Elderly Cared For By Female Doctors Fare Better Than Those Treated By Men
npr.org
npr.org
For example, they exclude all data from ICU doctors because they're disproportionately men – suppose only the best doctors work in the ICU, by excluding that you're excluding more of the best male doctors than the best of the female doctors resulting in leaving a better population of women in your study.
They correct for illness but not for doctor specialty, perhaps females specialize in things that happen to have lower mortality rates.
... and on and on and on. There are so many variables to possibly correct for that a study like this (especially having skimmed it) is pretty much useless. It would be trivial to do a study like this and get whatever result you wanted. Just stop doing statistical corrections when you get the result you're looking for. P-value doesn't mean anything here because it doesn't capture the ways the study could be wrong.
The question is "in a given medical speciality -- internal medicine in this study --, are patient's outcomes related to the admitting physician sex?", not if women make better doctors than females. As such, your point about the best doctors not being in internal medicine is pretty a non sequitur.
Basically, I see two potential biais that could explain at least part of the difference in outcomes :
1. Its is "common knowledge" that male doctors tend to refuse admissions more often than females. (I am not aware of any hard data to prove this point) It could be that the patients that they do admit are somewhat sicker that those they let go directly home. That could explain both higher mortality and re-admission rates.
2. It is again, "common knowledge" (again, I'm not aware of any study) that women write better discharge summaries, including all co-morbid conditions. When coded in a database, those patients will appear sicker than similar ones treated by male doctors, and this could skew any analyses.
A final confounder is that patients often have many doctors during the stay, both male and female, and the study assigned as "the" doctor the one who billed most for the patient, which may not be the one who had the most impact on outcomes. It is difficult to say how this would advantage any particular sex, however.
If that data is true, then we should see a reversed result in other medical areas. It could be that if you wanted the best result of surgery, pick a male doctor. If you want the best result afterward, pick a female doctor.
http://khanism.org/society/created-equal/
It is important that this study is limited to elderly patients. It does use a lot of data though from many doctors and physicians, but only over the course of a 30 day window.
I'd like to see studies that do this with younger patients as well, as well as studies done over a longer timespam. If the same percentage present themselves, it be interesting to see if there was some kind of training or something that could be added to the medschool/education process to help male physicians implement the natural practices used by the female physicians to reduce the overall mortality rates.
If studies on younger patients or longer timespans show the percentages converging down to zero, than maybe this study was an isolated result from 30 days in that one facility and the differences aren't really statically significant. Studies like this really need to be reproduced.
The study covered significantly more than one facility. The data included nearly 60k physicians and over 1.6M patients.
This is why we need to focus on equality of opportunity, not equality of outcome.
To be clear, having connections to the Clinton's really is different than sitting in on meetings with foreign heads of state.
(I'm not sure I think that Ivanka having coffee with someone is problematic, but it's still different than a lobbyist doing it)
From the guidelines:
> please use the original title, unless it is misleading or linkbait.
We reverted the HN title to the article title. I'm not sure the absence of 'elderly' counts as misleading but s/patients/elderly/ is probably ok.
In my experience women tend to go to female doctors and given women live longer than men..
hey presto magico.. patients of women doctors live longer
> We accounted for patient characteristics, physician characteristics, and hospital fixed effects. Patient characteristics included patient age in 5-year increments (the oldest group was categorized as ≥95 years), sex, race/ethnicity (non-Hispanic white, non-Hispanic black, Hispanic, and other), primary diagnosis (Medicare Severity Diagnosis Related Group), 27 coexisting conditions (determined using the Elixhauser comorbidity index28), median annual household income estimated from residential zip codes (in deciles), an indicator variable for Medicaid coverage, and indicator variables for year. Physician characteristics included physician age in 5-year increments (the oldest group was categorized as ≥70 years), indicator variables for the medical schools from which the physicians graduated, and type of medical training (ie, allopathic vs osteopathic29 training).
They don't say _how_ they controlled for those characteristics though. Presumably, they divided each patient's calculated 30-day risk of death [1, table 10] by the relative ratios in risk of death of every category, calculated from the same data set. That should probably cut it for controlling for this particular difference, although I am not a statistician.
Paper link:
https://jamanetwork.com/journals/jamainternalmedicine/fullar...
[1] Supplemental material https://jamanetwork.com/data/Journals/INTEMED/0/IOI160102sup...
Ideally, we'd ask a group of male doctors and a group of female doctors to independently diagnose and treat the same set of patients. We can't actually do that--in addition to the cost, you obviously can't treat the same patient twice. However, we can try to estimate this effect statistically.
First, they build a model describing the probability of a patient dying within 30 days. They used a linear probability model, which essentially means that the probability of someone dying is the sum of the "weights" related to the patient, doctor, and hospital. These weights are estimated from the data using ordinary least squares (the same way you may have learned to fit a line to points at school).
Having built the model, they then ask what the marginal effect of the doctor's sex is. In other words, if you hold everything but that constant, how does the probability of dying change? They cite a nice Stata guide (#32 in the paper here: http://www.stata-journal.com/sjpdf.html?articlenum=st0260 ) which gives some background and examples.
The rest of the paper looks at different variations (only hospitalists, different diseases, etc), using a pretty similar approach.
That's an interesting observation. On the one hand younger doctors have been more recently exposed to "current" ideas, research, and stuff. On the other hand younger doctors lack the experience to catch things that are unusual and often discussed as theoretical.
I'd be curious to see if there were research on this topic now!
The paper reports that they included both physician age AND years in practice, along with a slew of other factors.
We should inhibit the impulse to dish out snark for the brief thrill of feeling smarter than an author or researcher, not because they don't occasionally miss the obvious (who doesn't?), but because it lowers the standard of discussion here.
A better way to present such a comment might be as a question: "In my experience, X. Does the study Y?"