The title should be "hospital patients treated by low volume physicians are more likely to die". But that would have been less likely to get published. The "high volume" group was also really NOT high volume: 200 patients per year is around 4 patients per week. So the study really tells us about very 'low volume' providers compared to slightly higher volume providers, it's interesting that that was enough to get rid of any age-related effect. That in turn suggests the effect was pretty small.
Similarly, I'm pretty sure that "code written by programmers who don't program often is more likely to have bugs", and "pilots who don't fly often are more likely to crash".
(Strictly speaking, you'd want to normalize the risk of bugs / crashes per some unit of output e.g. per hour flown for pilots.)
Older docs don't have to take board exams every ten years. Incoming doctors all have to take board exams every 10 years for the rest of their working life. This may account for why high volume doctors don't have the higher mortality rate even for older physicians. Perhaps the higher volume makes them more likely to be current in their field.
> So the study really tells us about very 'low volume' providers compared to slightly higher volume providers
I don't think 'slightly higher' is accurate. The report says, "We classified physicians into thirds of patient volume: low (estimated number of total admissions <90 per year), medium (91-200 admissions), and high (>201 admissions)". So you have two-thirds of doctors whose median volume is 90 per year, and one third of doctors whose median volume is well above 201 per year. That seems to be a significant difference.
> That in turn suggests the effect was pretty small.
For two-thirds of doctors the effect is: "adjusted 30 day mortality rates were 10.8% for physicians aged <40 (95% confidence interval 10.7% to 10.9%)...and 12.1% for physicians aged ≥60 (11.6% to 12.5%)". I'd say that's a significant effect - certainly something that should be included in the title.
Could it be that older (more experienced) physicians are more likely to get assigned to patients with more complex or serious conditions?
(I don't mean to state the obvious but this wasn't made explicitly clear enough to me.)
Edit: My initial comment here is probably wrong based on the detailed section "Adjustment variables":
> Patient characteristics included age in five year increments, sex, race or ethnic group (non-Hispanic white, non-Hispanic black, Hispanic, other), primary diagnosis (diagnosis related group), 27 comorbidities (Elixhauser comorbidity index22), median household income of zip code (in 10ths), an indicator for dual Medicare-Medicaid coverage, day of the week of the admission date (to account for the possibility that severity of illness of patients could be higher on specific days of the week), and year indicators.
They do say that they adjust for "patient characteristics", although they don't go into much detail. Also it's important to note that physicians that have a large volume of patients don't have a higher mortality rate on their patients. It looks like a real effect, maybe from "staying behind" or maybe simply not being on the "top of their game".
It's difficult to really say for certain what's going on. The adjustments I'm sure are very crude compared to what case assignment decisions are actually based on, for example, so I'm sure they're adjustments wouldn't really account very well for patient illness severity or other subtleties along those lines.
Another possibility is that younger staff are more likely to be questioned about things. "Have you thought about X?" causes them to rethink something and make a revision. If older staff are just assumed to know what they're doing, they might be questioned less.
The fact that differences weren't present among physicians with a large volume also makes me wonder if this is just a fishing expedition that wouldn't replicate. Not to cast aspersions on the authors; just to say that if you slice up any dataset enough you can find something.
Patient assignment to physicians (at least in internal medicine) is based upon either a rotated call schedule or, in the case of hospitalists, who tend to admit every day that they are on service, is done randomly to keep the different providers' patient load balanced in size.
I always find it concerning when authors dichotomize a variable without an extremely solid basis for doing so. It reduces statistical power, and it hints of over-mining the data to dredge out an effect.
This group of authors is well respected and known for doing studies like this. However, if their chief interest is observing the effect of physician age on patient outcome, physician age should clearly be treated as a continuous or truncated variable here.
Edit: In the supplement [1. Table B], they do perform the calculation with physician age as a continuous variable, and the effect stands. Good on them for doing the math in this way.
Physician age was modeled both as a continuous linear variable and as a categorical variable (in categories of <40, 40-49, 50-59, and ≥60) to allow for a potential non-linear relation with patient outcomes.
can you explain what it means? Specificially, how does making it categorical allow for it, and keeping it continuous prevent it?
Probably because when treating it as continuous they only look for linear regression.
When categorizing in buckets, they probably do an ANOVA. This technique posits that the average does vary per category exactly as measured, and asks the question: If I tell you the category, how much is the variance of your data reduced? If the variance falls a lot (relatively to what it was), it means there's a statistically significant effect between the category and your variable.
And, in their defense, they can't really go fishing for different continuous relationships once they have the data, as that'd reduce their statistical power.
Of interest too is the number of adjustable parameters of the model:
If instead of four age categories you use, say, four hundred, you end up splitting each doctor into one category. The predictive power of that model is greatest, with very good statistical significance, but you have achieved no insight at all.
Similarly when taking age as continuous; if instead of a straight line you fit a curve with four hundred free parameters, you overfit it to the point of destroying any insight.
So in that sense it's "unfair" that they used four age categories, vs two free parameters of a linear regression. And there would need to be some explanation as to the age ranges they used for each category.
I listened to a podcast on this, Freakenomics Radio Bad Medicine Part 3.
The takeaway was that newer doctors had better outcomes than older doctors with the exceptions of surgeons.
"JENA: Exactly. So patients more or less end up getting quasi-randomized to physicians with different characteristics. So for example if you happen to get hospitalized in the first week of May, you may be treated by a group of doctors who on average have five years’ less experience than if you happen to get hospitalized in the second week of May. And we can basically see what happens if a patient happens to be treated by a doctor who is 20 years out of residency versus 5 years out of residency. And what we find is that if you happen to be treated by a doctor who is 10 years or 15 years out of residency, your mortality within thirty days of being hospitalized is higher."
"The effect of senior obstetric presence on maternal and neonatal outcomes in UK NHS maternity units: a systematic review and meta-analysis"
> Fifteen studies fulfilled the inclusion criteria, presenting data from 125 856 births. Overall, there was no significant difference between lesser and increased consultant presence for any outcome. When data were stratified by comparison type, the likelihood of emergency caesarean section was significantly lower (odds ratio, OR 0.91; 95% confidence interval, 95% CI 0.86–0.96) and the likelihood of non-instrumental vaginal delivery was significantly higher (OR 1.07; 95% CI 1.02–1.12) when the rostered hours of consultant presence per week were increased.
The news here (Japan) was talking the other day about cases of TB slipping through diagnosis because younger physicians had no experience with it. Older doctors knew what it was right away.
Older doctors can probably diagnose TB better, but I would wonder if that can be used as a core competency measure of a doctor. Also, I believe there are cases younger doctors diagnose a lesser-known disease when older ones could not.
There can be all different sorts of anecdotes, but the link was about a study with more than 100k doctors, which would be a stronger evidence that the probability of survival is better for patients with younger doctors.
Funny, this reminded me of my own surgery that had complications. My surgeon said that he has done over 200 similar surgeries and I was his first complication. The first thing that came out of my mouth was no wonder you don't know how to handle complications because you have been running around like a headless chicken. In the end, postop complications were addressed by a surgeon half way around the world than the operating surgeon.
> The first thing that came out of my mouth was no wonder you don't know how to handle complications because you have been running around like a headless chicken.
I daresay you drew the wrong conclusions from this incident.
All things being equal, a doctor with more experience and a lower rate of complications should be your preferred choice for any medical procedure.
"Lower rate of complications" is much better than "ZERO rate of complications". When you had zero problems, you have no experience handling problems. When you had some problems, you know how to handle problems. When you had too many problems, you are careless.
I meant doctor didn't come across confident in how he was handling the complications. He was trying lot of different things without proper reasoning. He was clearly flustered. I was actually more calmer and methodical than him.
The way I see it in the field, older doctors are less likely to try and keep terminal patients alive as long as possible and more likely provide just palliative care. You know, instead of intubating 90+ y/o elders that won't get extubated until death.
Sounds like a study with a lot of confounding factors. Example- patients treated in the ICU are more likely to die than those not in the ICU. The confounding factors being the critical condition of the patient. Patients in critical condition are brought to the ICU. The abstract of this paper says that it essentially compares doctors in the same hospital. Is it a stretch to think that senior doctors would see more complex cases.
In my experience, older doctors simply... get old.
They lose enthusiasm and energy. They are inclined to study less. They perform fewer procedures due to diminishing motor, visual-spatial and cognitive skills.
They suffer the same ailments as their patients - hypertension, diabetes, arthritis, dementia; divorce, overwork, errant children (that's a whole category of grievance and burden !) as well as sundry personal issues.
There is the drudgery. Paperwork. After a few decades you have seen it all: the rare cases don't excite as much. They are just another presentation of the human condition.
Finally,medicine is a hierarchical discipline, younger practitioners are discouraged from questioning (dubious) decisions made by their seniors.
Older practitioners compensate for these deficits with an accumulated body of experience that a younger doctor simply does have.
The best age(s) to be a doctor is mid-thirties to early fifties. Just like most other professions.
The actual results are not quite as dire as the headline suggests:
"patients’ adjusted 30 day mortality rates were 10.8% for physicians aged <40 … and 12.1% for physicians aged ≥60 … Among physicians with a high volume of patients, however, there was no association between physician age and patient mortality."
All of the patients were 65 or older with a medical condition. Perhaps the oldest and sickest are regularly routed to older doctors? As ever, correlation does not imply causation:
Re: ". Among physicians with a high volume of patients, however, there was no association between physician age and patient mortality. Readmissions did not vary with physician age, while costs of care were slightly higher among older physicians."
So it's not just age per se, but age plus lack of case quantity.
Which now raises the questions:
1) How are patients assigned to doctors? Is there something else that effects outcomes?
2) Why are some docs carrying less patients? Is that the cause, and age the correlation?
It was an older vascular surgeon who found the ascending aortic dissection that the much younger ER attending and hospitalist had both missed. For hours.
It may have do with experience. When you have limited experience, you tend to use all your faculties and guided by logical reasoning. When you have lot of experience, you are guided by past experiences and likely to miss something new, when symptoms are similar to something you have encountered before. Interestingly both my major medical issues were diagnosed by my primar care physician and not by the specialists that I was already working with.
Even in my professional work experience, the new problems that may fall across multiple domains tend to be identified/solved by generalists rather than specialist.
It used to be a commented on phenomenon that the month after the twice yearly arrival of newly qualified housemen in hospitals were the worst periods, mortality wise.
I don't know if that is still the case or indeed was ever a 'real' thing.
From their conclusions, I wonder if there is some kind of "use-it-or-lose-it" effect going on in the sample of older physicians, which does not affect the sample of younger physicians as severely due to their age. That is, the high volume physicians are kept sharp by the high patient workload regardless of age.
Authors' conclusions reproduced below:
"Within the same hospital, patients treated by older physicians had higher mortality than patients cared for by younger physicians, except those physicians treating high volumes of patients."
A little off-topic, but I get the feeling that these studies won't be so important in the coming decades. AI is going to be better than both young and old doctors when it comes to diagnosis, or recommending drugs and treatments. I've tried to have some discussions about this on Quora and Reddit, but I quickly get shot down by people (sometimes doctors) who refuse to accept this. I think there are even a lot of skeptical people on Hacker News, which I don't understand. It just feels obvious and inevitable.
So... the patients with the most serious illnesses are assigned to the most experienced physicians? While the younger ones start out taking care of people with less serious conditions?
This does not relate to the physician population studied, but I've seen older attendings in certain specialties use political clout to score more exciting rotations in critical care units after rarely practicing while younger attendings who don't often practice generally are forced to maintain a clinic. I would be interested in seeing if that had any general impact in care.
For the people that keep saying this result is because older doctors get allocated sicker patients - this is definitely not the case. When you are rostered on, you see every patient that comes in the door no matter how simple or complex.
A similar trend exists with practices which I read about in the book Peak by Anders Ericsson. Older doctors and specialists' performance grew worse over time. Older doctors knew less and did worse in terms of providing appropriate care than doctors with far fewer years of experience.
Similarly, I'm pretty sure that "code written by programmers who don't program often is more likely to have bugs", and "pilots who don't fly often are more likely to crash".
(Strictly speaking, you'd want to normalize the risk of bugs / crashes per some unit of output e.g. per hour flown for pilots.)