Speaking of physician shortages, Tennessee just became the first state to pass legislation allowing international medical graduates to obtain licensure and practice independently without completing a U.S. residency program. Bryan Carmody breaks it down.
ChatGPT’s newest version, GPT4, was able to pass a no-image multiple-choice radiology exam.
GPT4 is neat, but this says a whole lot more about how useless and off-base a radiology exam without pictures is than about how ready for prime time the current AI tools are. But they’re coming, and I for one am interested to see more natural language processing combined with what’s already out there to actually make healthcare more efficient (automated discharge summary drafts! a real summarized history on imaging orders!)
The authors also do note that when GPT4 is wrong, it’s often wrong in spectacular ways (and will boldly make up lies with the same confidence as it dishes out true answers). As in, not quite ready for anything when real performance counts.
It took a few years before it finally got there, but massive private equity-owned physician staffing company Envision finally filed for Chapter 11 bankruptcy this week.
The harbinger of the coming wave of PE defaults, bankruptcies, distressed exchanges, and other failures has fully arrived. Make no mistake, this is just the beginning.
There are people who see this news and rejoice. It’s not hard to see why. There might be more than a bit of schadenfreude seeing a big private equity company go belly up. These entities are so often in the business of pure value extraction. They aggressively use leverage to buy a bunch of stuff using a bunch of borrowed money and try to increase profits through negotiating clout, suppressed salaries, and unsavory financial machinations. They often take successful companies and saddle them with so much debt that they fail, strip them for parts, and let everything fall apart after they’ve made sure they made their buck. Many of the big retail failures of the past decades have all been the same story.
Envision was in the process of the usual playbook of financial machinations to separate the profitable wheat from the debt-riddled chaff when the WSJ reported on the possible impending bankruptcy and forced their hand.
Because such a large portion of their purchases are funded through debt, it’s relatively rare that the PE-owner actually loses a ton of their own money in the process. Envision’s owner KKR wasn’t quite so lucky: while the levered buyout was almost $10 billion in 2018, they are still likely to lose their entire ~$3.5 billion stake.
A Fall Long Coming
Envision’s reimbursement games didn’t pan out, not just their ploy of going out of network to charge exorbitant rates to unsuspecting patients–a practice curtailed by the No Surprises Act–but also from the bad acting of big payers like UnitedHealthcare (there are very few good guys in healthcare). Adding insult to injury, they weren’t able to squeeze physicians and other staff in the hot job market. Labor costs have been going up.
While Envision as a normal business is functioning, valuable, and generates cash, its growth was nowhere near the level required to service its more than $7 billion of debt. If the credit markets were loose like in the pre-Covid era, they probably would have been able to refinance without issue. Now, the cost of capital is simply too expensive.
This possibility was in the news back during the early Covid days, but Envision was temporarily saved by an influx of cash from the CARES Act. They recently defaulted on their debt and subsequently filed for Chapter 11 bankruptcy on May 15.
From the announcement email from Envision CEO Jim Rechtin:
Upon emergence from the restructuring, both Envision and AMSURG will be under new and separate ownership, comprised of current lenders. KKR will no longer have a stake in either company.
The email goes on to state the following items unironically:
- Envision and AMSURG are not going out of business. The filing ensures an orderly process for restructuring our debt and finances. This is not a liquidation.
- Our clinicians and clinical support teammates can expect to receive their normal wages and benefits. Independent contractors and locums can expect their usual payments.
- The filing does not change the regular work schedules of our clinicians or clinical support teams – operations will be business as usual.
- Our top priority is continuing to deliver high-quality care and supporting our hospital partners and surgery centers without interruption to services.
- There should be no change to the quality of service our patients and their families have come to expect from us.
As part of the process, Envision is now owned by its creditors (the lenders who had given secured loans and/or purchased corporate bonds,) and KKR has lost its stake and will no longer own/run the company. And it’s worth pointing out that nothing unsavory has really happened in the sense of business practice. This is how the industry is designed to work. People invest money and take on risk in order to make money. A company taking on debt it knows it can’t really afford and other unnecessary/excessive risks that might screw over its creditors is part of the game. When companies fail, the creditors get the scraps before the equity owners/shareholders.
Billions of dollars have been lost, absolutely, but at the end of the day, it’s mostly big institutional investors like large pension funds that are the ones who have lost in the short term. KKR made a bet and lost. They’ll be fine.
Of interest to most physicians is that the day-to-day function of Envision probably won’t change much, and this big company that got big by borrowing an unsustainable amount of money to fund its growth still exists. It may even emerge from this process potentially stronger than recent years now that it won’t have billions of dollars on the balance sheet and the need to make periodic debt payments. They will probably not be able to raise more capital in the current environment, which will prevent the kind of debt-fueled highly-leveraged growth that allowed a company like Envision to buy large practices in the first place. And their management record still does not inspire confidence. But at the end of the day, Envision as an entity is still big, still employs thousands of doctors, and still has a dominant market position in several locales. If there is any physician staffing company that could be considered too big to fail, Envision is one.
You might ask, why would Envision’s creditors take the deal? Is losing billions of dollars fun? Well, no. This is the nature of distressed exchanges: better to lose a few billion and end up with a big profitable company at the end than lose all of your billions.
What Next?
From the official FAQ:
How will patients be impacted?
Patients will continue to receive the same high-quality, high-value care our clinicians and physician partners have always provided. Patients and their families should notice no difference in our operations or level of care.
This is why those hoping that the collapse of private equity-funded healthcare ventures will lead to a return to better times are unfortunately in for a grim reality check. The tactics and market consolidation don’t have to go away just because they can’t pay their debts. We’re not likely to undo any damage already done. For better or worse, these companies will mostly soldier on. The playbook lives to see another day.
Unless physicians quit in droves on principle or in fear, the status quo continues. If people take the wake-up call about the flaws in the funding model, that’s a different story.
From Elisabeth Rosenthal’s (author of An American Sickness) “Denials of health-insurance claims are rising — and getting weirder“:
An insurer’s letter was sent directly to a newborn child denying coverage for his 4th day in a neonatal intensive-care unit. “You are drinking from a bottle,” the denial notification said, and “you are breathing on your own.” If only the baby could read.
People have really enjoyed asking the current generation of large language models (LLMs) like ChatGPT about AI: a sort of overly on-the-nose meta-discussion. Reid Hoffman, co-founder of LinkedIn and techno-optimist/evangelist, co-wrote a free book about AI with GPT-4 called Impromptu: Amplifying our Humanity Through AI.
In a late chapter, Hoffman makes an argument that modern humans are homo techne (“the technological human”), essentially that “technological innovation is, and always has been, humanity’s defining feature.” He talks about the many inventions of the past and how amazing it has been since the early 1920s. For example:
Whoever you were in say, 2005, you are—if you regularly use a smartphone now—a dramatically enhanced version of that person. (p. 192)
GPT-4’s response is a bit more nuanced:
I don’t necessarily disagree with any of the points you made, but I think it’s important to remember that not everyone experiences these benefits equally. For example, while it’s true that the average human life has doubled in the past hundred years, there are still parts of the world where life expectancy is much lower, due to poverty, lack of access to healthcare, or other factors. And while smartphones and other technology have certainly made our lives easier in many ways, they can also exacerbate existing inequalities—for example, by making it easier for those who can afford them to access information and opportunities, while those who can’t are left further behind. So while I don’t disagree that we’re living in an incredible time, I think it’s important to keep in mind that these benefits aren’t universally shared.
Reid:
That’s a very important point. Do you think modern emerging technology can help us democratize these benefits, or otherwise address long-standing equity issues?
GPT-4:
I think it’s definitely possible. For example, telemedicine could help address the lack of access to healthcare in under-resourced areas, and technology that allows for remote work or online learning could create new opportunities for people in rural or impoverished areas. But I also think that it’s important to remember that technology is only a tool—it’s up to us as a society to make sure that it’s used in a way that promotes equity and benefits everyone, rather than just a select few.
There’s a certain grain of techno-optimism that’s almost as tedious as the doomsaying: the belief that good arises organically as a feature of the technology itself as opposed to from the human systems that deploy it.
For a lot of people, the early democratic internet seemed to bear this out. This is what I thought as a middle schooler playing online hand-coding websites in HTML to post on Geocities. The whole thing is magic! And then we got Wikipedia–amazing! But I think in the era of social media and conglomerate capitalism, we should all know better by now. Hoping everything gets so profoundly broken that the governments of the world will be forced to provide a universal basic income (UBI) but that otherwise no harm is done is probably naive.
GPT4 is derived from the content of the internet. While the model is tuned to provide more useful and less racist/sexist/terrible responses, the fact that its statistical process is able to generate responses like this suggests to me that the people who have written about this publically have probably thought about it correctly. I don’t know if we’ll listen.
Years ago, when I was a resident and the ABR Core Exam was still novel, the ABR offered a lengthy “ABR CORE Examination Study Guide” PDF, which–in addition to over a hundred pages of endless bullet points listing every conceivable topic in radiology–included 57 official practice questions at the end (with an answer key).
They took that down years ago. But, thanks to the miracle that is The Internet Archive, you can still enjoy a copy of that PDF here. Well worth doing in the final weeks leading up to the June exam. Enjoy!
(Other nonofficial question resources are discussed here.)
((Lest there be any confusion, I have no working relationship with the ABR. In fact, I’m probably a persona non grata. These are just questions that they once posted on a public-facing website.))
It should go without saying, but I’ll say it anyway: these are my opinions, formed from the combination of my biases, my experience as a radiologist since beginning residency 10 years ago, and my many conversations with radiologists across the country. You don’t have to agree with me.
Not Enough and No Help Coming
For today’s needs and today’s technology, we have simply produced far too few radiologists. There is a sizable and worsening radiologist shortage, and there is no end in sight on the basis of increased radiologist supply. There are currently 1788 separate job postings on the ACR job board. Imaging volumes are increasing between 3 to 5% per year (increasingly including low-yield complex exams), but no one is seriously attempting to address utilization at any level. Nationwide, the supply of radiologists is basically flat. The anticipated wave of retirements from vested PE buyouts is just beginning.
It’s true that reimbursement has been steadily falling and that radiologists have been forced to read more in order to maintain their income, but it seems that even there, any excess workforce tolerance for higher workloads has been saturated. If anything, the tighter job market after the 2008 crash and the desire to maintain income against that downward reimbursement pressure masked the problem. Burnout is now so rampant and commonly discussed that it’s mostly just meme bait on social media.
Turnaround times are worsening. For example, a memo to the medical staff of Ascension Saint Mary in Chicago was making the rounds back in March:
Our current Radiologist group, RadPartners, has been experiencing challenges with physician coverage for some time. As a result of this radiologist shortage, outpatient exams are taking anywhere from one to six weeks to be read.
Six weeks?! I don’t think most practices have much more to give before flaming out, and many groups are shedding contracts in an attempt to right-size their workloads. (This was in fact a contract in its final months that RP had already terminated. [Also note, given comments I’ve received: this quotation was included for flavor, not because RP or this one group is the basis for this article’s argument.])
There’s a generational shift contributing as well. People’s understandable desire to have a better lifestyle also means that in some cases we require more young radiologists to cover the jobs of those leaving the workforce. It wasn’t that long ago that most radiologists covered their own nights on a rotation (or paid for tele coverage) and no one had dedicated night teams. Then it was normal to see a 7-on/7-off schedule. Now 7/14 and even 7/21 schedules are increasingly common. When you need three people to do the job of one person, that isn’t going to help with the workforce shortage.
Frankly, I think there’s no chance of radiologists meeting demand without a paradigm shift of some kind, either the long-awaited mass efficiency gains from meaningfully helpful AI products (maybe good?) or the significant expansion of the role of midlevel providers in image interpretation (highly suboptimal and currently not permitted). It’s hard to imagine a world where volumes actually go down in this country, but that would also work.
The training pipeline is essentially fixed in size and long in duration. Even opening up more training spots would take years to help. If the shortage gets worse, then turnaround times will continue to lengthen (and patients suffer) and hospitals will struggle to get coverage (and patients suffer). That will be the time when the government/Medicare/national organizations start advocating against the currently protected role that radiologists hold for imaging interpretation.
Years from now, there may be a world where there are too many radiologists, but that world is one where radiologists are performing a substantially different role than they are today, and I’m not sure there’s any way to meaningfully prepare for that possible future while also solving the problem of getting today’s work done. (more…)
From an opinion piece in AJR recently titled “The Case for Presence as a Source of Professional, Educational, and Social Fulfillment“:
Although the long-term impact on social wellbeing of working virtually compared to working in-person is not yet fully understood, physical presence is likely to be conducive to establishing connectedness.
This is a valid knock on teleradiology. Working alone by yourself just isn’t the same as having real colleagues, hanging out with peers, and enjoying spontaneous interactions throughout your work day. I absolutely agree. Sure, having some remote work is great. It’s flexible and efficient. But I took the specific job in private practice I did precisely because I wanted to have peers, teach residents, and otherwise have a varied work-life experience (yes, including working from home sometimes).
All things being equal, we really benefit from spending time with real, live humans. The data show that having a “best friend at work” is a powerful force.
But.
The problem with this kind of article is that it’s a reflection of the academic bubble. When we draw a comparison between a typical academic center or hospital-based practice and teleradiology, we miss the fact that many, many radiology jobs are not team-based daily work. Yes, there are still jobs where you’ll drive to the hospital and work with your peers. There are even some with communal reading rooms and the chance to socialize. But the reality of modern private practice is that a lot of radiologists drive around town to sit by themselves in small reading rooms in the back of outpatient imaging centers located in strip malls.
The false dichotomy (tele = inescapable loneliness, non-tele = Shangri-La) misses the fact that the so-called downside of a remote/at-home practice applies equally well to the reality of private practice in many locales. If you’re commuting just to cover contrast from a dark closet somewhere, you’re not really benefiting from the perks of presence.
The key to meaningful comparison always rests on a foundation of fairness (apples to apples, not apples to oranges). Considering the enrichment you might get from physical presence in an academic medical center radiology position is one important consideration, but it’s ultimately a poor reference when comparing the jobs that many residents in many markets will decide between.
The more salient distinction between a teleradiology position and a local private practice job is the difference between sitting in your pajamas at home versus providing contrast coverage and the occasional procedure at an outpatient imaging center. Realistically, for better or worse, plenty of recent graduates don’t like doing procedures and don’t socialize with the techs. With that reality, it’s not hard to see why even trainees are interested in jumping straight into teleradiology. They’ve never experienced the relative isolation of being the only radiologist at a facility, let alone the isolation of being entirely remote.
Radiologists can argue themselves red in the face about how important it is to be visible and available to clinicians in order to demonstrate our value and the importance of face-to-face communication. That’s all well and good. But it is also outside the locus of control for an individual radiologist pursuing an individual job. The majority of imaging volume is outpatient imaging, and the majority of communication we do is over the phone. The volume is there, and the positions exist. How can we blame radiologists for taking the jobs that are available? The market consolidation from the growth of massive academic medical centers and nationwide private equity conglomerates coupled with a worsening radiologist shortage has fundamentally changed the workforce.
The reality when assessing an individual position is that there are good and bad types of every job. There are assuredly some teleradiology positions that have good support with built-in ways to reach out to colleagues for second opinions and reasonable productivity demands. And there are jobs that are local and in-person but spread out enough with bad IT infrastructure that you may feel even more alone.
You have to know what it is you want, and you have to evaluate each job on its own merits. You have to ask questions.
Yes, we’d probably all be happier feeling like we were part of something. I like my remote work days, but I have no interest in an exclusively teleradiology position. I agree with the thrust of the paper: presence matters. Unfortunately, most conventional jobs simply don’t offer that much presence and many that do are so busy that you can’t enjoy it.
So, ultimately, the distinction isn’t really just teleradiology versus in-person. It’s community vs isolation.
Osteopathic and allopathic physicians, DOs and MDs, are already essentially the same and have been increasingly so over recent years. But one admissions practice is very common for osteopathic schools and exceedingly rare for allopathic schools: requiring a letter of recommendation from a practicing physician (PLOR):
Although requiring a PLOR is very common practice among osteopathic medical schools, with 81.8% (36 out of 44) requiring it, it is rare among allopathic schools, with 3.9% (6 out of 154) requiring a PLOR. Allopathic medical schools only require LORs from a student’s undergraduate institution and strongly recommend a clinical letter but do not require it. According to the Association of American Medical Colleges (AAMC), allopathic schools matriculated 14.6% URM students in the year 2020 [28], compared to 11.1% URM students at osteopathic schools [4]. They also had more than double the percentage of Black matriculants (7.6 vs. 3.3%) [4, 28].
But.
On average, schools that required a PLOR have 37.3% (185 vs. 295; p<0.0001) fewer Black applicants and 51.2% (4 vs. 8.2; p<0.0001) fewer Black matriculants.
That’s a painful number. Schools that have this requirement receive end up with half as many black students.
Perhaps there are confounding factors here, but that difference demands at least further study. Frankly, I’m not sure whatever the purported benefits of a physician letter are that they could possibly justify the practice given the functional barrier they seem to create.
If you look at the data, applicants across the board are actually down with the requirement. While the barrier wasn’t specific to any group or underrepresented minority, the changes reached statistical significance only in that subgroup. It’s just a cudgel to decrease the admissions administrative burden.
I’ve written before about the “good reason to be a doctor” police. I think we, as a profession, are simply not that good at choosing candidates, and I sincerely doubt a letter from a random doctor means literally anything. Letters of Recommendation are mostly useless, but I especially fail to see how a letter from someone you follow around for a shadowing experience tells me anything about you as a person that I care about that couldn’t be determined from someone else.
There are social determinants of medical school admissions that are entrenched and difficult to change. Then there are the incredible costs of medical school that are baked into the status quo. But this? This is not a good or equitable way to shrink the applicant pool to a more manageable size for the admissions committee.
This is a petty, minor detail that every school should delete today.
(hat tip Bryan Carmody)
Inexperienced radiologists were significantly more likely to follow the suggestions of the purported AI when it incorrectly suggested a higher BI-RADS category than the actual ground truth compared with both moderately (mean degree of bias, 4.0 ± 1.8 vs 2.4 ± 1.5; P = .044; r = 0.46) and very (mean degree of bias, 4.0 ± 1.8 vs 1.2 ± 0.8; P = .009; r = 0.65) experienced readers.
Small but pretty clever study.
“Automation bias” is an insidious combination of anchoring and the authority fallacy, and it demonstrated a huge (though experience-mediated) effect here. We are still very much in the early days here (most radiologists are still very skeptical about the current powers of “AI” tools).
As machine learning tools grow in power and complexity, they will undoubtedly become a larger part of the radiology workflow. But counter to enabling inexperienced practitioners to function without oversight (e.g. a non-trained non-radiologist working independently with AI bypassing radiologists), we will instead need more robust skills: Raising the floor to miss fewer fractures and PEs is the easy part; it takes knowledge and experience to countermand the computer you increasingly rely on.
This isn’t going to be easy.