CE Dojo

03/31/2026

Asymmetric Reporting

Not all information in a system flows equally.

And what gets reported… isn’t always what happened.

When we talk about “reporting,” this isn’t about charts or documentation.

It’s the everyday flow of information inside a practice:
what gets said
what gets repeated
what gets passed along

In many settings, that loop doesn’t end with the clinician.

It closes somewhere else.

By the time something reaches a point of decision, it’s often been filtered, simplified, or reshaped.

Not necessarily intentionally—just structurally.

Over time, the system begins to respond
not to what actually happened…
but to what was reported.

And those aren’t always the same.

That gap creates tension.

Because clinicians are still accountable for outcomes—
but don’t fully control the narrative that defines them.

This isn’t just communication.
It’s structure.

03/31/2026

I’ve been thinking a lot about the role of “wellness” in healthcare.

And I don’t think it’s as simple as we usually make it.

A lot of what we see—resilience training, mindfulness, support programs—is genuinely helpful.

But it also seems like it’s happening alongside increasing workload, not instead of it.

Which makes me wonder…

is wellness actually reducing pressure?

or helping us keep functioning under it?

Not a criticism—just something I’ve been thinking about.

03/29/2026

Control Mismatch

I’ve been thinking about something that shows up a lot in clinical practice, but we don’t always put words to it.

You’re responsible for the outcome…
but you don’t control all the inputs.

The schedule is set.
The pace is set.
Staffing, flow, timing—most of that is decided elsewhere.

But when something goes wrong, the responsibility doesn’t move with those decisions.

It stays with you.

Over time, that creates a kind of tension that’s hard to describe.

Not because people aren’t working hard.
Not because they don’t care.

But because they’re being held accountable for a system they don’t fully control.

I’m starting to think this is part of why “wellness” can feel so elusive in certain environments.

Not just an individual issue…
but something structural.

Curious if others have felt this, or see it differently.

03/29/2026

I’ve been thinking more about how AI is changing clinical workflow.

The obvious part is documentation—it’s getting easier, faster, less intrusive.

That’s been a real improvement.

But there’s another layer I didn’t fully appreciate at first.

When things get more efficient, they don’t usually slow down.

They speed up.

More patients.
More decisions.
Less time between them.

And then something subtle happens.

The increased pace doesn’t just get expected…
it starts to get rewarded.

At that point, it’s not just external pressure anymore.

You’re incentivized to operate at that level.

Which raises a question I don’t think we talk about enough:

If efficiency gains are always tied to more output…
does anything ever actually slow things down?

Or does the baseline just keep moving?

03/28/2026

I’ve been experimenting with AI scribes in my clinical workflow lately.

One thing I didn’t expect…

It doesn’t just save time.

It changes how you experience the patient encounter.

When documentation fades into the background, you can actually stay fully present.

And that part has been great.

But it also got me thinking…

If AI starts helping not just with notes—but with decision-making too—
what happens then?

Because the system doesn’t slow down.
It speeds up.

More patients.
More decisions.
Less time between them.

At some point, the limiting factor isn’t the chart…

it’s us.

03/26/2026

Most dentists are still doing notes the same way we did 10 years ago…

Typing. Clicking. Finishing charts at night.

AI scribes are starting to change that.

But here’s the part I think matters more:

AI doesn’t actually reduce work.
It creates time.

And what happens to that time depends on your practice model.

In a corporate setting, that extra time often turns into:
➡️ more patients
➡️ tighter schedules
➡️ higher production expectations

In an independent practice… it can look very different:
➡️ more time with patients
➡️ better documentation
➡️ getting home earlier
➡️ or yes—more production (if you want it)

Same tool.
Very different outcome.

So maybe the real question isn’t “Do AI scribes work?”

It’s:

👉 Who controls what happens after they do?

Curious—anyone here actually using one yet?

03/25/2026

I came across a post about AI scribes being used to reduce physician burnout.

On the surface, that sounds like a great thing.

But it got me thinking…

If documentation is no longer the bottleneck, what happens next?

In most systems, that time doesn’t come back to the clinician—it gets turned into more patient volume.

So instead of reducing workload, we may just be shifting it.

From physical work (charting, typing)…
to cognitive work (decision-making, back-to-back cases, mental fatigue).

There’s only so many complex encounters you can process in a row before something starts to give.

Which raises a bigger question:

Can clinician wellness really improve in a system that keeps resetting expectations as efficiency increases?

03/24/2026

AI-Adjusted Standard of Care (AASC) — Part 2

After the last post, a few people asked a very reasonable question:

“What does that actually mean?”

Traditionally, standard of care is defined by:

training
experience
peer behavior
expert testimony

It evolves slowly.

But AI introduces something new:

→ real-time pattern recognition
→ population-level data
→ continuous feedback

Now imagine this:

An AI system can show that:

78% of comparable cases are treated one way
Complication rates drop when protocol X is followed
Certain deviations correlate with higher risk

At that point, something subtle happens.

The “standard” is no longer just:
→ what clinicians say

It becomes:
→ what the data shows

This doesn’t eliminate clinical judgment.

But it does change the environment around it.

Deviation becomes visible
Variation becomes measurable
Decisions become comparable

And that raises a harder question:

If AI can define what is “typical”…
does it begin to define what is “acceptable”?

We’re not there yet.

But we’re closer than most people think.

And the systems we build now will determine:

→ whether AI supports clinical judgment
or
→ quietly replaces it

More on that next.

03/24/2026

I posted that AI could give solo dentists the operational power of a DSO.

The reaction from dentists was immediate—and not subtle.

→ “This is just corporate dentistry with a new face.”
→ “You’re replacing one master with another.”
→ “Who controls the algorithm controls everything.”

That reaction is the signal.

Because what’s being challenged isn’t just technology.

It’s control.

For years, the tradeoff has been clear: → Join a system → gain efficiency, lose autonomy
→ Stay independent → keep autonomy, lose scale

AI changes that equation.

It can give independent practices:

operational infrastructure

data advantages

negotiating leverage

Without requiring ownership consolidation.

But the pushback reveals something deeper:

Dentistry isn’t resisting AI.

It’s resisting who controls it.

Because if the system defines the standard…

Then independence becomes a question, not a fact.

Curious how others see this.

Is AI going to empower independent practice…

Or just redefine control in a more subtle way?

03/24/2026

I’ve been spending some time thinking about substance use disorders in healthcare professionals—an area that is receiving much-needed attention.

One dimension I’ve been reflecting on is the potential role of underlying metabolic dysfunction in shaping addictive behaviors.

There is growing discussion around whether disruptions in energy regulation and glucose metabolism may influence reward pathways—not just in alcohol use, but potentially across a broader spectrum of behaviors.

If that connection proves meaningful, it may broaden how we think about both risk and treatment—shifting part of the conversation from purely behavioral frameworks to more integrated biological models.

Still early, but an interesting area to watch as our understanding evolves.

03/20/2026

When in worry or in doubt...

02/09/2026

North Carolina Dental Society Sedation is becoming more difficult in practice - why and what can be done.

Sedation is getting harder — and dentistry is feeling it.
Patients increasingly require higher doses and respond less predictably to moderate sedation. That’s not a training failure or a professionalism issue — it reflects a changed patient population.

As tolerance rises, moderate sedation drifts from a boundary-based model (“some patients don’t belong here”) to a push-through model (“add more, keep going”). Rules, simulation, and additional agents may look like safety, but they can’t replace the judgment that comes from residency-level anesthesia training. Sedation safety has always depended on knowing when to stop.

Check out our blog post 👉 https://ce-dojo.com/why-dental-sedation-is-getting-harder-and-why-pushing-through-is-the-wrong-response/