alternate explanations explored and ruled out, before we start wheeling that one out and tarring people with it.
The other problem with that is more practical... if it "truly is" sexism, then you also foreclose any chance of fixing it, because there's just no way you're going to go to doctors and make them precisely 10% less sexist than they are now. But if it is in fact something else, it may be fixable. (Or illusory.)
Lots of people have biases that they don't realize can impact the quality of their interactions. There's a frequent issue where people who speak English as their second language are more likely to be perceived as less intelligent. Certain thick regional accents also can cause that issue.
Part of the educational process for all professionals, especially doctors, includes learning to monitor for potential prejudices like that and taking steps to ensure it does not impact your ability to deliver high quality care (ie, ask more questions or have a colleague review your work if you are unsure).
I'm not tar and feathering people. But when women in our society are constantly saying "Some men don't take me as seriously as my male counterparts despite my equal (or superior) credentials" then maybe there is some truth to that which can bleed over professional interactions in hospitals as well? I've experienced it first hand myself professionally (never been to the ER) only a handful of times, but I don't think it's the norm, and I don't go into professional situations with men assuming it will happen. Still, when it happens, it sucks and I wish other men would talk to those guys and tell them why it sucks so those guys will do better.
We've gone a long way towards making sexism less of a problem for everyday women. Just because there are a few examples of it that have slipped by doesn't mean we give up. We just know more of what to watch out for.
Part of the educational process for all professionals, especially doctors, includes learning to monitor for potential prejudices like that and taking steps to ensure it does not impact your ability to deliver high quality care (ie, ask more questions or have a colleague review your work if you are unsure).
I'm not tar and feathering people. But when women in our society are constantly saying "Some men don't take me as seriously as my male counterparts despite my equal (or superior) credentials" then maybe there is some truth to that which can bleed over professional interactions in hospitals as well? I've experienced it first hand myself professionally (never been to the ER) only a handful of times, but I don't think it's the norm, and I don't go into professional situations with men assuming it will happen. Still, when it happens, it sucks and I wish other men would talk to those guys and tell them why it sucks so those guys will do better.
We've gone a long way towards making sexism less of a problem for everyday women. Just because there are a few examples of it that have slipped by doesn't mean we give up. We just know more of what to watch out for.
Isn't he also trying to say that perhaps the bias that some women have against male doctors might also contribute to the statistic? In other words, women heart attack patients might be more stressed or worried with male doctors leading to higher mortality.
You yourself admit to being biased against male doctors.
You yourself admit to being biased against male doctors.
"We've gone a long way towards making sexism less of a problem for everyday women."
I couldn't have asked for a better example of precisely what I was talking about. We are so primed to jump down people's throat because of SEXISM that by the time you reached the end of your post, you've already slipped into the assumption that it's the only possible explanation, and are lecturing the doctors in question about how sexist they are and how they should stop it.
It is counter to the principles of science to be so sure, though. It's not that large of an effect, even with the population size, and there's plenty of room for some other systematic error to be the problem.
But you've been programmed to assume that if I'm bringing up the possibility that a scientific paper may have a second explanation, then politically I must also be denying the existence of sexism in the universe and must therefore be downvoted and also lectured to about how important it is that we not be sexist.
But I reject your attempt to exert moral superiority, for the exact reasons I gave in the original post. What's important is not shutting down sexism and scoring moral preening points for having Right Opinions. What's important is finding the real cause, so we can address it. Science is filled unto overflowing with examples and inductive proof that when people go into something with a predetermined conclusion about the causes of some phenomenon, they are often wrong, and end up doing great harm because of it. If we have to choose between getting to yell at people because Sexism, or actually fixing the real problem, which is it going to be?
Unfortunately, as your own message demonstrates, which I have no reason to believe is particularly exceptional, I know the answer. In 2018, it's getting to yell at people Because Sexism, and to hell with whatever the real reason may be. We already know the real reason, and it's Sexism. Because in 2018, even if the real reason isn't sexism, the real reason is still sexism, you just must not be looking hard enough.
I couldn't have asked for a better example of precisely what I was talking about. We are so primed to jump down people's throat because of SEXISM that by the time you reached the end of your post, you've already slipped into the assumption that it's the only possible explanation, and are lecturing the doctors in question about how sexist they are and how they should stop it.
It is counter to the principles of science to be so sure, though. It's not that large of an effect, even with the population size, and there's plenty of room for some other systematic error to be the problem.
But you've been programmed to assume that if I'm bringing up the possibility that a scientific paper may have a second explanation, then politically I must also be denying the existence of sexism in the universe and must therefore be downvoted and also lectured to about how important it is that we not be sexist.
But I reject your attempt to exert moral superiority, for the exact reasons I gave in the original post. What's important is not shutting down sexism and scoring moral preening points for having Right Opinions. What's important is finding the real cause, so we can address it. Science is filled unto overflowing with examples and inductive proof that when people go into something with a predetermined conclusion about the causes of some phenomenon, they are often wrong, and end up doing great harm because of it. If we have to choose between getting to yell at people because Sexism, or actually fixing the real problem, which is it going to be?
Unfortunately, as your own message demonstrates, which I have no reason to believe is particularly exceptional, I know the answer. In 2018, it's getting to yell at people Because Sexism, and to hell with whatever the real reason may be. We already know the real reason, and it's Sexism. Because in 2018, even if the real reason isn't sexism, the real reason is still sexism, you just must not be looking hard enough.
I'm flattered by your interpretation of my comment as one which allows me to "exert moral superiority". I have made no judgements against your morals, only against the merits of your arguments. Now let me correct your other misconceptions.
>> "We've gone a long way towards making sexism less of a problem for everyday women."
> I couldn't have asked for a better example of precisely what I was talking about. We are so primed to jump down people's throat because of SEXISM that by the time you reached the end of your post, you've already slipped into the assumption that it's the only possible explanation, and are lecturing the doctors in question about how sexist they are and how they should stop it.
You misunderstand context. That last line was there to convey the sentiment that society HAS successfully addressed sexism in the past. It was a direct refutation of your claim:
> if it "truly is" sexism, then you also foreclose any chance of fixing it...
> But you've been programmed to assume that if I'm bringing up the possibility that a scientific paper may have a second explanation, then politically I must also be denying the existence of sexism in the universe and must therefore be downvoted and also lectured to about how important it is that we not be sexist.
1. Calling people "programmed" for disagreeing with you is rude, and hacker news readers tend to prefer polite discourse - this may have affected your votes.
2. You did not propose a second explanation at all. You simply said that the one I proposed should not even be investigated until every other alternative is ruled out. How can you claim to care about science but not even be willing to investigate a hypothesis that is supported by data, just because you don't like the idea that it relates to a political and social topic? Take your anger out on the people tar-and-feathering, not the people trying to figure out how to stop women from dying disproportionately due to preventable health issues. If you really have a strong theory on an alternative reason behind this data, then propose it and make your own case.
3. "lectured"? I disagree with your assessment of tone there. I simply re-iterated my argument with context that is more relatable to hacker news readers and shared a relevant experience.
The point is: Even if it's NOT sexism underlying the root cause of this particular issue, you appear logically biased when you dismiss the role it could play for no reason other than "I don't like when people blame sexism for things". Dismissing it out of hand due to a purely emotional appeal makes it seem like your analysis is troubled. It's as short-sighted and illogical as people who blame sexism for every little thing ever. Morality aside, the downvotes you earned were well deserved due to the poor quality of argument and the uncivil tone.
Also, "sexism" doesn't need to have the "s" capitalized.
>> "We've gone a long way towards making sexism less of a problem for everyday women."
> I couldn't have asked for a better example of precisely what I was talking about. We are so primed to jump down people's throat because of SEXISM that by the time you reached the end of your post, you've already slipped into the assumption that it's the only possible explanation, and are lecturing the doctors in question about how sexist they are and how they should stop it.
You misunderstand context. That last line was there to convey the sentiment that society HAS successfully addressed sexism in the past. It was a direct refutation of your claim:
> if it "truly is" sexism, then you also foreclose any chance of fixing it...
> But you've been programmed to assume that if I'm bringing up the possibility that a scientific paper may have a second explanation, then politically I must also be denying the existence of sexism in the universe and must therefore be downvoted and also lectured to about how important it is that we not be sexist.
1. Calling people "programmed" for disagreeing with you is rude, and hacker news readers tend to prefer polite discourse - this may have affected your votes.
2. You did not propose a second explanation at all. You simply said that the one I proposed should not even be investigated until every other alternative is ruled out. How can you claim to care about science but not even be willing to investigate a hypothesis that is supported by data, just because you don't like the idea that it relates to a political and social topic? Take your anger out on the people tar-and-feathering, not the people trying to figure out how to stop women from dying disproportionately due to preventable health issues. If you really have a strong theory on an alternative reason behind this data, then propose it and make your own case.
3. "lectured"? I disagree with your assessment of tone there. I simply re-iterated my argument with context that is more relatable to hacker news readers and shared a relevant experience.
The point is: Even if it's NOT sexism underlying the root cause of this particular issue, you appear logically biased when you dismiss the role it could play for no reason other than "I don't like when people blame sexism for things". Dismissing it out of hand due to a purely emotional appeal makes it seem like your analysis is troubled. It's as short-sighted and illogical as people who blame sexism for every little thing ever. Morality aside, the downvotes you earned were well deserved due to the poor quality of argument and the uncivil tone.
Also, "sexism" doesn't need to have the "s" capitalized.
> But given the opprobrium currently attached to labeling someone "SEXIST" in our society, personally I'd like to see a bit more evidence, and some alternate explanations explored and ruled out, before we start wheeling that one out and tarring people with it.
There's opprobrium attached to being uniquely sexist / otherwise bigoted, but I think there is relatively little opprobrium in saying that most men, statistically, behave in the following way because of social conditioning since childhood, and no man in the relevant population is specifically intending to be sexist. That's where the whole idea of "unconscious bias" comes from. (Arguably, the entire idea of "unconscious bias" training is to provide a way for companies to address these types of issues precisely without having to label their employees sexist and bring out the tar.)
Also, even if it did require tar, I think we would need to have a hard discussion about where the tradeoff between "more patients die, but doctors have good reputations" and "fewer patients die, but people think doctors are sexist" is. It does not seem obvious to me that we should choose the former.
> because there's just no way you're going to go to doctors and make them precisely 10% less sexist than they are now.
I don't see how this follows.
For instance, you can imagine pretty direct ways to work around both potential explanations: if it's social conditioning on the part of the doctor, have patients report pain on an objective scale (i.e., not "1-10", I believe there are studies that women statistically report lower scores than men; instead assign specific comparisons like "stubbing your toe" or "unable to focus on work" or whatever), and ask doctors to respond in standard ways based on the response. Again - assuming that this isn't doctors consciously choosing to ignore women's concerns - we should probably assume doctors are actually interested in giving their patients meaningful care. If the social conditioning is on the side of patients not reporting pain, make sure there are enough women medical professionals around and have a practice of women reporting their symptoms to a woman. (Since nurses are something like 90+% women this shouldn't be too difficult; it would just require asking male doctors to calibrate their responses to nurses' notes instead of asking questions de novo.)
Also, historically, we have seen examples of people becoming less sexist and less bigoted. The idea that women just do not have the mental capabilities to vote, for instance, has become an extreme minority position. It may take generations of change, but it's still a change that we can effect.
Also, even if we're talking about populations, it's not really the case that every person is equally sexist. If you want to make doctors precisely 10% less sexist, measure them for sexism and reject the ones that exhibit abnormally high levels of sexism.
There's opprobrium attached to being uniquely sexist / otherwise bigoted, but I think there is relatively little opprobrium in saying that most men, statistically, behave in the following way because of social conditioning since childhood, and no man in the relevant population is specifically intending to be sexist. That's where the whole idea of "unconscious bias" comes from. (Arguably, the entire idea of "unconscious bias" training is to provide a way for companies to address these types of issues precisely without having to label their employees sexist and bring out the tar.)
Also, even if it did require tar, I think we would need to have a hard discussion about where the tradeoff between "more patients die, but doctors have good reputations" and "fewer patients die, but people think doctors are sexist" is. It does not seem obvious to me that we should choose the former.
> because there's just no way you're going to go to doctors and make them precisely 10% less sexist than they are now.
I don't see how this follows.
For instance, you can imagine pretty direct ways to work around both potential explanations: if it's social conditioning on the part of the doctor, have patients report pain on an objective scale (i.e., not "1-10", I believe there are studies that women statistically report lower scores than men; instead assign specific comparisons like "stubbing your toe" or "unable to focus on work" or whatever), and ask doctors to respond in standard ways based on the response. Again - assuming that this isn't doctors consciously choosing to ignore women's concerns - we should probably assume doctors are actually interested in giving their patients meaningful care. If the social conditioning is on the side of patients not reporting pain, make sure there are enough women medical professionals around and have a practice of women reporting their symptoms to a woman. (Since nurses are something like 90+% women this shouldn't be too difficult; it would just require asking male doctors to calibrate their responses to nurses' notes instead of asking questions de novo.)
Also, historically, we have seen examples of people becoming less sexist and less bigoted. The idea that women just do not have the mental capabilities to vote, for instance, has become an extreme minority position. It may take generations of change, but it's still a change that we can effect.
Also, even if we're talking about populations, it's not really the case that every person is equally sexist. If you want to make doctors precisely 10% less sexist, measure them for sexism and reject the ones that exhibit abnormally high levels of sexism.
People on HN frequently proclaim that we need self-driving cars now, now, now!! to prevent thousands of deaths caused by car accidents every day—even if it involves "breaking a few eggs" in the short term.
Meanwhile, I feel like those very same people would be very reluctant to "play the sexism card", even if it meant that thousands of women's lives could be saved, and even though this is a problem that has been pointed out and studied for a long time[1], and that it's potentially much easier to correct our biases with better training than it is to approach general AI with technology.
I really wish these trends were reversed.
[1] See Serena Williams' childbirth story for one recent example: https://qz.com/1177004/serena-williamss-terrifying-childbirt...
Meanwhile, I feel like those very same people would be very reluctant to "play the sexism card", even if it meant that thousands of women's lives could be saved, and even though this is a problem that has been pointed out and studied for a long time[1], and that it's potentially much easier to correct our biases with better training than it is to approach general AI with technology.
I really wish these trends were reversed.
[1] See Serena Williams' childbirth story for one recent example: https://qz.com/1177004/serena-williamss-terrifying-childbirt...
Life is not a conspiracy against your opinions, be carefull with accusations like that. Do not make up fictional enemies.
But shouldn't this effect be across all health issues then, not just heart attacks?
Yes, and I have strong feeling it probably is. It's a hard statistic to measure in other fields though. Fatalities due to heart failure are pretty open and shut. For other conditions, especially in fields such as psychiatry, the effect of doctors not taking the symptoms of women seriously is more likely to manifest in the form of misdiagnoses, which can't be easily detected or tracked. Furthermore, many criteria for diagnosing diseases were developed based on primarily male subjects, so some conditions (such as autism-spectrum disorders) are somewhat underdiagnosed in women due to confusion over presentation in female patients. That isn't necessarily the doctor's fault, but the outcome can make it hard to distinguish whether the fault is with a doctor who dismissed a patient's symptoms due to sex, or whether it's just insufficient diagnostic criteria.
as another point of data:
https://www.health.harvard.edu/blog/women-and-pain-dispariti...
https://www.health.harvard.edu/blog/women-and-pain-dispariti...
I also wonder if it might be because men are trained to complain less and "man up". But the whole concept of "hysteria" has a long medical history so we certainly can't ignore that very possible reality.
Actually. I think it's the opposite in this case. That is, these are heart attacks that end up in __ER__ not all HA's. The bias is that women don't have HT's so __if__ they end up in ER then it's likely to be bad.
Can you explain what you mean by hysteria and provide some salient evidence, please?
Sure. "Hysteria" being a nonsense medical diagnosis from the past that's basically the poster child for sexism in medicine (https://en.wikipedia.org/wiki/Female_hysteria).
I bring it up because I'm suggesting that one possible explanation is that maybe this study is revealing yet remaining sexism in medicine. Just like the whole nonsense concept of hysteria, maybe professionals still discriminate by assuming women are just being "hysterical". Not consciously, but more as an artifact of western medicine and society.
I also strongly reccommend this fantastic podcast about the topic: http://www.maximumfun.org/sawbones/sawbones-hysteria
I hope this satisfies your question. I suspect I was just not clear enough that I was not legitimately suggesting hysteria as an actual explanation.
I bring it up because I'm suggesting that one possible explanation is that maybe this study is revealing yet remaining sexism in medicine. Just like the whole nonsense concept of hysteria, maybe professionals still discriminate by assuming women are just being "hysterical". Not consciously, but more as an artifact of western medicine and society.
I also strongly reccommend this fantastic podcast about the topic: http://www.maximumfun.org/sawbones/sawbones-hysteria
I hope this satisfies your question. I suspect I was just not clear enough that I was not legitimately suggesting hysteria as an actual explanation.
Thank you, this podcast episode looks worthwhile. I did misread your intent, I’m afraid; otherwise the history of hysteria is familiar to me.
Note, also from the article:
"In the new study everyone was more likely to survive if they saw a female physician, and a study(1) published last year in JAMA Internal Medicine indicated all patients of female physicians had lower mortality and hospital readmission rates. “It seems that the female doctors practice in a better way or outperform male doctors,” says the JAMA study’s first author, Yusuke Tsugawa, an assistant professor of medicine at the David Geffen School of Medicine at University of California, Los Angeles."
1) https://jamanetwork.com/journals/jamainternalmedicine/fullar...
"In the new study everyone was more likely to survive if they saw a female physician, and a study(1) published last year in JAMA Internal Medicine indicated all patients of female physicians had lower mortality and hospital readmission rates. “It seems that the female doctors practice in a better way or outperform male doctors,” says the JAMA study’s first author, Yusuke Tsugawa, an assistant professor of medicine at the David Geffen School of Medicine at University of California, Los Angeles."
1) https://jamanetwork.com/journals/jamainternalmedicine/fullar...
That directly contradicts this:
> The researchers divided 500,000-plus cases into four categories: male doctors treating men; male doctors treating women; female doctors treating men; and female doctors treating women. “All of those are statistically indistinguishable except for male doctor–female patient,” says Brad Greenwood, an author on the study and a data scientist at the University of Minnesota.
> The researchers divided 500,000-plus cases into four categories: male doctors treating men; male doctors treating women; female doctors treating men; and female doctors treating women. “All of those are statistically indistinguishable except for male doctor–female patient,” says Brad Greenwood, an author on the study and a data scientist at the University of Minnesota.
> That directly contradicts this
No, it just means in this study's data, there was no statistically significant signal that there was a difference between the groups treated by a male doctor vs a female doctor.
That doesn't mean there's not a difference in outcomes, just that one isn't suitably demonstrated by this data, but it's also a result over a completely different subset of the population than was looked at by the study in the GP's link (which was of hospitalized Medicare patients age 65 or over).
No, it just means in this study's data, there was no statistically significant signal that there was a difference between the groups treated by a male doctor vs a female doctor.
That doesn't mean there's not a difference in outcomes, just that one isn't suitably demonstrated by this data, but it's also a result over a completely different subset of the population than was looked at by the study in the GP's link (which was of hospitalized Medicare patients age 65 or over).
Actually if you look at their full sample data you'll see that women physicians had higher survival rates for both make and female patients. It's just that only female patients were statistically different from zero. And note that just because female-female was statistically significant and female-male was not, that doesn't by itself imply that female-female was statically distinguishable from female-male. (Though it may have been, I don't understand all the controls.)
I'm guessing it's a combination. Heart attack signs and symptoms are different for men and women. But most of the awareness and training, especially in the past, has been more focused on the typically male symptoms.
Add to that the likely facts that 1) women doctors are, on average, more recently trained than men doctors; 2) women doctors are probably far more likely to be aware of the differences in symptoms between the traditionally discussed symptoms and those that are specific to women, simply from a self-interest perspective; 3) men are likely to be a higher percentage of heart attack patients, so the effect of fewer men being as aware of women-specific symptoms of heart attacks would be amplified by the relative frequency of the occurrences (ie, they see few female heart attacks and so the differences in appropriate treatment are less likely to sink in with someone who doesn't have a personal awareness ("what if this were me having the heart attack?")).
But yes I agree it's too bad these topics were skipped in the article in favor of less likely differences (such as "women are better doctors"--something that I wonder if it's controlled for age, but might just be the effect of the fact that women who do make it through medical school and continue to practice are probably just far more driven and serious about the career than similar men, because the obstacles women face in reaching the same point in their career are much higher, so the women who do make it through will naturally be better doctors than the "average" man doctor).
Add to that the likely facts that 1) women doctors are, on average, more recently trained than men doctors; 2) women doctors are probably far more likely to be aware of the differences in symptoms between the traditionally discussed symptoms and those that are specific to women, simply from a self-interest perspective; 3) men are likely to be a higher percentage of heart attack patients, so the effect of fewer men being as aware of women-specific symptoms of heart attacks would be amplified by the relative frequency of the occurrences (ie, they see few female heart attacks and so the differences in appropriate treatment are less likely to sink in with someone who doesn't have a personal awareness ("what if this were me having the heart attack?")).
But yes I agree it's too bad these topics were skipped in the article in favor of less likely differences (such as "women are better doctors"--something that I wonder if it's controlled for age, but might just be the effect of the fact that women who do make it through medical school and continue to practice are probably just far more driven and serious about the career than similar men, because the obstacles women face in reaching the same point in their career are much higher, so the women who do make it through will naturally be better doctors than the "average" man doctor).
You're discussing things which are discussed in the abstract of the linked study... which makes it all the more frustrating that these things are omitted from the article.
> Patients treated by female physicians had lower 30-day mortality (adjusted mortality, 11.07% vs 11.49%; adjusted risk difference, –0.43%; 95% CI, –0.57% to –0.28%; P < .001; number needed to treat to prevent 1 death, 233) and lower 30-day readmissions (adjusted readmissions, 15.02% vs 15.57%; adjusted risk difference, –0.55%; 95% CI, –0.71% to –0.39%; P < .001; number needed to treat to prevent 1 readmission, 182) than patients cared for by male physicians, after accounting for potential confounders.
> Patients treated by female physicians had lower 30-day mortality (adjusted mortality, 11.07% vs 11.49%; adjusted risk difference, –0.43%; 95% CI, –0.57% to –0.28%; P < .001; number needed to treat to prevent 1 death, 233) and lower 30-day readmissions (adjusted readmissions, 15.02% vs 15.57%; adjusted risk difference, –0.55%; 95% CI, –0.71% to –0.39%; P < .001; number needed to treat to prevent 1 readmission, 182) than patients cared for by male physicians, after accounting for potential confounders.
> 2) women doctors are probably far more likely to be aware of the differences in symptoms between the traditionally discussed symptoms and those that are specific to women, simply from a self-interest perspective;
Meanwhile here we are on a forum of randos from the internet, and half the thread is people noting that heart attacks have different symptoms in men and women. So what's the doctor's excuse?
I'm not saying this to argue with you, I mostly agree. The point is if that's the explanation, it's a pretty pitiful one.
Meanwhile here we are on a forum of randos from the internet, and half the thread is people noting that heart attacks have different symptoms in men and women. So what's the doctor's excuse?
I'm not saying this to argue with you, I mostly agree. The point is if that's the explanation, it's a pretty pitiful one.
[deleted]
Heart attack symptoms differ in men and women. The most common ones in men (chest and left arm pain) are less common in women.
Perhaps female doctors are more likely to be familiar with the symptoms of heart attack in women.
Additionally, I think there's a stereotype of a heart attack being a male affliction (probably because the difference in symptoms led to underdiagnosis in women in the mid-20thC). It's conceivable that male doctors are less likely to consider heart attack as a diagnosis for a woman even when the symptoms are typical of a heart attack?
Perhaps female doctors are more likely to be familiar with the symptoms of heart attack in women.
Additionally, I think there's a stereotype of a heart attack being a male affliction (probably because the difference in symptoms led to underdiagnosis in women in the mid-20thC). It's conceivable that male doctors are less likely to consider heart attack as a diagnosis for a woman even when the symptoms are typical of a heart attack?
I don’t have sources but I remember reading that heart issues manifest differently in women than men and that women weren’t taken as seriously when explaining their symptoms (indicative of heart issues) to male docs. I think that would explain why the reverse situation doesn’t arise.
[deleted]
Like this [0] issue, but for heart problems specifically? How pervasive is this...
[0] https://digitalcommons.law.umaryland.edu/cgi/viewcontent.cgi...
[0] https://digitalcommons.law.umaryland.edu/cgi/viewcontent.cgi...
Yeah. Here I think is an article I’d read about it: https://www.theatlantic.com/health/archive/2015/10/heart-dis...
I'm curious what people would propose we do about this? What if it turns out that doctors of the same ethnic group treat their co-ethnics better, even if it isn't conscious? I fear the conclusion people will draw is just a new form of segregation in every area of life.
Or maybe it's an argument in favor of diversity:
"The male doctors in their study were better at treating women with heart attacks when they had more experience treating such patients—and especially when they worked in hospitals with more female doctors. This suggests that whatever female doctors are doing that’s better is also transferable."
https://www.theatlantic.com/science/archive/2018/08/women-mo...
"The male doctors in their study were better at treating women with heart attacks when they had more experience treating such patients—and especially when they worked in hospitals with more female doctors. This suggests that whatever female doctors are doing that’s better is also transferable."
https://www.theatlantic.com/science/archive/2018/08/women-mo...
"These differences persisted even after the team accounted for factors like the doctors’ years of experience.."
So, I'm having a little bit of trouble reconciling these two statements. Who are "such patients" and why wouldn't doctors with more years of experience have more experience treating them?
So, I'm having a little bit of trouble reconciling these two statements. Who are "such patients" and why wouldn't doctors with more years of experience have more experience treating them?
"Such patients" means women who had heart attacks. Apparently, "years of experience" doesn't necessarily mean the same thing? Maybe some kinds of experience are better than others?
But if you really want to dig into this you'll probably have to read the paper.
But if you really want to dig into this you'll probably have to read the paper.
Train them better. There’s nothing inherent about these studies’ results. Doctors are well-educated human beings and are capable of correcting for their subconscious biases.
If that is true (which I think there isn't a real reason to believe a priori, but sure, it's a possible hypothesis), I feel like I'd prefer a world where more people live to a world with less segregation, if I had to choose.
Try to replicate in a more rigorous statistical setting. Do nothing until the result is replicated. I’d be willing to bet a significant amount of money that this result is due to a missed latent variable (or a few) that explains everything without making it seem like gender is causal to the outcome.
> The researchers divided 500,000-plus cases into four categories: male doctors treating men; male doctors treating women; female doctors treating men; and female doctors treating women. “All of those are statistically indistinguishable except for male doctor–female patient,”
> Female doctors may also simply be performing at least some parts of the job better than their male counterparts do. In the new study everyone was more likely to survive if they saw a female physician, and a study published last year in JAMA Internal Medicine indicated all patients of female physicians had lower mortality and hospital readmission rates.
Both of the above findings are at least somewhat contradictory, given that the first study found no statistical difference between male-patient-outcomes when being treated by male vs female doctors. Before jumping to conclusions, I think it's worth studying this effect more rigorously first. The female cardiologist they quoted said it best:
> It is a little early to say male physicians have trouble treating female heart attack patients based on these data alone, says Michelle O’Donoghue, a cardiologist at Brigham and Women’s Hospital and Harvard Medical School who did not work on the new study. “Spurious signals sometimes come up [in research], so this should be replicated,”
Or as xkcd would put it: https://xkcd.com/882/
> Female doctors may also simply be performing at least some parts of the job better than their male counterparts do. In the new study everyone was more likely to survive if they saw a female physician, and a study published last year in JAMA Internal Medicine indicated all patients of female physicians had lower mortality and hospital readmission rates.
Both of the above findings are at least somewhat contradictory, given that the first study found no statistical difference between male-patient-outcomes when being treated by male vs female doctors. Before jumping to conclusions, I think it's worth studying this effect more rigorously first. The female cardiologist they quoted said it best:
> It is a little early to say male physicians have trouble treating female heart attack patients based on these data alone, says Michelle O’Donoghue, a cardiologist at Brigham and Women’s Hospital and Harvard Medical School who did not work on the new study. “Spurious signals sometimes come up [in research], so this should be replicated,”
Or as xkcd would put it: https://xkcd.com/882/
Haven't RTFAed (on mobile with shit internet). Does the gender of the ER doc effect a change in male mortality rates as well?
> The researchers divided 500,000-plus cases into four categories: male doctors treating men; male doctors treating women; female doctors treating men; and female doctors treating women. “All of those are statistically indistinguishable except for male doctor–female patient,” says Brad Greenwood, an author on the study and a data scientist at the University of Minnesota. If a heart attack patient is a woman and her emergency physician is a man, he says, her risk of death suddenly rises by about 12 percent.
I wanted to look at the actual numbers and see how close the findings were, but I don't see the study linked nor the title of the study (I do see a different study, but it isn't the one those numbers are from).
A different article someone else linked seemed to have the study, but it is behind a pay wall.
http://www.pnas.org/cgi/doi/10.1073/pnas.1800097115
This seems to have the actual numbers though.
http://www.pnas.org/content/pnas/suppl/2018/07/31/1800097115...
I'm having trouble grasping how to read the tables (especially given it seems Female Physician Female Patient is repeated twice on tables S2 and S3, but I think that is just a title error.
Here are the numbers, best as I can grasp.
S2 is full, S3 is matched
Mean then standard deviation.
Edit: formatting
A different article someone else linked seemed to have the study, but it is behind a pay wall.
http://www.pnas.org/cgi/doi/10.1073/pnas.1800097115
This seems to have the actual numbers though.
http://www.pnas.org/content/pnas/suppl/2018/07/31/1800097115...
I'm having trouble grasping how to read the tables (especially given it seems Female Physician Female Patient is repeated twice on tables S2 and S3, but I think that is just a title error.
Here are the numbers, best as I can grasp.
S2 is full, S3 is matched
Mean then standard deviation.
M/MS2:.881/.114
M/MS3:.870/.124
M/FS2:.854/.353
M/FS3:.861/.121
F/MS2:.887/.120
F/MS3:.867/.130
F/FS2:.857/.116
F/FS3:.862/.112
Edit: formatting
[deleted]
This is an area which exposes how subconscious discrimination is itself a significant problem, not just overt sexism. Doctors who don't take women's reported symptoms as seriously results in more women dying, without any malice or intentional discrimination.
Your assumption is possible to be true but is not the only possible cause and the article it is very clear about the conclusions, as an example someone linked in this comments some differences were notices with animals too.
An objective test would fix the problem (removing subconscious bias).
https://newsroom.heart.org/news/more-sensitive-blood-test-di...
> A new high-sensitivity blood test for heart attacks successfully diagnosed heart attacks faster and more accurately in the emergency room than the existing test.
> The new high-sensitivity blood test for cardiac troponin, given in a hospital emergency room, was also found to be safe and effective. When patients present to emergency rooms with heart attack symptoms, doctors assess them in part by using a cardiac troponin test to measure a protein released into the blood when the heart is damaged.
> “We did not miss any heart attacks using this test in this population,” said lead author Rebecca Vigen, M.D., M.S.C.S., a cardiologist at the University of Texas Southwestern Medical Center. “The test also allowed us to determine faster that many patients who had symptoms of a heart attack were not having a heart attack than if we had relied on the traditional test.”
I would even advocate for this test being administered by EMTs and other first responders, instead of waiting until the patient arrives at the ER.
https://newsroom.heart.org/news/more-sensitive-blood-test-di...
> A new high-sensitivity blood test for heart attacks successfully diagnosed heart attacks faster and more accurately in the emergency room than the existing test.
> The new high-sensitivity blood test for cardiac troponin, given in a hospital emergency room, was also found to be safe and effective. When patients present to emergency rooms with heart attack symptoms, doctors assess them in part by using a cardiac troponin test to measure a protein released into the blood when the heart is damaged.
> “We did not miss any heart attacks using this test in this population,” said lead author Rebecca Vigen, M.D., M.S.C.S., a cardiologist at the University of Texas Southwestern Medical Center. “The test also allowed us to determine faster that many patients who had symptoms of a heart attack were not having a heart attack than if we had relied on the traditional test.”
I would even advocate for this test being administered by EMTs and other first responders, instead of waiting until the patient arrives at the ER.
> Put another way, a heart attack patient dies in the ER about 11.9 percent of the time overall—but the research team found women with heart attacks will die about 12.4 percent of the time if their cases are handled by male doctors.
Isn't this a very dangerous headline? A 0.5% difference?
What are your thoughts on this
Isn't this a very dangerous headline? A 0.5% difference?
What are your thoughts on this
In addition to a tendency towards arrogance, doctors hold unconscious biases like everyone. Unsurprising.
Anecdotally, I recently had a same-gender doctor recount his glory day (just one day) in the ER solving a hypertensive crisis by syringe bloodletting onto the floor and tell me that my autonomic dysreflexia was “all in my head,” and that fixing stress was the panacea. Meanwhile myoclonus, nystagmus, anhedonia, (autoimmune?) inflammation/swelling, tremors keep getting worse. Thanks doc, you really solved everything.
Anecdotally, I recently had a same-gender doctor recount his glory day (just one day) in the ER solving a hypertensive crisis by syringe bloodletting onto the floor and tell me that my autonomic dysreflexia was “all in my head,” and that fixing stress was the panacea. Meanwhile myoclonus, nystagmus, anhedonia, (autoimmune?) inflammation/swelling, tremors keep getting worse. Thanks doc, you really solved everything.
Patients also hold unconscious biases. Perhaps patients, especially women, are more equivocal in their accounts when talking to male doctors.
FTA> There have definitely been several studies that have shown that women are slower to be diagnosed, and that might be explained by the fact that women are more likely to have ‘atypical’ symptoms
Also FTA> Female doctors are more likely to speak with their patients longer and provide more evidence-based care than their male colleagues... This could help them to pick up on heart attacks, even if women have more atypical symptoms.
Seems like women have a naturally higher likelihood of dying from heart attack. This is offset by a higher likelihood of methodical individual care (perhaps at cost of speed) if the doctor happens to be female.
Also FTA> Female doctors are more likely to speak with their patients longer and provide more evidence-based care than their male colleagues... This could help them to pick up on heart attacks, even if women have more atypical symptoms.
Seems like women have a naturally higher likelihood of dying from heart attack. This is offset by a higher likelihood of methodical individual care (perhaps at cost of speed) if the doctor happens to be female.
>This is offset by a higher likelihood of methodical individual care (perhaps at cost of speed) if the doctor happens to be female.
Then why wouldn't the female doctors provide better care for the men as well? The study concluded that the female-female match was better off, not that women were better doctors than men overall.
Then why wouldn't the female doctors provide better care for the men as well? The study concluded that the female-female match was better off, not that women were better doctors than men overall.
Because heart attacks in men are typically more straightforward to diagnose. In women they often require additional diagnostic effort, which coincidentally female doctors are more likely to undertake.
I can't help reading this article, thinking that if you were to swap "male" for "female" and vice versa, this would be an absolute scandal that would trigger a twitter mob and get the author fired for being sexist.
If you change the words, you change the meaning.
Let's try and get to the bottom of why the swapped version is meaningfully different. What makes "men" and "women" fundamentally different in this context, so much so that they can't be exchanged without significantly altering the effect of the headline?
Let's try and get to the bottom of why the swapped version is meaningfully different. What makes "men" and "women" fundamentally different in this context, so much so that they can't be exchanged without significantly altering the effect of the headline?
The author is basically implying that men are worse at that profession than females because of their natural behavior. Isn't it exactly the sort of arguments that got that google guy fired?
What what?
That's what you took away from the article?
That's what you took away from the article?
Quoting the article:
> Female doctors may also simply be performing at least some parts of the job better than their male counterparts do
Imagine writing the vice versa about any other profession.
> Female doctors may also simply be performing at least some parts of the job better than their male counterparts do
Imagine writing the vice versa about any other profession.
That's the point I'm trying to make. You instinctively feel that the exchanged version isn't the same. That the exchanged version isn't kosher. Now try and figure out why.
You are already halfway there.
I am implying that suggesting these days that men are intrinsically better at one profession than women would get someone fired.
> Now try and figure out why. You are already halfway there.
You can keep your condescension for yourself.
> Now try and figure out why. You are already halfway there.
You can keep your condescension for yourself.
nautilus12(1)
The article states that 3 out of four ER doctors are male.
So, out of 50% of 75% of the sample, they found a very slim, close to noise, discrepancy.
They are not focusing on a very strict group, they are simply taking 60% of the group and comparing it to the rest 40%. A small discrepancy in the data is obviously expected, even on large samples.
The article's author even has the courage of saying that the lack os women working as ER doctors is a sign of a lack of gender equality on medicine. Cmon now. Women make up a larger percentage of medicine graduates over the whole western world. Maybe they simply would prefer to work on less stressful environments than ER and it's not a matter of prejudice?
PC took over the world. Idiocracy is already a reality.
So, out of 50% of 75% of the sample, they found a very slim, close to noise, discrepancy.
They are not focusing on a very strict group, they are simply taking 60% of the group and comparing it to the rest 40%. A small discrepancy in the data is obviously expected, even on large samples.
The article's author even has the courage of saying that the lack os women working as ER doctors is a sign of a lack of gender equality on medicine. Cmon now. Women make up a larger percentage of medicine graduates over the whole western world. Maybe they simply would prefer to work on less stressful environments than ER and it's not a matter of prejudice?
PC took over the world. Idiocracy is already a reality.
If you're going to post in this thread, please do so according to the guidelines. Eschew flamebait especially.
https://news.ycombinator.com/newsguidelines.html
https://news.ycombinator.com/newsguidelines.html
There's really not much you can do with this without more investigation.
For example, what about ages? Are male doctors more likely to be older and it's actually a generational effect, say, of not listening? Or to the contrary, are male doctors more likely to be older and more experienced, and riskier female cases are sent to them disproportionately out of some bias towards extra care? If a male has more female colleagues, does this affect his behavior or is this simply because they tend to be better-run institutions in general which already seek to be more diverse?
It feels like there are a million ways it could be sliced, and while I'd totally buy the "men without the influence of women tend to not listen to women or pay as much attention to them" if that were backed up causally... it also seems like it's jumping to a click-baity conclusion whose causality is completely unsubstantiated. (No mention that they also measured how much a patient felt listened to, for example.)
For example, what about ages? Are male doctors more likely to be older and it's actually a generational effect, say, of not listening? Or to the contrary, are male doctors more likely to be older and more experienced, and riskier female cases are sent to them disproportionately out of some bias towards extra care? If a male has more female colleagues, does this affect his behavior or is this simply because they tend to be better-run institutions in general which already seek to be more diverse?
It feels like there are a million ways it could be sliced, and while I'd totally buy the "men without the influence of women tend to not listen to women or pay as much attention to them" if that were backed up causally... it also seems like it's jumping to a click-baity conclusion whose causality is completely unsubstantiated. (No mention that they also measured how much a patient felt listened to, for example.)
Ed Yong at the Atlantic looked into that:
"These differences persisted even after the team accounted for factors like the doctors’ years of experience and the patients’ age, ethnicity, other diseases, educational level, or the hospitals to which they were admitted."
https://www.theatlantic.com/science/archive/2018/08/women-mo...
"These differences persisted even after the team accounted for factors like the doctors’ years of experience and the patients’ age, ethnicity, other diseases, educational level, or the hospitals to which they were admitted."
https://www.theatlantic.com/science/archive/2018/08/women-mo...
Years of experience isn't the only way to measure skill. There are software engineers with 20 years experience that aren't as good as one with 2 years experience. I'd like to see the skill levels of the doctors normalized by something else, like whether they can somehow be identified as part of a group that specializes in high risk cases.
Isn't this Ageism? There are tons of 20-year experience engineers who are better than 2-year experience engineers. Yes, there are outliers, as with any normalized population, but typically years of experience in a skilled field correlates with ability to do the job well.
The person above wrote that there exists in a subset of engineers that have 20 years of experience, a group of engineers that are not better than engineers in a subset that have 2 years of experience
It was offering perspective, not a blanket statement about the entire set
That isn't ageism.
It was offering perspective, not a blanket statement about the entire set
That isn't ageism.
Again, there are outliers in a normalized population. Assuming that it's an entire subset without evidence is bias, i.e. ageism.
Simply being a perspective doesn't shield it from being biased.
Simply being a perspective doesn't shield it from being biased.
What form of evidence would you like?
I don't see the difference with the exact opposite of the statement (ie. that some engineers with more work experience are in fact better than others with less work experience), aside from the potential novelty. How would you prove that statement, so that someone else could prove the opposite. Are you saying that in outliers shouldn't be considered at all, when they are in fact a subset of a population? If so then you missed the point that someone above was talking about outliers and that was the only observation made.
Alternatively, is your stance that there is no difference to claim something is ageism if it is directed at an older population or a younger population? that noticing that older experienced engineers would also fit the criteria for ageism against a younger population making this whole conversation moot?
I don't see the difference with the exact opposite of the statement (ie. that some engineers with more work experience are in fact better than others with less work experience), aside from the potential novelty. How would you prove that statement, so that someone else could prove the opposite. Are you saying that in outliers shouldn't be considered at all, when they are in fact a subset of a population? If so then you missed the point that someone above was talking about outliers and that was the only observation made.
Alternatively, is your stance that there is no difference to claim something is ageism if it is directed at an older population or a younger population? that noticing that older experienced engineers would also fit the criteria for ageism against a younger population making this whole conversation moot?
How is that ageism? Being experienced simply does not equate to being skilled. It is correlated but some people, irrespective of age or experience, just aren't as good at $task than other people.
It's just as ageist to assume that a young person doesn't know anything
I spoke to a doctor about publishing statistics and the major concern with him and his peers was exactly what you mentioned. Riskier cases will make your statistics drop, but the more experienced doctors would almost always get the most difficult cases.
I wonder what the doctor thinks of publishing risk adjusted statistics. That is, publishing the difference between expected and actual outcome.
That's not true ... after all, that would mean putting MBA type managers in charge of hospitals (like is being done all across the US) is going to lead to disastrously bad decisions as they will institute individual incentives. Giving those experienced doctors little choice : either refuse cases that might die ... or get fired.
Right, which is why some experienced doctors can be overly conservative. The ones that take up the hard cases are therefore penalized even more.
You see the same thing with lawyers. The ones with a 100% trial success rate are very choosy about which cases they accept or are more inclined to pressure clients to settle.
The phenomenon is real. Whether it exists at the heart of this study or is simply being used to excuse underperforming doctors....
You see the same thing with lawyers. The ones with a 100% trial success rate are very choosy about which cases they accept or are more inclined to pressure clients to settle.
The phenomenon is real. Whether it exists at the heart of this study or is simply being used to excuse underperforming doctors....
That's sarcasm, right? Because that's what has happened, and been happening while healthcare in the US is treated as a for-profit enterprise.
I’d also posit that female ER doctors could as a group, simply be better than the average male.
Not inherent to their gender, but because they are a more motivated group to overcome the systemic bias in medicine to get there.
If you get to 50/50 this would mean the stats converge, but the same findings would need to be repeated across other conditions as well.
Not inherent to their gender, but because they are a more motivated group to overcome the systemic bias in medicine to get there.
If you get to 50/50 this would mean the stats converge, but the same findings would need to be repeated across other conditions as well.
Then we would've seen the same trend with female doctors treating male patients.
Not necessarily. It could be that only good doctors treat female patients well, while all doctors treat male patients well. For example, if women patients are in some way harder cases while male patients are not, then treatment of women patients may separate good doctors from the rest.
Alternatively, women patients speak differently to male doctors in ways that make it more difficult to make accurate and reliable diagnoses.
Educated professionals are certainly capable of exhibiting bias. But professionals are also more aware of the issue, and are even taught (formally and informally) compensating strategies. People off the street? Not so much....
Educated professionals are certainly capable of exhibiting bias. But professionals are also more aware of the issue, and are even taught (formally and informally) compensating strategies. People off the street? Not so much....
OR just that female doctors paid more attention to the fact that heart attack symptoms are different for women than for men. This may be as simple as it affecting them. If the male takes longer to recognise heart attack symptoms of females, it could easily produce worse results.
https://www.healthline.com/health/heart-disease/heart-attack...
https://www.healthline.com/health/heart-disease/heart-attack...
Maybe we have?
The article says "the other differences were not significant", but that does not mean there was no difference. It means "there was not enough evidence to reject the assumption that there were no other differences". That's one problem with this kind of statistics: absence of evidence is not evidence of absence, but people (including head line writers) act as if it was.
The article says "the other differences were not significant", but that does not mean there was no difference. It means "there was not enough evidence to reject the assumption that there were no other differences". That's one problem with this kind of statistics: absence of evidence is not evidence of absence, but people (including head line writers) act as if it was.
I have noticed the same thing in tech. Only the healthiest orgs I been at have had women clustered around the median, most are at least a std deviation above the median.
Here is a link to far more specific data from the main study in the article. I suggest people look over the data themselves.
http://www.pnas.org/content/pnas/suppl/2018/07/31/1800097115...
The data appears to not be in the friendliest of formats (tables with an axis labeled 'X'? No way my professors would've let that slide).
http://www.pnas.org/content/pnas/suppl/2018/07/31/1800097115...
The data appears to not be in the friendliest of formats (tables with an axis labeled 'X'? No way my professors would've let that slide).
Thanks for the link. With that paper in hand, I can say confidently that the Scientific American article is a flat out lie, starting from the headline.
Chart S1 plots the distribution of the predicted probability for survival in four conditions. The distributions for "Male Doc, Female Patient" and "Female Doc, Female Patient" are visually indistinguishable and peak at around 0.96. "Female Doc, Male Patient" peaks at around 0.97, "Male Doc, Male Patient" at 0.98 or so. The difference in the position of the maximum is real, but tiny; the distributions for female patients are much wider (which visually exaggerates the difference). The math seems to agree with my reading, as it says: "when physician gender (male / female) is regressed upon (ŷ), conditional upon controls, there is no significant correlation between ex ante probability of survival and the gender of the physician."
So, dear "Scientific American": It is completely untrue that "Women Die More from Heart Attacks Than Men—Unless the ER Doc Is Female". The data says that "Women Die More from Heart Attacks Than Men—No Matter Who Treats Them" and that "Men Die More from Heart Attacks Than Other Men—When the ER Doc Is Female"
No thanks for turning a study that found tiny differences into a politically charged statement.
But then why would Brad Greenwood, the author of the study, state that "All of those are statistically indistinguishable except for male doctor–female patient", when it's obvious to the naked eye that there are other difference? I guess one difference made it over the arbitrary threshold of significance, and others didn't. That's just the nature of SHIT (Statistical Hypothesis Inference Testing).
Chart S1 plots the distribution of the predicted probability for survival in four conditions. The distributions for "Male Doc, Female Patient" and "Female Doc, Female Patient" are visually indistinguishable and peak at around 0.96. "Female Doc, Male Patient" peaks at around 0.97, "Male Doc, Male Patient" at 0.98 or so. The difference in the position of the maximum is real, but tiny; the distributions for female patients are much wider (which visually exaggerates the difference). The math seems to agree with my reading, as it says: "when physician gender (male / female) is regressed upon (ŷ), conditional upon controls, there is no significant correlation between ex ante probability of survival and the gender of the physician."
So, dear "Scientific American": It is completely untrue that "Women Die More from Heart Attacks Than Men—Unless the ER Doc Is Female". The data says that "Women Die More from Heart Attacks Than Men—No Matter Who Treats Them" and that "Men Die More from Heart Attacks Than Other Men—When the ER Doc Is Female"
No thanks for turning a study that found tiny differences into a politically charged statement.
But then why would Brad Greenwood, the author of the study, state that "All of those are statistically indistinguishable except for male doctor–female patient", when it's obvious to the naked eye that there are other difference? I guess one difference made it over the arbitrary threshold of significance, and others didn't. That's just the nature of SHIT (Statistical Hypothesis Inference Testing).
There's also a mis-labled column in table S2. Which one is Female Doctors Male Patients?
In the table it also specifies which is male and which is female.
The third column (according to the top rows of the table).
I'd also like to see if the female doctors simply follow the checklist better than male doctors.
ER outcomes have been shown over and over to improve when there is a checklist available and followed.
ER outcomes have been shown over and over to improve when there is a checklist available and followed.
That would only apply if we saw the same trend with female doctors treating male patients.
> The researchers divided 500,000-plus cases into four categories: male doctors treating men; male doctors treating women; female doctors treating men; and female doctors treating women. “All of those are statistically indistinguishable except for male doctor–female patient,” says Brad Greenwood
> The researchers divided 500,000-plus cases into four categories: male doctors treating men; male doctors treating women; female doctors treating men; and female doctors treating women. “All of those are statistically indistinguishable except for male doctor–female patient,” says Brad Greenwood
The article mentions that women are more likely to present with "atypical" symptoms (which actually may be typical for women). Maybe almost all men present with "typical" symptoms or female doctors are more diligent about checking women for "atypical" symptoms.
FYI, just because effect A is statistically distinguishable from zero and effect B is not statistically distinguishable from zero, that does not imply effect A is statistically distinguishable from effect B.
It could still be the case that female doctors are better overall, even if it was only distinguishable from zero in a single branch.
(I looked at paper myself but am not confident I can interpret it correctly.)
It could still be the case that female doctors are better overall, even if it was only distinguishable from zero in a single branch.
(I looked at paper myself but am not confident I can interpret it correctly.)
learnstats2(5)
The article to me seems to be pushing a specific viewpoint which is essentially jumping to a conclusion that male doctors treat women patients poorly.
Without context these numbers don’t mean anything. There could be many factors why these statistics exist - are older / more severe female cases more likely to see a male doctor? As an example.
I really dislike this being presented as news and having all sorts of negative connotations towards men. It’s a finding that requires more investigation and is meaningless without context.
Without context these numbers don’t mean anything. There could be many factors why these statistics exist - are older / more severe female cases more likely to see a male doctor? As an example.
I really dislike this being presented as news and having all sorts of negative connotations towards men. It’s a finding that requires more investigation and is meaningless without context.
There are numbers, linked to in the article: http://www.pnas.org/content/early/2018/07/31/1800097115
Well, diagnosis relies on hard data and empathy. It is a personal observation of mine (male) that women have general higher empathy.
For medicine in particular, female biology forces you to experience symptoms and treatments earlier, more often (male teenagers do not experience menstruation and OB/GYN visits, to spell it out).
I can absolutely see how this shapes behavior.
A lot of patients complain about western medicines inhuman conveyor belt methods, which plays into this. Diagnosis practices in TCM are wondrous in comparison (male and female!).
For medicine in particular, female biology forces you to experience symptoms and treatments earlier, more often (male teenagers do not experience menstruation and OB/GYN visits, to spell it out).
I can absolutely see how this shapes behavior.
A lot of patients complain about western medicines inhuman conveyor belt methods, which plays into this. Diagnosis practices in TCM are wondrous in comparison (male and female!).
I fail to see how your comment supports the claims in the article. If what you say is true than the results would be that in general female doctors are better but this data shows that they are only better with other female patients.
What I really wanted to understand about this study: (1) whether they accounted for the number of years out of residency the physician was, and (2) whether they accounted for cumulative physician experience in some more rigorous way. I skimmed and searched with keywords rather than reading exhaustively, but I don't see a good description of these features.
Re: (1), if the guidelines are correct and effective, I would expect women to score better because of the probability density of older men. That is, the average woman is younger and "closer to the data".
Re: (2), if experience is helpful, I would expect those with more experience to do better.
A priori, the person least likely to do well is a person who is far out from residency but who hasn't practiced a bunch. That person is more likely to be male than female (based on the above, basically, the historical consequence of systematic discrimination against women in medicine), and is less likely to have been trained to recognize symptoms uncommon in men.
In their tables, they describe "Physician experience control." I don't see a rigorous definition of this. They have a section in the supplement on variable definitions where they do not describe this. What does this mean? From Table S2, you can see that the men have accrued a mean of ~14 physician experience points, while women have accrued a ~mean of 10, a tremendous difference at this sample size. Does this score refer to (1) or does it refer to (2)? If it refers to (1), then I'm not surprised that men do worse. If it refers to (2), then this is all the more surprising.
Supplementary Table S2 also has incorrect labels (they seem to have duplicated female-physician / female-patient and left out the female-physician / male-patient). More confusingly, in the male-physician / male-patient section, the label appears to say that 10% of the male physicians are female. That can't be what they mean - but can anyone else interpret this? Edit -- I think this is referring to the average physician at that hospital. Not well named in the supplement, but that's OK.
Finally, 25% of their data is with physicians with names that preclude gender assignment by their algorithm. If we assume that to be a mix of men and women, that group should perform somewhere between the male and female physicians. Why exclude this data from the analysis, rather than analyze it to confirm the trend?
Study is here: http://www.pnas.org/content/pnas/early/2018/07/31/1800097115...
Supplement is here: http://www.pnas.org/content/pnas/suppl/2018/07/31/1800097115...
Re: (1), if the guidelines are correct and effective, I would expect women to score better because of the probability density of older men. That is, the average woman is younger and "closer to the data".
Re: (2), if experience is helpful, I would expect those with more experience to do better.
A priori, the person least likely to do well is a person who is far out from residency but who hasn't practiced a bunch. That person is more likely to be male than female (based on the above, basically, the historical consequence of systematic discrimination against women in medicine), and is less likely to have been trained to recognize symptoms uncommon in men.
In their tables, they describe "Physician experience control." I don't see a rigorous definition of this. They have a section in the supplement on variable definitions where they do not describe this. What does this mean? From Table S2, you can see that the men have accrued a mean of ~14 physician experience points, while women have accrued a ~mean of 10, a tremendous difference at this sample size. Does this score refer to (1) or does it refer to (2)? If it refers to (1), then I'm not surprised that men do worse. If it refers to (2), then this is all the more surprising.
Supplementary Table S2 also has incorrect labels (they seem to have duplicated female-physician / female-patient and left out the female-physician / male-patient). More confusingly, in the male-physician / male-patient section, the label appears to say that 10% of the male physicians are female. That can't be what they mean - but can anyone else interpret this? Edit -- I think this is referring to the average physician at that hospital. Not well named in the supplement, but that's OK.
Finally, 25% of their data is with physicians with names that preclude gender assignment by their algorithm. If we assume that to be a mix of men and women, that group should perform somewhere between the male and female physicians. Why exclude this data from the analysis, rather than analyze it to confirm the trend?
Study is here: http://www.pnas.org/content/pnas/early/2018/07/31/1800097115...
Supplement is here: http://www.pnas.org/content/pnas/suppl/2018/07/31/1800097115...
> Finally, 25% of their data is with physicians with names that preclude gender assignment by their algorithm. If we assume that to be a mix of men and women, that group should perform somewhere between the male and female physicians. Why exclude this data from the analysis, rather than analyze it to confirm the trend?
I think leaving that out makes a lot of sense actually. You can't assume that the mix is 50-50 just because you don't know the data. Anecdotally, I know more women who use a male or gender-agnostic version of their name professionally than I do men. It may be more common in fields other than medicine, but for example we only know "JK Rowling" as "JK" because her publishers were worried that having an author with a feminine name would make it harder to sell the book to boys.
I think leaving that out makes a lot of sense actually. You can't assume that the mix is 50-50 just because you don't know the data. Anecdotally, I know more women who use a male or gender-agnostic version of their name professionally than I do men. It may be more common in fields other than medicine, but for example we only know "JK Rowling" as "JK" because her publishers were worried that having an author with a feminine name would make it harder to sell the book to boys.
> You can't assume that the mix is 50-50
I don't assume that it's a 50/50 split. I assume it's somewhere between 0% female to 100% female. And it's a big sample. If a mix of (men and women) doesn't perform somewhere between the all-male and all-female groups, that's a big problem with their hypothesis.
They're saying something equivalent to Group A scores mean 90 and Group B scores mean 95. If you then take a very large set of people that is drawn from Group A and Group B with an unknown proportion and they score mean 85 or 100, that would be fairly devastating to the claim.
I'm not saying that this should be weighted into the main analysis. I'm saying they should test their hypothesis with this.
I don't assume that it's a 50/50 split. I assume it's somewhere between 0% female to 100% female. And it's a big sample. If a mix of (men and women) doesn't perform somewhere between the all-male and all-female groups, that's a big problem with their hypothesis.
They're saying something equivalent to Group A scores mean 90 and Group B scores mean 95. If you then take a very large set of people that is drawn from Group A and Group B with an unknown proportion and they score mean 85 or 100, that would be fairly devastating to the claim.
I'm not saying that this should be weighted into the main analysis. I'm saying they should test their hypothesis with this.
Since you don't know the relative mix, including those 25% adds another nuisance parameter but not that much more statistical power, so why bother?
> I'm not saying that this should be weighted into the main analysis. I'm saying they should test their hypothesis with this.
TL;DR
The researchers divided 500,000-plus cases into four categories:
male doctors treating men;
male doctors treating women;
female doctors treating men;
and female doctors treating women.
“All of those are statistically indistinguishable except for male doctor–female patient,”There was more than that. There was the match and the non-match division, and there was the case where they couldn't determine the gender of the Physician. Also, some of the data doesn't look exactly indistinguishable.
Look at Fig.S2 here http://www.pnas.org/content/pnas/suppl/2018/07/31/1800097115...
It looks like male and female doctors result in the same probability curve for female patients, but male doctors result in a higher probability curve for male patients.
Look at Fig.S2 here http://www.pnas.org/content/pnas/suppl/2018/07/31/1800097115...
It looks like male and female doctors result in the same probability curve for female patients, but male doctors result in a higher probability curve for male patients.
There is a lot of assumptions made in this article, and it's interesting that we never see publications on the superior performance of male surgeons ETC. I guess those facts would be offensive to some though.
Here is the most likely reason for this statistic. (Of you can call it that since it is objectively statistically insignificant, being that male doctors treated 150X more women overall).
The male doctors are better doctors (all factors such as age and experience being the same), and its well documented that they can handle higher stress levels and make Less emotionally influenced mistakes. So they get the tougher cases to begin with. This is a plausible of an argument as any in the article or mentioned here.
Is funny that those who fight gender biases the most are some of the most biased.
Here is the most likely reason for this statistic. (Of you can call it that since it is objectively statistically insignificant, being that male doctors treated 150X more women overall).
The male doctors are better doctors (all factors such as age and experience being the same), and its well documented that they can handle higher stress levels and make Less emotionally influenced mistakes. So they get the tougher cases to begin with. This is a plausible of an argument as any in the article or mentioned here.
Is funny that those who fight gender biases the most are some of the most biased.
So they get the tougher cases to begin with.
Do you have evidence that this happens in the ER? When my wife did her ER rotation it wasn't like this.
We have a study that shows women with heart attacks do worse in ERs unless they are treated by a female doctor. You are presenting facts (without attribution) about surgeons. ER doctors are not surgeons. So what evidence do you have from the ER that contradicts the apparent conclusion of the study?
Is funny that those who fight gender biases the most are some of the most biased.
It's quite ironic that you wrote the above sentence given your post. The only evidence you provide is about surgeons and conclude that male superiority in medicine is the most likely reason for the statistics in the study. That is quite a stretch there.
Do you have evidence that this happens in the ER? When my wife did her ER rotation it wasn't like this.
We have a study that shows women with heart attacks do worse in ERs unless they are treated by a female doctor. You are presenting facts (without attribution) about surgeons. ER doctors are not surgeons. So what evidence do you have from the ER that contradicts the apparent conclusion of the study?
Is funny that those who fight gender biases the most are some of the most biased.
It's quite ironic that you wrote the above sentence given your post. The only evidence you provide is about surgeons and conclude that male superiority in medicine is the most likely reason for the statistics in the study. That is quite a stretch there.
Thanks, it's meant to be ironic. There are only guesses all around based on a numbers with a similar ratio of 5 cases for women physicians and 700 for men. How can this be considered serious reporting? If the numbers favored men, we wouldn't be having this conversation for a number of reasons.
There hasn't been thousands of years of gender bias in favor of women so it's expected that results that show men are better than women in some areas are not necessarily newsworthy. Sometimes such results are newsworthy.
You miss my point. No statistician worth his salt would ever consider these numbers relevant, Yet here it it's all over the news. Why the over compensation for women? A whole story making women out to be superior to men in some way with trash to back it up. Why? If women are capable, give them props. Don't make up stuff based on horrible data.
If the numbers favored men, we wouldn't be having this conversation for a number of reasons.
I think you missed my point. I was responding solely to the above quote that you made.
I think you missed my point. I was responding solely to the above quote that you made.
>So [men] get the tougher cases to begin with.
This argument has come up several times here as though it is an obvious possibility, but I have significant reason to doubt it.
In politics, it is known that women end up being given statistically riskier elections to defend - i.e. those that are the most critical ones for a political party, while also offering individuals less secure career prospects.
Why, then, is it assumed that the exact opposite must be true in medicine?
This argument has come up several times here as though it is an obvious possibility, but I have significant reason to doubt it.
In politics, it is known that women end up being given statistically riskier elections to defend - i.e. those that are the most critical ones for a political party, while also offering individuals less secure career prospects.
Why, then, is it assumed that the exact opposite must be true in medicine?
How can we begin comparing political strategy to sub minute life and death medical decisions? I am confused, or missing your point.
“And its well documented that they can handle higher stress levels and make Less emotionally influenced mistakes.”
Can we see some of this documentation, please?
Can we see some of this documentation, please?
There have been countless studies. Mostly by the military. Google it. Of course those studies were all biased so I can't expect you to believe them.
Since you are making the assertion that this is well documented, surely you would be able to provide links on your own? I’m interested in what evidence you are basing your argument on.
What do you think will come from your posting this here? I know men are stereotypically more prone to taking action that has an uncertain payoff, but this is (if I may be so bold) ridiculous.
Its completely relevant and my original guess explaining this unlikely variance may actually be factual. The stress coping capabilities of a physician is one of the largest predictors of proper patient treatment in the ER
We detached this subthread from https://news.ycombinator.com/item?id=17701593.
[deleted]
Once upon a time, mortality rate of the pregnant women were higher at the male doctor than the traditional female midwife.
Some people try to explain that statistics with a hypothesis that the presence of male doctor stress the pregnant women.
The real reason was, male doctor at that time treat pregnant woman immediately after they perform the dissection WITHOUT washing their hands! Killing pregnant women by infection.
Some people try to explain that statistics with a hypothesis that the presence of male doctor stress the pregnant women.
The real reason was, male doctor at that time treat pregnant woman immediately after they perform the dissection WITHOUT washing their hands! Killing pregnant women by infection.
“Spurious signals sometimes come up [in research], so this should be replicated”
As the replication crisis becomes more apparent, if you are looking to fill your mind with true facts in sociology, psychology or health, replication should be the bare minimum before even spending time to decide if a study's conclusions are likely to be true.
As the replication crisis becomes more apparent, if you are looking to fill your mind with true facts in sociology, psychology or health, replication should be the bare minimum before even spending time to decide if a study's conclusions are likely to be true.
It's important to note that men are also more likely to survive if the ER doc is female.
Thanks to the person who linked to the original data. In the table S2, it lists the standard deviations for a lot of the measures, including survival. Lots of other interesting stuff there in that table. I totally believe that there are good reasons to have more women doctors, and I'd advise looking at the article itself rather than Scientific American's summary, which is not the greatest.
Oh geez I forgot to post the link myself so you don't have to find it in another thread: http://www.pnas.org/content/pnas/suppl/2018/07/31/1800097115...
...and there it is, right in table S4, a p-test just barely under the old 0.05 threshold (0.0468).
In addition to differences in doctor competence and behavior, perhaps the female patients behaved differently when treated by a male doctor.
There's a typo that appears twice in the appendix where both 'female physician/female patient' and 'female physician/male patient' were labeled female/female in both Table S2 and Table S3.
Also interesting are the raw numbers from Table S2 of patient survival:
These numbers are obviously too broad to tell the whole story but if you trained the male doctors to have the same male-to-female patient mortality drop as female doctors, that still leaves 3/4 of the male doctor male-to-female patient mortality difference untouched. That is unless you throw out the .888->.866 drop, which they apparently did, and I wish I had the whole paper in front of me right now to figure out why.
It looks to me like there might be more productive questions to answer here: Why are female doctors outperforming male doctors in this area? Why are female patients (ballpark) twice as sensitive to the gender of their doctor?
source: http://www.pnas.org/content/pnas/suppl/2018/07/31/1800097115...
Also interesting are the raw numbers from Table S2 of patient survival:
Female Dr. Male Dr.
Female Patient 0.866 0.854
Male Patient 0.888 0.883
These numbers are obviously too broad to tell the whole story but if you trained the male doctors to have the same male-to-female patient mortality drop as female doctors, that still leaves 3/4 of the male doctor male-to-female patient mortality difference untouched. That is unless you throw out the .888->.866 drop, which they apparently did, and I wish I had the whole paper in front of me right now to figure out why.
It looks to me like there might be more productive questions to answer here: Why are female doctors outperforming male doctors in this area? Why are female patients (ballpark) twice as sensitive to the gender of their doctor?
source: http://www.pnas.org/content/pnas/suppl/2018/07/31/1800097115...
Somebody with more expertise than me needs to chime in here.
If you take the data from Table S2 and perform a two-sample binomial test (as seen here[0] and at 3 minutes here[1]) you can directly contradict a statement in the paper's abstract ("Male patients and female patients experience similar outcomes when treated by female physicians") Using the female doctor numbers I get a z-value of 8.36 which is well over the standard two-tailed significance value of 1.96 for p<0.05. With N being so large it looks like the gender of the patient is absolutely statistically significant with female doctors as well as male.
I feel like I must be missing something here but I'm such a beginner with statistics that I don't know what it is. Is it not a binomial distribution, is it not normally distributed? Am I plugging my numbers in wrong?
[0] - https://stats.stackexchange.com/questions/113602/test-if-two... [1] - https://www.coursera.org/lecture/biostatistics-2/two-sample-...
If you take the data from Table S2 and perform a two-sample binomial test (as seen here[0] and at 3 minutes here[1]) you can directly contradict a statement in the paper's abstract ("Male patients and female patients experience similar outcomes when treated by female physicians") Using the female doctor numbers I get a z-value of 8.36 which is well over the standard two-tailed significance value of 1.96 for p<0.05. With N being so large it looks like the gender of the patient is absolutely statistically significant with female doctors as well as male.
I feel like I must be missing something here but I'm such a beginner with statistics that I don't know what it is. Is it not a binomial distribution, is it not normally distributed? Am I plugging my numbers in wrong?
[0] - https://stats.stackexchange.com/questions/113602/test-if-two... [1] - https://www.coursera.org/lecture/biostatistics-2/two-sample-...
I'd guess that male doctors are a bit more protective of female patients thus letting them stay too long in the hospital hindering rehabilitation.