Race and gender should be inputs then.
The female part is actually a bit more surprising. Its easy to imagine a dataset not skewed towards black people. ~15% of the population in North America, probably less in Europe, and way less in Asia. But female? Thats ~52% globally.
Surprising? That's not a new realisation. It's a well known fact that women are affected by this in medicine. You can do a cursory search for the gender gap in medicine and get an endless amount of reporting on that topic.
I learned about this recently! It's wild how big the difference is. Even though legal/practical barriers to gender equality in medicine and data collection have been virtually nonexistent for the past few decades the inertia from the decades before that (where women were often specifically excluded, among many other factors) still weigh heavily.
To any women who happen to be reading this: if you can, please help fix this! Participate in studies, share your data when appropriate. If you see how a process can be improved to be more inclusive then please let it be known. Any (reasonable) male knows this is an issue and wants to see it fixed but it's not clear what should be done.
Race and sex should be inputs. Giving any medical prominence to gender identity will result in people receiving wrong and potentially harmful treatment, or lack of treatment.
Most trans people have undergone gender affirming medical care. A trans man who has had a hysterectomy and is on testosterone will have a very different medical baseline than a cis woman. A trans woman who has had an orchiectomy and is on estrogen will have a very different medical baseline than a cis man. It is literally throwing out relevant medical information to attempt to ignore this.
How is that in any way in conflict with what he said? You're just making an argument for more inputs.
Biological sex, hormone levels, etc.
The GP literally said “giving any medical prominence to gender identity will result in people receiving wrong and potentially harmful treatment” which is categorically false for the reasons the comment you replied to outlined.
Sex assigned at birth is in many situations important medical information; the vast majority of trans people are very conscious of their health in this sense and happy to share that with their doctor.
>Sex assigned at birth is in many situations important medical information
Which is not gender identity. As a result of being trans there may be things like hormone levels that are different than what you'd expect based on biological sex, which is why I say hormone levels are important, but how you identify is in fact irrelevant.
Well, this is clearly wrong – it's obvious, for example, that gender identity could have a significant impact on mental health.
Regardless of that, you seem to agree that:
- Sex assigned at birth is important medical information
- Information about gender affirming treatments is important medical information
So I don't think there's much to worry about there.
The problem is that over the past few decades there has been substantial conflation of sex and gender, with many information systems replacing the former with the latter, rather than augmenting data collection with the latter.
I think it's pretty clear to see how discrimination is the cause of that. Why would you volunteer information that from your point of view is more likely to cause a negative interaction than not?
In many places I'd seriously question the motives for asking about either in general. Do you really need gender info to write better targeted spam mails for your SaaS product?
>why I say hormone levels are important, but how you identify is in fact irrelevant
I don't understand what your issue with it is, it's just another point of data.
I don't want to be treated like a cis woman in a medical context, but I sure do want to be treated like a trans woman.
> hormone levels, etc.
Right… their gender they identify as.
So sex, and then also the gender they identify as.
You can’t hide behind an “etc”. Expand that out and the conclusion is you really do need to know who is trans and who is cisgender when doing treatment.
Seems like adding in gender only makes things less clear. The relevant information is sex and a medical history of specific surgeries and medications - the type of thing your doctor should already be aware of. Adding in gender only creates ambiguity because there's no way to measure gender from a biological perspective.
That’s mostly correct, that “gender identity” doesn’t matter for physical medicine. But hormone levels and actual internal organ sets matter a huge amount, more than genes or original genitalia, in general. There are of course genetically linked diseases, but there are people with XX chromosomes that are born with a penis, and XY people that are born with a vulva, and genetically linked diseases don’t care about external genitalia either way.
You simply can’t reduce it to birth sex assignment and that’s it, if you do, you will, as you say, end up with wrong and potentially harmful treatment, or lack of treatment.
>But hormone levels and actual internal organ sets matter a huge amount, more than genes or original genitalia
Or current genitalia for that matter. It's just a matter of the genitalia signifying other biological realities for 99.9% of people. For sure more info like average hormone levels or ranges over time would be more helpful.
Yeah, sure, and for most people it’s a fair enough proxy. But if it has to be boiled down to exactly one of “M” or “F”, then “birth sex” must not be the deciding factor. If it must be a single criteria, it should be current hormone levels, artificial or not. And, since most trans people who actually transition and live as their preferred gender identity are on hormones, “gender identity” is a good proxy for 99.99% of the population, including the set of people for who “birth genitalia” is also a good proxy. But ideally, it doesn’t get simplified this much in the first place. And of course, it doesn’t, in practice, because most people actually form a relationship with their doctor, and they treat holistically, based on individual factors, and not simply whether the medical record says M or F.
But, if we must over generalize, “gender identity” really is the most useful proxy, in fact, and it also happily happens to be quite inclusive too.
Of course this conversation started from a transphobic viewpoint, which doesn’t actually care about any of these distinctions anyways, regardless of the merit, it’s just someone being triggered about someone respecting someone else’s gender identity.
Actually both are important inputs, especially when someone has been taking hormones for a very long time. The human body changes greatly. Growing breast tissue increases the likelyhood of breast cancer, for example, compared to if you had never taken it (but about the same as if estradiol had been present during your initial puberty).
Modern medicine has long operated under the assumption that whatever makes sense in a male body also makes sense in a female body, and womens' health concerns were often dismissed, misdiagnosed or misunderstood in patriarchal society. Women were rarely even included in medical trials prior to 1993. As a result, there is simply a dearth of medical research directly relevant to women for models to even train on.
https://www.npr.org/2022/11/01/1133375223/the-first-female-c... Twenty Twenty Two!
Republicans early in this admin actually bitched in congress that we were "wasting" money on woman crash test dummies.
I'm going to lay this out how I understand it:
The NIH Revitalization Act of 1993 was supposed to bring women back into medical research. The reality was that women were always included, HOWEVER in 1977,(1) because of the outcomes from thalidomide (causing birth defects), "women of childbearing potential" were excluded from the phase 1, and early phase 2 trials (the highest risk trials). They're still generally generally excluded, even after the passage of the act. This was/is to protect the women, and potential children.
According to Edward E. Bartlett in his meta data analysis from 2001, men have been routinely under-represented in NIH data (even before adjusting for men's mortality rates) between 1966-1990. (2)
There's also routinely twice as much spent every year on women's health studies vs men's by the NIH. (3)
It makes sense to me, but I'm biased. Logically, since men lead in 9 of the top 10 causes for death, that shows there's something missing in the equation of research. (4 - It's not a straight forward table, you can view the total deaths, and causes and compare the two for men, and women)
With that being said, it doesn't tell us about the quality of the funding or research topics, maybe the money is going towards pointless goals, or unproductive researchers.
Are there gaps in research? Most definitely, like women who are pregnant. This is put in place to avoid harm but that doesn't help them when they fall into them. Are there more? Definitely. I'm not educated enough in the nuances to go into them.
If you have information that counters what I've posted, please share it, I would love know where these folks are blind so I can take a look at my bias.
(1) https://petrieflom.law.harvard.edu/2021/04/16/pregnant-clini... (2) https://journals.lww.com/epidem/fulltext/2001/09000/did_medi... (3) https://jameslnuzzo.substack.com/p/nih-funding-of-mens-and-w... < I spot checked a couple of the figures, and those lined up. I'm assuming the rest is accurate (4) https://www.cdc.gov/womens-health/lcod/index.html#:~:text=Ov...
> Its easy to imagine a dataset not skewed towards black people. ~15% of the population in North America, probably less in Europe, and way less in Asia.
What about Africa?
That's not where most of the data is coming from. If it was we'd be seeing the opposite effect, presumably.
The story is that there exists this model which poorly predicts for black (and female) patients. Given there are probably lots of datasets where black people are a vast minority makes this not surprising.
For all I know there are millions of models with extremely poor accuracy based on African datasets. Wouldnt really change anything about the above though. I wouldnt expect that though and it would definitely be interesting.
How much medical data/papers do you think they generate in comparison to these three ?
Why not socioeconomic status or place of residence? Knowing mean yearly income will absolutely help an AI figure out statistically likely health outcomes.