Perfection is a goal, one realistically never achieved.
I indulged in an ordered-in dinner last night, which culminated in a couple of fortune-cookies. The first said something like “Perfection will soon be yours.” Yikes, I thought, I sure hope not. Second fortune was much better: “You will learn quickly.”
Lest it need saying, I don’t consider fortune-cookies a reliable means of augury. I have, however, occasionally contemplated the notion of perfection and determined that under no circumstances do I want it for myself.
Folks reading my last few columns might already have figured out why: Perfection is a goal, one realistically never achieved. Set that excessively-high standard for yourself, and you can spend your whole life feeling like a failure.
Utilizing systems that move towards perfection, however, is far more satisfying. Every time you better yourself, you’re succeeding a little. Even learning you were wrong about something can be framed as a good experience, because you’ve identified that small imperfection in yourself and fixed it.
That’s why the second fortune appealed to me: Tell me I’ll learn quickly? You’re singing my song. If I’m a little embarrassed by an error I committed yesterday but won’t again, I consider a bruised ego an excellent price to pay for my incrementally-improved self.
On the other hand, suppose I somehow manage to achieve perfection, as threatened by the first fortune. Now I’m stuck. There’s no improvement to be had once I’m perfect; that’s the definition of the word. It’s the North Pole of quality, and everything’s south from there. At the peak of a mountain, one can only go down.
If perfect, the best you can do is maintain your status quo…but since the only constant is change, you’re almost certainly going to deteriorate. What a stressful struggle it will be, trying to maintain your position! Imagine being Superman, knowing that sooner or later you’re going to lose your powers.
Even if you can handle such a fall gracefully, others might not appreciate it when you do. Suppose you maintain a flawless QA profile for a quarter—heck, even a year. Or you wow everyone in your radgroup by completely cleaning up the worklist, whereas they’ve been accustomed to some nonemergent leftovers at the end of each day.
Then, at some point, you confirm that you are a mere mortal, and get a ding on your QA. Maybe a nitpick, maybe a genuine “miss.” Or the cases on your worklist get more numerous and/or complex, such that even you can’t make it through them all by day’s end. Perhaps you just get a little older and less energetic.
Maybe nobody notices…or they’re decent enough not to comment on it. Heck, you’re still pretty darned good. But maybe they’ve come to expect your perfection, and point out its absence: “Hey, buddy, you’re slipping.” Was that just a little good-natured ribbing, or did that have an edge to it? You’ll more likely perceive such an edge if you’re already uncomfortably aware and/or defensive of your lost perfection.
I’ve found I don’t need to achieve perfection to have such issues. Simply performing well and being ahead of the curve can have the same effect. We medical professionals are more than a little accustomed to competition, what with battling for rankings every step of the way from college through fellowship (and, in many instances, before and after). Slipping from 99th percentile to 95th probably feels awfully similar to losing perfection…to say nothing of dropping to the 50%-range.
That goes for less-quantifiable stuff, too. Things like RVUs and QA are commonly tracked, but consider things like your helpfulness and overall friendliness as a member of the team. A tech calls up with a protocol question, a colleague asks for a curbside-consult, an admin reaches out for some, well, administrative issue.
If historically you’re always perfectly available and happy to help, but today you’re swamped, grouchy, or otherwise at your limit, it’ll stand out to them a lot more strongly than if they approach Dr. Curmudgeon in the next reading-room, who’s always a troll and proceeds to act like one. It’s not fair that your superior track-record might wind up working against you…but I’ve written before about that particular F-word.
Perhaps for such reasons, I’ve adapted my behavior to serve as a sort of “perfection insurance.” Little things I say and do to emphasize my fallibility, even when I’m confidently doing well. I avoid excessive hedging, because that can undermine the value of my professional opinions…and I don’t get blatant with false humility, because sooner or later people can perceive that as game-playing and might resent it.
What I will do is say (or think) things like, “I could be wrong, but…” or “I’m about 80% sure that…” to keep myself grounded. Or I’ll substantiate why I am offering a particular opinion: “I saw a lesion like this a few years ago. Dug into some references, asked a colleague, and ultimately reported it was most probably diagnostic entity XYZ.” I thus “show my work” in how I came to my conclusion, including how imperfect it was, and let my audience determine for themselves the reliability of my input.
In the case of working alongside Dr. Troll, I might scale back on cheeriness and falling all over myself with eagerness to help. Not to the point I’m ornery and fearsome to approach—and certainly not so much that my professional value is reduced—but enough to remind that I’m human, too, and can have my imperfect moments. Maybe I tell the rad who’s curbsiding me about some frustrating interaction I had with a referrer. Or I apologetically say to the tech with the protocol-question that I’m momentarily overburdened, and will have to get back to him in a few minutes unless he thinks he can ask someone else sooner than that.
It occurs to me I probably shouldn’t have thrown out the “Perfection will soon be yours” fortune. If I ever stop working as a telerad, I might have blown it up, framed it, and put it on my future office wall. After crossing out “soon” and writing “never” in red marker. Could be a helpful visual aid to my visitors…and a reminder to myself.
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February 11th 2022Richard Duszak, MD, and Mina Makary, MD, discuss a number of issues, ranging from demographic trends and NPRPs to physician burnout and medical student recruitment, that figure to impact the radiology workforce now and in the near future.
New Study Examines Short-Term Consistency of Large Language Models in Radiology
November 22nd 2024While GPT-4 demonstrated higher overall accuracy than other large language models in answering ACR Diagnostic in Training Exam multiple-choice questions, researchers noted an eight percent decrease in GPT-4’s accuracy rate from the first month to the third month of the study.
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