Are Women Really Better Doctors Than Men?

A new study suggests you’re better off if your hospital physician is female.

It’s a battle of the sexes today as we dive into a paper that made me say “wow, what an interesting study” and also “boy am I glad I didn’t do that study”.  And that’s because studies like this are always somewhat fraught – they say something about medicine but also something about society – and that makes this… well… a bit precarious. But that’s never stopped us before. So let’s go ahead and try to answer the question: do women make better doctors than men?

On the surface, it seems like a nearly impossible question to answer. It’s too broad for one – what does it mean to be a “better” doctor? And at first blush it would seem there are just too many variables to control for here – the type of doctor, the type of patient, the clinical scenario and so on.

But this paper, which appears in the Annals of Internal Medicine, uses a fairly ingenious method to cut through all the bias by leveraging two simple facts: First, a lot of hospital medicine is conducted by hospitalists these days. And second, due to the shift-based nature of hospitalist work, the hospitalist you get when you are admitted to the hospital is pretty much random.

In other words, if you are admitted to the hospital for an acute illness, and get a hospitalist as your attending, you have pretty much no control over whether it is a man or a woman. Is this a randomized trial? No – but it’s not bad.

Researchers used Medicare claims data to identify adults over age 65 who had non-elective hospital admissions throughout the United States. Based on claims, they could tell the sex of the patient and who the attending physician was, and by linking to a medical provider database they could determine the sex of the provider.

The goal was to look at outcomes across four dyads: male patient – male doctor, male patient – female doctor, female patient – male doctor, and female patient – female doctor. The primary outcome? 30-day mortality.

OK I told you that by focusing on hospitalists, you get some pseudo-randomization, but let’s look at the data to be sure.  We have just under a million patients treated by around 50,000 physicians, 30% of whom were female. And, though female patients and male patients differed, they did not differ with respect to the sex of their hospitalist. So, by physician sex we have similar mean age, race, ethnicity, household income, eligibility for Medicaid, and comorbid conditions. The authors even created a “predicted mortality” score which was similar across the groups as well.

Now, the female physicians were a bit different than the male physicians. We know they were all hospitalists, but you can see that the female hospitalists were slightly more likely to have an osteopathic degree, and had slightly lower admissions per year in the dataset. They were also a bit younger.

OK so we have broadly similar patients regardless of who their hospitalist ends up being – but we know those hospitalists differ by factors that are not exclusively sex. Fine. What are the results?

I’ve graphed them here. What you can see is that female patients had a significantly lower 30-day mortality rate than male patients, but they fared even better when cared for by female doctors compared to male doctors. There was not a particularly strong influence of physician sex on outcomes for male patients. The secondary outcome, 30-day hospital readmission, showed a similar trend.

This is a relatively small effect, to be sure – but if you multiply it across the millions of hospitalist admissions per year you can start to put up some real numbers.

So… what is going on here?

I think there are four broad buckets of possibilities.

Let’s start with the obvious explanation – women, on average, are better doctors than men. I am married to a woman doctor and based on my personal experience this is undoubtedly true. But why would that be?

The authors cite data that suggests that female physicians are less likely to dismiss patient concerns than male physicians – and particularly they are less likely to dismiss the concerns of female patients – perhaps leading to fewer missed diagnoses. But this is impossible to measure with administrative data, so this study can no more tell us whether these female hospitalists are more attentive than their male counterparts than it can suggest that the benefit is mediated by the shorter average height of female physicians – perhaps the key is being closer to the patient?

The second possibility here is that this has nothing to do with the sex of the physician at all – it has to do with those other things that associate with the sex of the physician. We know, for example, that the female physicians saw fewer patients per year than the male physicians – but this was adjusted for in the statistical models. Still – other unmeasured factors- confounders – could be present. By the way, if this is the case it doesn’t necessarily change the primary finding – you are better off being cared for by a female physician, it’s just not because they are female – it’s just a convenient marker for some other quality – like age.

The third possibility is that the study represents a phenomenon called collider bias. The idea here is that physicians only get into the study if they are hospitalists – and the quality of physician choosing to be a hospitalist may differ by sex.  When deciding on a specialty, a talented resident considering certain lifestyle issues may find hospital medicine particularly attractive – and that draw towards a more lifestyle-friendly specialty may differ by sex, as some prior studies have shown. If true, the pool of women hospitalists may be better than their male counterparts because male physicians of that caliber don’t become hospitalists.  OK – don’t write in guys – I’m just trying to cite examples of how to think of collider bias. I can’t prove this is the case, and in fact the authors do a sensitivity analysis of all physicians, not just hospitalists, and show the same thing, so this is probably not true but epidemiology is fun, right?

And the fourth possibility – this is nothing. The effect size is incredibly small and just on the border of statistical significance. Especially when you’re working with very large datasets like this, you’ve got to be really careful about overinterpreting statistically significant findings that are nevertheless of small magnitude.

Regardless – it’s an interesting study. One that made me think, and of course, worry a bit about how I would present it to all of you.  Forgive me if I’ve been indelicate in handling the complex issues of sex, gender and society here. But I’m not sure what you expect. After all, I’m only a male doctor.

A version of this commentary first appeared on Medscape.com.