Equity, Organized Medicine, and the Radiology Value Chain

It’s often said that large organizations are difficult to steer and slow to change course, but that’s only part of why they sometimes act in seemingly inexplicable ways. There’s another more insidious reason, and that is conflicts of interest, not just within leadership but also in the changing demographics of the membership.

A passage from “Value Chain: Where Radiologists Should Put Their Focus in Threats Against Income” by Seth Hardy MD MBA in Applied Radiology:

So, while private/public equity firms can use leverage to amplify profits to the upside, leverage has an opposite effect when gross income is in decline. Any cuts to reimbursement would be truly devastating to these firms’ employees; since the debt holders get paid before the radiologists, the impact on employed radiologists’ salaries may be significant. As equity-employed radiologists make up a greater share of dues-paying members within organized medical societies, it is easy to understand why the proposed CMS cuts were characterized as draconian by those societies. But a clear understanding of value chain by physicians is increasingly critical to evaluate the rhetoric of our medical society leadership.

I am now a partner in a physician-owned independent radiology practice. A CMS paycut would mean that we earn commensurately less money–not that we will become insolvent.

That should count for something when choosing where to work.

To STAT or not to STAT

A passage about limited resources and optimizing imaging from The Emergency Mind: Wiring Your Brain for Performance Under Pressure by Dan Dworkis MD PhD:

Within the broader context of your responsibility however, there frequently will be significant variability in the relative urgencies of individuals being imaged. Some patients—like a person seemingly experiencing an acute stroke—do need to be scanned immediately. Others—such as a patient with abdominal pain, stable vitals, and a reassuring physical exam—while no less “deserving” of those resources, would receive nearly equal benefit from being scanned now as in an hour from now. Optimizing care across the field in this context would involve prioritizing CT scans for those patients who would receive outsized benefits from immediate imaging, even if this makes some other patients wait longer.

Put a different way: If everything is stat, nothing is stat.

Stat abuse is one of those crimes especially tempting to inpatient teams in busy hospitals. It’s natural to want answers (and dispo) as soon as possible, and we assume that we will get them faster if we increase the priority of the exam.

All a clinician knows is that sometimes something ordered routine takes forever and that ordering stat should generally result in it being performed faster. They may not even care if the read is prioritized in all cases so long as the patient is freed from the waiting and future transport.

It’s also human nature for there to be a distribution with certain individuals ordering an outsize proportion of “stat” exams. The negatives of over-ordering or inappropriate priority are almost always placed on other staff. In a zero-sum game, selfish behavior may be an optimal choice for individual success even if it makes the system less efficient overall. Hospitals very rarely scold their staff for such abuses.

I don’t think most clinicians even have any idea where along the spectrum their behavior falls. Knowledge of outlier performance one hopes might curb excesses, and that data would certainly be helpful for individuals to know (presuming those individuals are capable of feeling shame and said shame functions as a deterrent). Such information would have to be long-term and stratified well to be meaningful (we should expect different levels of stat exams as a fraction of orders from different hospital units, for example). Otherwise, data are dismissible.

Ultimately, pleading and punishment are often ineffective and/or undesirable.

A more helpful approach would include data to guide decision-making on a case by case basis:

The EMR should show in real-time the expected wait for different study types based on the current queue and exam types pending, both inpatient and outpatient (i.e. how many unnecessary exams are obtained during an inpatient stay due to fears of long delays for outpatient follow-up?). Yes, a routine study may unexpectedly get bumped further down the line, but a smart system would incorporate predictions based on the current patient census, admission diagnoses, time of year, and whatever else some machine learning algorithm would include its impenetrable black box of Skynet code.

It would be extremely helpful for all parties to know if an MRI should be expected today or tomorrow, sometime this afternoon or more likely at 3 am.

And so, yes, of course, people are working on this in the machine learning world. But hurry up. I for one will continue to welcome our AI overlords and their promised efficiency gains, but I’m still waiting.

Getting Started in Radiology

Here’s a little compilation of posts from the last few years about getting started as a new radiology resident.


Approaching the Radiology R1 Year and its short companion post: How to be a First-Year Radiology Resident.

Want something a little more controversial? Stop Free Dictating.


Book Recommendations for First-Year Radiology Residents (and some further recommendations for when there’s extra book fund to burn).

You can round that out with some more general thoughts on studying during residency.

Also, residents from across the country in the ACR Resident and Fellow Section came together and assembled a nice collection of free radiology learning resources from across the interwebs including lots of videos.


Diganostic FOMO

From Suneel (brother of Sanjay) Gupta’s Backable: The Surprising Truth Behind What Makes People Take a Chance on You:

Apply the following quotation to why doctors don’t want to make the call:

If the fear of betting on the wrong idea is twice as powerful as the pleasure of betting on the right idea, then we can’t neutralize the fear of losing with the pleasure of winning. We can only neutralize the fear of losing with…the fear of losing. Enter FOMO, the fear of missing out. For backers, the only thing equally powerful to missing is…missing out.

Gupta goes on to discuss how potential backers initially too scared to be the first investor eventually pile on to avoid missing out on rare unicorns.

The fear of betting on the wrong idea in medicine manifests through overtesting and hedging. More than our desire to be right, we really don’t want to be wrong. But we can’t use the usual FOMO to our advantage, because medicine isn’t about making pitches or raising money but about directly helping individual people.

We don’t want to miss anything and so are forced to entertain everything, even if that means everyone in the ED gets a CT scan or a radiologist gives an impression a mile long with the words “cannot be excluded” featured prominently next to something extremely scary.

The true solution is this: we need to disentangle the outcome from the process. You can have good outcomes from bad decisions (dumb luck) or you can have bad outcomes after good decisions (bad luck). Luck and uncertainty are part of life, and they’re a big part of medicine. We should expect some bad outcomes even when doing the right thing, and we shouldn’t forget that overtesting and overdiagnosis have their own costs, risks, and harms. Passing the buck to the future doesn’t mean it won’t be paid.

By not making the call, we are making a decision: a decision to abdicate the diagnostic yield of an encounter or examination.

There are absolutely times when uncertainly is prudent. There are true “differential” cases. But the FOMO of diagnostic medicine should be passing up an opportunity to clearly define the next steps in a patient’s care.

Student loan debt predicts burnout

From “Predictors Between the Subcomponents of Burnout Among Radiology Trainees” by Le et al. in JACR.



In summary:

Debt level < $200,000 was associated with lower [emotional exhaustion] scores among upper-level trainees and was the only predictor of burnout that significantly affected multiple years of training.

I suspect there is a dose-response above that debt level as well.

Uncertainty breeds despair. Make sure you develop a student loan action plan.