Tuesday, August 18, 2026

Mark and Madi Turley: Two Preemies, 30 Years Apart—and What Their Story Reveals About the Broken Translation Between Medicine and Money

The patient’s story begins in the exam room. Somewhere between clinical care and the claim, we keep losing it.



“The white coat symbolizes the other critical part of students’ medical education, a standard of professionalism and caring and an emblem of the trust they must earn from patients.”American Medical Association, 2026


A baby survived. Then the paperwork began.

In 1975, Mark Turley was born seven weeks premature.

Doctors gave him roughly a 50–50 chance of survival.

More than three decades later, Mark and his wife, Kennetha Turley, found themselves confronting a nightmare that felt strangely familiar.

Their daughter, Madi Turley, was born at only 24 weeks.

She was tiny.

Very tiny.

She spent 66 days in the NICU and faced serious medical complications. Her medical journey continued long after she left the hospital, with more than 200 days in hospitals during her early childhood and years of therapy.

The Turley family's story is remarkable because Madi survived.

But that isn't where the story ends.

Today, Madi is an adult and a drag racer.

The little girl who once fought simply to stay alive found confidence behind the wheel.

Her story is a reminder of what healthcare is ultimately supposed to accomplish.

Not merely keeping someone alive today.

Giving them a chance to live tomorrow.

And that is where I want to make an uncomfortable leap.

Because I think this story has something important to teach us about medical billing.

At first glance, it has nothing to do with billing.

And that's exactly why it does.


The patient doesn't know where the exam room ends

When a physician sees a patient, the physician sees a person.

A story.

Symptoms.

History.

Risk.

Context.

Sometimes fear.

Sometimes hope.

Sometimes a family sitting quietly in the corner pretending not to be terrified.

The physician makes decisions.

The nurse documents.

The team coordinates care.

Then the patient leaves.

And the healthcare machine changes languages.

The patient's story becomes:

ICD-10.

CPT.

HCPCS.

Modifiers.

Eligibility.

Authorization.

Claim edits.

Payer rules.

Medical necessity.

Adjudication.

Denial codes.

The patient says:

“I need help.”

The physician says:

“Here is what I believe is medically appropriate.”

The billing system says:

“Invalid.”

That translation gap is one of the least discussed problems in American healthcare.

And I think it is becoming one of the most important.


My contrarian take

Medical billing is not primarily a collections problem.

It is an information problem.

More specifically, it is a translation problem.

Clinical medicine produces rich, contextual information.

Financial systems require structured information.

Somewhere between the two, meaning gets lost.

A physician documents a complex clinical encounter.

A coder interprets it.

A billing system converts it.

A clearinghouse checks it.

A payer applies its rules.

Then someone receives a denial.

And everyone acts surprised.

Why?

We shouldn't be.

We built a healthcare system where the same patient story is repeatedly translated by different people, different systems and different rule sets.

Then we wonder why things get lost in translation.


And then we call it a denial problem

This is where I think healthcare has gotten the diagnosis wrong.

A denial is often treated as the problem.

It isn't always the problem.

Sometimes the denial is simply the symptom.

The real problem happened earlier.

Maybe the documentation didn't clearly support the service.

Maybe coding did not accurately reflect the documentation.

Maybe the payer's requirements were not known at the point of care.

Maybe authorization was missed.

Maybe information existed in the EHR but wasn't structured in a way the downstream system could use.

Maybe the claim contained an error that could have been caught before submission.

Then the denial arrives.

And we call the billing department.

Someone works the account.

Someone calls the payer.

Someone submits an appeal.

Someone waits.

Someone calls again.

Eventually, the claim gets paid.

Everyone celebrates.

I have a slightly different reaction.

Why did we need the appeal in the first place?


We celebrate recovery when we should celebrate prevention

Healthcare loves heroic recovery stories.

We celebrate the physician who saves the patient.

The surgeon who performs the impossible operation.

The nurse who catches the subtle deterioration.

The emergency team that acts in seconds.

We should.

But there is another kind of healthcare heroism that receives much less attention:

preventing the problem before anyone notices it.

A clean claim doesn't make headlines.

A prevented denial doesn't get a standing ovation.

A payer requirement correctly identified before the visit isn't exactly cinematic.

Nobody makes a documentary about:

“Local medical practice submits accurate claim. Nobody has to call anyone.”

Yet that is precisely the kind of boring success we should want more of.


Boring is beautiful

Physicians understand this.

The best clinical workflow is often the one you barely notice.

The medication reconciliation happens.

The allergy is caught.

The right test gets ordered.

The documentation is complete.

The referral goes where it needs to go.

The patient receives the care.

No drama.

No heroics.

No midnight phone call.

Healthcare operations should aspire to the same thing.

The best revenue cycle should be boring.

No drama.

No mystery.

No endless payer phone trees.

No staff member whispering:

“I'm going to try calling them again.”

No physician staring at a denial wondering what happened.

No CEO discovering six months later that an entire category of claims has been underpaid.

Just:

right information → right workflow → right claim → right payment.

That sounds almost ridiculously simple.

Which probably means it is harder than it sounds.


The numbers are telling us something

The latest AMA data should make every physician owner stop for a moment.

Physicians report completing an average of 40 prior authorizations per week.

That workload consumes approximately 13 hours of physician and staff time each week.

40% of physicians report having staff dedicated exclusively to prior authorization.

And 94% say prior authorization contributes to burnout.

Let me translate that into practice-owner language.

Thirteen hours isn't a statistic.

It's Tuesday afternoon.

It's Wednesday morning.

It's someone's lunch break.

It's another employee.

It's the physician finishing charts at 8:00 p.m.

It's the staff member who came into medicine because they wanted to help people spending half the day navigating payer requirements.

And this is not just an inconvenience.

The AMA reports that 95% of physicians say prior authorization delays access to necessary care, while 92% say it negatively affects clinical outcomes.

That is no longer a back-office conversation.


The strangest part: we keep adding technology to the same broken workflow

Now comes the part where I will probably annoy some people in healthcare technology.

Everyone wants to put AI into the revenue cycle.

Fine.

But here is my question:

What if we are putting AI in the wrong place?

If the workflow is broken, AI can automate the broken workflow.

Congratulations.

Now it breaks faster.

That is not transformation.

That's high-speed inefficiency.

We have to be careful not to confuse automation with improvement.

A faster bad process is still a bad process.

A beautifully designed dashboard showing 17 different types of denials does not fix the fact that the practice is generating the same preventable denials every week.

A chatbot that tells staff what to do after a denial is useful.

But I would rather build a system that helps prevent the denial.

That is a very different philosophy.


AI shouldn't be the hero

This is another contrarian point.

I don't think the future of healthcare billing is:

AI replaces billing staff.

I don't think that is particularly interesting.

The better future is:

AI makes billing staff less necessary for repetitive work and more valuable for complex work.

That means AI handles pattern recognition.

AI handles repetitive checks.

AI identifies anomalies.

AI surfaces payer-specific requirements.

AI connects information.

AI prioritizes work.

Humans handle:

judgment.

exceptions.

relationships.

ambiguity.

escalation.

clinical nuance.

compliance oversight.

That is much more realistic.

And much safer.


The real opportunity is upstream

This is where my own thinking about OnnX begins.

I believe the highest-value place to intervene is before the claim exists.

Not after the denial.

Before it.

Think about the chain:

Patient → Clinical Encounter → Documentation → Coding → Payer Requirements → Claim → Adjudication → Payment

Most traditional revenue-cycle technology concentrates heavily toward the right side.

Claim.

Denial.

A/R.

Appeal.

Collections.

But the information that determines the quality of that claim often originates much earlier.

At the clinical encounter.

That is why I keep coming back to one phrase:

Precision at the Source.

If we can improve the quality and structure of information at the point where it is created, we have a better chance of improving everything downstream.


The patient is telling one story

Here is the philosophical problem.

The patient tells one story.

Healthcare turns it into dozens of data objects.

The patient says:

“My knee hurts. I fell. I can't sleep. I can't work. I tried physical therapy. It's getting worse.”

The physician interprets that story clinically.

The EHR records it.

The coder translates it.

The payer evaluates it.

The billing system processes it.

The patient gets a bill.

Everyone is working from the same patient.

But not necessarily from the same representation of the patient.

That is the problem.


Clinical-to-financial intelligence

This is why I believe healthcare needs something beyond conventional revenue-cycle automation.

We need better clinical-to-financial intelligence.

The phrase sounds complicated.

The idea isn't.

It means connecting the clinical reality of what happened to the administrative and financial requirements needed to process it.

The physician shouldn't have to become a billing expert.

The coder shouldn't have to reconstruct the clinical story from fragments.

The billing staff shouldn't have to discover payer requirements after the claim is rejected.

The technology should help connect those dots.

That is the opportunity.


And healthcare is finally moving toward the problem

This isn't just my opinion.

The AMA announced in July 2026 an initiative focused on mapping SNOMED CT clinical concepts to CPT terminology specifically to help EHRs and payer systems communicate more effectively during prior authorization.

That is significant.

Why?

Because it acknowledges something fundamental:

clinical language and administrative language do not naturally speak to each other.

Someone—or something—has to translate.

Today, that translator is often a human being.

Usually a very tired human being.


We have built a human middleware layer

Think about that.

Healthcare has created an enormous workforce whose job is essentially:

translate one healthcare system into another healthcare system.

The physician documents.

The staff interprets.

The coder translates.

The biller corrects.

The authorization specialist negotiates.

The payer reviews.

Then someone sends an appeal.

This is human middleware.

And it is expensive.

Very expensive.

Not just financially.

Human attention is one of the scarcest resources in medicine.

We should be extremely careful about wasting it.


The small-practice problem

Large health systems can sometimes absorb administrative complexity through scale.

Independent practices cannot.

A large organization may have:

authorization teams.

coding departments.

compliance officers.

revenue-cycle executives.

analytics teams.

IT departments.

legal teams.

specialized payer contracts.

A five-physician practice?

Maybe it has one office manager who knows everything.

And if she goes on vacation?

Everyone discovers what "mission critical infrastructure" really means.

That is not a joke.

It is an operating model.

Small practices often depend on institutional knowledge trapped inside individual people.

That is dangerous.

What happens when the person who knows how to handle Payer X leaves?

What happens when the billing specialist retires?

What happens when the payer changes a requirement?

What happens when claim volume doubles?

The practice needs institutional intelligence—not just institutional memory.


This is where technology should help

The goal should not be to turn a small practice into a miniature health system.

The goal should be to give the small practice the intelligence of a much larger organization without the overhead.

That means:

Payer intelligence.

Workflow intelligence.

Coding intelligence.

Denial intelligence.

Documentation intelligence.

Revenue intelligence.

But these should not exist as six disconnected dashboards.

They should work together.


The best question to ask about any healthcare technology

Forget the demo for a moment.

Forget the AI.

Forget the shiny interface.

Ask:

What work disappears?

That's my favorite technology question.

Not:

“How many features do you have?”

Not:

“Is it AI-powered?”

Not:

“Does it have predictive analytics?”

Ask:

What does my staff stop doing?

Then ask:

What does my physician stop doing?

Then:

What error stops happening?

Then:

What happens earlier than it does today?

Those questions get you much closer to ROI.


Five questions before buying an AI billing platform

1. Does it prevent or merely recover?

If the system mainly helps after the denial, it may be useful.

If it can prevent the denial, that is potentially much more valuable.

 

2. Does it understand the clinical context?

Billing cannot be separated completely from clinical documentation.

If the system sees only billing codes, it is missing part of the story.

 

3. Can it explain itself?

If it recommends something, ask:

Why?

If nobody can answer, be cautious.

Healthcare is not the place for:

“Trust the algorithm.”

 

4. Does it fit the workflow?

If staff have to open another application, copy information, paste information, log in again and manually reconcile results, you may not have automation.

You may have another job.

 

5. Does it learn?

A good revenue cycle should become smarter over time.

If the same payer rejects the same type of claim repeatedly, the system should learn from the pattern.

Otherwise, you're paying humans to rediscover the same lesson forever.


My favorite healthcare metric may be the one nobody reports

Physician hours returned.

We obsess over:

days in A/R.

clean claim rate.

denial rate.

collection rate.

gross charges.

net collections.

Those are important.

But I would add:

Physician Administrative Hours Returned

Because physician time is not inventory.

You can't manufacture more of it.

If technology saves a physician two hours a week, that isn't merely a productivity metric.

That's:

two more hours with patients.

two more hours with family.

two more hours sleeping.

two more hours thinking.

two more hours being a human being.

That matters.


The hidden ROI of administrative simplicity

Suppose a practice saves:

5 hours of staff time per week.

2 hours of physician time per week.

10% of avoidable denials.

3 days of A/R.

That doesn't sound revolutionary.

But multiply it by 52 weeks.

Then by multiple physicians.

Then by multiple years.

Suddenly the boring improvements become strategic.

That's how healthcare transformation usually works.

Not one giant breakthrough.

A thousand small frictions removed.


A practical revenue-cycle audit for physicians

If I were walking into your practice tomorrow, I would start with one patient journey.

Not a dashboard.

A patient.

Follow the encounter from:

appointment → eligibility → visit → documentation → coding → authorization → claim → adjudication → payment.

Write down every human touch.

Every handoff.

Every delay.

Every correction.

Every phone call.

Every duplicate entry.

Then ask:

Why?

Not:

“Who made the mistake?”

Ask:

Why did the system allow the mistake?

That changes the conversation from blame to design.


Step 1: Find the recurring pain

Take the last 90 days.

Find your most common denials.

Not the most expensive.

The most common.

Frequency reveals workflow problems.

 

Step 2: Find the expensive pain

Now identify the denials with the largest financial impact.

A small number of high-dollar problems can matter more than hundreds of minor issues.

 

Step 3: Find the human cost

How many hours are spent fixing them?

This is where many practices stop too early.

They measure dollars.

They don't measure time.

Track both.

 

Step 4: Find the earliest intervention point

For every major denial ask:

When could we have known this was going to happen?

Before scheduling?

At eligibility?

During the encounter?

During documentation?

During coding?

Before submission?

The earlier you can identify the problem, the cheaper it usually is to fix.

 

Step 5: Create a denial taxonomy

Stop using “denial” as a single bucket.

Separate:

eligibility

authorization

coding

documentation

medical necessity

payer processing

demographics

timely filing

coordination of benefits

missing information

Now you can see patterns.

 

Step 6: Close the loop

Every meaningful denial should answer two questions:

What happened?

and

What should we change so it happens less often?

If your revenue-cycle team only answers the first question, you have a recovery department.

If it answers both, you have a learning system.

 

Step 7: Automate selectively

Automate what is:

repetitive

well-defined

measurable

low ambiguity

high volume

Be more cautious with tasks involving:

clinical judgment

uncertain documentation

exceptions

legal interpretation

high-risk financial decisions

The goal isn't maximum automation.

It's appropriate automation.


The myth that automation means no humans

Let's kill this one.

I don't want a healthcare system with no humans.

I want a healthcare system where humans spend their time on things that require humans.

That's different.

A good AI system should allow a billing specialist to spend less time checking 200 identical claims and more time solving the one complicated claim that actually needs expertise.

That's augmentation.

Not replacement.


Myth: More technology means less complexity

Not necessarily.

Healthcare has a talent for taking one fax machine and replacing it with:

three portals,

two logins,

an API,

a dashboard,

an inbox,

and a notification saying:

“Action required.”

We didn't eliminate the fax.

We gave it friends.

Technology is not the solution if it adds another layer.

The goal is fewer steps, not more software.


Myth: Denials are just part of doing business

This one bothers me.

Some denials are unavoidable.

Healthcare is complicated.

Payers have legitimate utilization-management functions.

Patients change insurance.

Eligibility changes.

Contracts differ.

Mistakes happen.

Fine.

But “some denials are inevitable” does not mean:

“Preventable denials are acceptable.”

Those are very different statements.


Myth: The billing department owns the revenue cycle

No.

The revenue cycle begins long before billing.

It begins with:

registration.

Then:

eligibility.

Then:

clinical documentation.

Then:

coding.

Then:

authorization.

Then:

claim preparation.

Then:

submission.

Then:

payment.

Then:

reconciliation.

Then:

learning.

That is a practice-wide system.


Myth: AI automatically makes the system smarter

AI can make a system smarter.

It can also make a bad system faster.

That distinction matters.

Before adding AI, ask whether you understand the workflow well enough to know:

What should be automated?

What should remain human?

What data are reliable?

What exceptions exist?

How will performance be measured?

How will errors be detected?

What happens when the model is wrong?

If you don't know those answers, you're not ready to automate.

You're ready to experiment.

Those are not the same thing.


The legal problem

There is another uncomfortable reality.

Healthcare billing is not a playground.

Automated systems operate in an environment involving:

HIPAA

Medicare and Medicaid requirements

payer contracts

coding rules

documentation requirements

fraud and abuse laws

False Claims Act exposure

overpayment obligations

and numerous federal and state requirements.

AI does not change those obligations.

If anything, automation can make governance more important.

A physician owner should know:

Who approved the workflow?

What data does the system use?

Who can change the rules?

How are recommendations audited?

How are errors corrected?

What happens when the system disagrees with the physician or coder?

Where is the audit trail?

If nobody can answer those questions, the system isn't ready for high-stakes automation.


Ethical considerations

The objective of revenue-cycle technology should never be:

maximize reimbursement at any cost.

It should be:

accurate reimbursement for appropriate care.

That means technology should never become an excuse for:

upcoding.

unsupported documentation.

fabricated clinical information.

inappropriate medical-necessity assertions.

automated manipulation.

Patients deserve transparency.

Physicians deserve control.

Payers deserve accurate information.

And practices deserve to be paid appropriately for legitimate care.

That's the ethical center of the problem.


The black-box problem

I have a simple rule:

If the system makes a consequential recommendation, I want to know why.

If the system says:

“This claim is likely to be denied.”

Great.

Tell me why.

If it says:

“This documentation may not support the code.”

Fine.

Show me the issue.

If it says:

“Change the code.”

I want evidence.

Healthcare AI needs explainability, especially when its output can affect reimbursement, documentation or patient access.

A black box may be impressive.

But impressive isn't the same as trustworthy.


The recent news that matters

There is an important shift happening right now.

The conversation is moving from:

“Should we digitize prior authorization?”

to:

“Can the systems actually understand each other?”

The AMA's July 2026 initiative to connect SNOMED CT clinical concepts with CPT terminology is a good example. The stated goal is to help bridge the gap between clinical information in the EHR and the coding information required by payers for authorization workflows.

That matters because merely moving a paper form onto a screen doesn't necessarily eliminate the work.

You can create a beautiful electronic version of a terrible process.

Congratulations.

You now have digital bureaucracy.

The harder problem is interoperability of meaning.


And prior authorization reform is still unfinished

The AMA reports that only one in three physicians believes insurer commitments will make a meaningful difference.

Meanwhile, physicians report:

40 prior authorizations per week.

13 hours of physician/staff time.

94% saying PA contributes to burnout.

32% reporting that requests are often or always denied.

74% saying denials have increased over five years.

This is why physician owners should not wait for Washington, insurers or technology vendors to solve every operational problem.

Some reforms require policy.

Some require payer behavior to change.

But some problems can be addressed inside the practice.

That is where operational intelligence matters.


The bigger healthcare lesson

Let's go back to Mark and Madi Turley.

Mark survived prematurity.

Then, decades later, his daughter faced an even more difficult beginning.

Their family experienced healthcare at its most human.

Doctors.

Nurses.

NICU teams.

Therapists.

Hospitals.

Years of care.

The ultimate measure wasn't a claim.

It wasn't an A/R report.

It wasn't a denial rate.

It was Madi eventually getting to live.

That's the point I want healthcare leaders to remember.

The administrative system exists to support the care system.

Not the other way around.

When administrative machinery becomes so complicated that it consumes the people delivering care, something has gone backward.


What I think the future looks like

I don't think the future medical practice will eliminate billing staff.

I don't think AI will eliminate payers.

I don't think claims will disappear.

I don't think healthcare will suddenly become simple.

I do think something more interesting can happen.

The revenue cycle can become predictive instead of reactive.

Instead of:

“This claim was denied.”

We move toward:

“This claim has a high probability of denial. Here's why. Here's what can be corrected before submission.”

Instead of:

“The payer requested documentation.”

We move toward:

“This documentation requirement is likely to apply. Here's what is missing.”

Instead of:

“The practice discovered a recurring denial.”

We move toward:

“The system detected a recurring payer pattern and recommends an upstream workflow change.”

That's a different revenue cycle.

It is not simply automated.

It is intelligent.


What OnnX is trying to build

This is the thinking behind OnnX.

I founded OnnX around a simple observation:

Small and medium-sized physician practices should not need an army of intermediaries to get paid accurately for the care they already delivered.

The opportunity isn't merely to build another billing tool.

It is to rethink the revenue cycle as an interconnected operating system.

An AI Revenue Cycle OS should help connect:

clinical documentation

to

coding

to

payer intelligence

to

claim optimization

to

denial prevention

to

revenue intelligence.

The goal is not to make physicians think more about billing.

It is to make physicians think less about billing.

That distinction is everything.


What I would build if I were starting a practice today

I would build around five principles.

1. Capture information once

Every unnecessary re-entry is an opportunity for error.

 

2. Put intelligence as close to the source as possible

Don't wait until the denial.

 

3. Make every recommendation explainable

No mysterious black boxes.

 

4. Measure time as aggressively as money

Because physician and staff attention are economic resources.

 

5. Design for the exception

Automation handles the routine.

Humans handle what is unusual.

That's where people add value.


The practice of the future may be smaller, not bigger

This is one of my favorite contrarian ideas.

We often assume healthcare organizations need to become larger to survive.

Maybe.

But another possibility exists.

What if technology allows a small physician practice to operate with the sophistication of a much larger organization?

Imagine a five-physician practice with:

real-time payer intelligence.

automated claim validation.

denial prediction.

coding support.

documentation intelligence.

workflow orchestration.

A/R prioritization.

Payment reconciliation.

Analytics.

Without building a 30-person administrative department.

That is interesting.

Because technology could potentially make independence more viable, not less.


The future competitive advantage may be administrative simplicity

Physicians already compete for patients.

They compete for staff.

They compete for time.

They compete for margins.

They compete for independence.

Soon, they may increasingly compete on something less obvious:

operational simplicity.

A practice that can deliver excellent medicine while generating less administrative friction has a structural advantage.

Its physicians may have more capacity.

Its staff may have less burnout.

Its cash flow may be more predictable.

Its patient experience may be better.

Its owner may have more time to actually run the business.

That is not glamorous.

It is strategic.


A challenge for physician owners

I want to challenge you to do something this week.

Don't buy anything.

Don't install anything.

Don't call a vendor.

Just measure.

Take one week.

Track:

How many hours did physicians spend on administrative work?

How many hours did staff spend on denials?

How many claims required correction?

What were the top three denial reasons?

How many payer calls occurred?

How many prior authorizations were submitted?

How many were denied?

How much revenue was delayed?

Then ask one question:

“Which of these problems should never have reached a human?”

That is where your opportunity is.


The five numbers I would put on every practice dashboard

Not 50.

Five.

1. Preventable denial rate

Not just denial rate.

Preventable denial rate.

 

2. First-pass claim success

How often does the claim move through without human repair?

 

3. Days to payment

Speed matters.

 

4. Administrative hours per 100 encounters

This tells you how much operational friction surrounds care.

 

5. Physician administrative hours

Because if that number is rising, something is wrong.


The question nobody asks after buying software

Here's another uncomfortable question:

Did the software actually make the practice simpler?

Not:

Did people log in?

Not:

Did usage increase?

Not:

Did we create reports?

Not:

Did the dashboard look good?

Ask:

Did work disappear?

If not, the technology may be measuring the problem rather than solving it.


Three lessons I would take from the Turley family's story

Lesson 1: Healthcare is longitudinal

The hospital sees an encounter.

The family experiences a lifetime.

 

Lesson 2: The outcome is bigger than the transaction

A claim is not the end goal.

The patient's life is.

 

Lesson 3: Every administrative hour has a human consequence

Someone is paying for that hour.

A physician.

A nurse.

A biller.

A patient.

A family.

A practice owner.

Often, all of them.


The uncomfortable truth about healthcare innovation

Healthcare doesn't need more technology for technology's sake.

It needs less friction.

We don't need another AI logo.

We need fewer phone calls.

We don't need another dashboard.

We need fewer denials.

We don't need another workflow.

We need fewer workflows.

We don't need another portal.

We need fewer passwords.

And we definitely don't need a chatbot telling a tired physician that their claim has been denied.

We need the system to say:

“We caught the problem before it left the practice.”

Now that's innovation.


Final Thoughts

Mark Turley survived when medicine wasn't nearly as advanced as it is today.

Decades later, his daughter Madi Turley faced her own extraordinary medical battle.

Medicine did what medicine is supposed to do.

It gave them a chance.

Then life took over.

That is what makes their story so powerful.

Healthcare is ultimately measured in the lives that happen after the encounter.

That should change how we think about everything surrounding the encounter.

Billing isn't the mission.

Authorization isn't the mission.

Coding isn't the mission.

Technology isn't the mission.

They are infrastructure.

The mission is the patient.

And if our infrastructure consumes the time, attention and energy of the people caring for that patient, we should have the courage to redesign it.

My contrarian view is simple:

The future of medical billing isn't more aggressive collections.

It is better information, earlier.

It is prevention instead of repair.

It is clinical intelligence connected to financial intelligence.

It is technology that disappears into the workflow instead of creating another workflow.

And perhaps most importantly:

It is giving physicians back the time they never should have lost in the first place.


Get Involved

I don't think physicians need another lecture about how broken healthcare is.

We already know.

The more interesting conversation is:

What are we going to redesign?

So I want to hear from you.

What is the single administrative task in your practice that makes you think, “Why are humans still doing this?”

Tell me in the comments.

If you've solved part of the problem, share what worked.

If you've failed at solving it, share that too.

Failure is data.

And if this perspective resonates with you, repost this article so another physician or clinic owner can join the conversation.

We don't need everyone to agree.

We need more people willing to question the status quo.

Ask better questions.

Share what you are learning.

Help build a healthcare system where administrative infrastructure serves medicine instead of competing with it.

That is where I believe the real opportunity is.


Continue the Conversation

The healthcare conversation doesn't end with one article.

I write about the intersection of medicine, healthcare operations, medical billing, technology, physician entrepreneurship and innovation.

My goal is straightforward:

Make complicated healthcare problems easier to understand—and harder to ignore.

Explore more practical ideas, operating lessons and perspectives on where healthcare may be headed.

Knowledge becomes valuable when it changes what we do next.

Visit my website:
Dr. Daniel Cham's website

Listen to the podcast on Spotify:
Dr. Cham on Spotify

Subscribe on YouTube:
Dr. Cham on YouTube

Follow me on X:
Dr. Cham on X

Follow on Facebook:
Dr. Cham on Facebook

Start with one question. Follow the friction. Find the root cause. Build something better.


Free Resource

PS: Visit the Featured section of my LinkedIn profile for a free resource. No signup required.

If you're a physician or clinic owner dealing with medical billing, denials, prior authorization, administrative overload or revenue-cycle problems, take a look.

And if you think I missed something, tell me.

The people closest to the problem usually know the most about the solution.


About the Author

Dr. Daniel Cham is a physician, healthcare entrepreneur and medical technology consultant focused on the intersection of clinical practice, healthcare operations, medical billing and technology.

He is the founder of OnnX, an AI-powered medical billing platform focused on helping small and medium-sized physician practices reduce administrative friction and improve the connection between clinical documentation and revenue-cycle performance.

His perspective comes from looking at healthcare from both sides:

the medicine and the machinery surrounding the medicine.

His work focuses on one central question:

How can technology help physicians spend more of their finite time practicing medicine—and less time fighting the infrastructure surrounding it?


Connect with Dr. Daniel Cham


Disclaimer

This article is provided for general educational and informational purposes only. It does not constitute medical, legal, coding, compliance, reimbursement or financial advice.

Healthcare regulations, payer policies, contracts and coding requirements vary and change over time. Readers should seek qualified professional advice for circumstances specific to their practice, organization or patients.


References

1. American Medical Association — 2026 Prior Authorization Physician Survey
The AMA's latest survey documents the continuing burden of prior authorization, including approximately 40 requests per physician each week, 13 hours of physician/staff time and significant reported effects on burnout and patient care.
Read the AMA findings

2. American Medical Association — SNOMED CT to CPT Mapping Initiative
The AMA's July 2026 initiative addresses the disconnect between clinical concepts in EHRs and administrative coding requirements used in prior authorization.
Read the AMA initiative

3. CAQH — 2025 CAQH Index
The latest CAQH Index reports that U.S. healthcare avoided an estimated $258 billion in administrative costs through electronic transactions and improved data exchange, while identifying an additional $21 billion savings opportunity.
Explore the 2025 CAQH Index findings


One Last Question

Madi Turley survived because medicine worked.

But medicine is surrounded by systems that often don't work nearly as well.

So here is my question for every physician owner:

If you could eliminate one administrative task from your practice tomorrow, what would it be—and why hasn't someone eliminated it already?

Leave your answer below.

Your frustration might be someone else's product idea.

Your workaround might be someone else's breakthrough.

And your story might help another physician realize they are not the only one fighting the same battle.

#Healthcare #MedicalBilling #RevenueCycleManagement #PhysicianPractice #HealthcareInnovation #HealthTech #HealthcareAI #PhysicianEntrepreneur #MedicalPracticeManagement #HealthcareLeadership #PriorAuthorization #ClaimDenials #IndependentPractice #HealthcareOperations #ClinicalDocumentation #OnnX

If this perspective resonates, repost it. Someone in your network may be spending 13 hours this week solving a problem that should have been prevented.

 

Monday, August 17, 2026

THE OTHER 166 HOURS

ONE WIFE, ONE PATIENT, AND THE HIDDEN LABOR OF AMERICAN HEALTHCARE



“Our care is better for patients when we don't feel burned out. We make fewer mistakes when we don't feel burned out.” — Christine Sinsky, MD, American Medical Association

Source: American Medical Association, Addressing the rapid rise in physician burnout revealed by a new study.


There is a sentence in healthcare that sounds comforting until you actually have to live with it:

“You're going home with services.”

Sounds good.

Almost luxurious.

Services.

Plural.

It has the ring of a concierge package.

Then you get home.

And discover that “services” may mean a nurse comes once a week.

A physical therapist comes once a week.

And your spouse becomes the rest of the healthcare system.

That is the story of an unnamed husband and wife featured in a recent 24/7 Wall St. report.

The husband went home needing help with wound care, medications, mobility, meals, bathing and the ordinary things that suddenly become extraordinarily difficult when someone is sick.

A home-health nurse came once a week.

A physical therapist came once a week.

Everything else belonged to his wife.

The article put the arithmetic bluntly:

168 hours in a week.

Professional home-health visits covered roughly two.

His wife was effectively responsible for the other 166 hours.

No dramatic operating room.

No billionaire startup.

No breakthrough drug.

No shiny AI robot.

Just a husband.

A wife.

A walker.

A medication schedule.

A 3 a.m. bathroom trip.

And a healthcare system that technically did what it promised.

That last part is what interests me.

Because the system wasn't necessarily lying.

It was simply defining “care” much more narrowly than the family experienced it.

And that should make every physician and clinic owner stop for a moment.

Because we have our own version of the Other 166 Hours Problem.

It happens after the patient leaves the exam room.


THE PATIENT LEFT.

THE WORK DIDN'T.

A physician sees a patient.

Maybe 15 minutes.

Maybe 30.

Maybe an hour for a complicated visit.

The patient leaves.

The door closes.

The physician moves to the next patient.

But somewhere behind the scenes, another patient is born.

The administrative patient.

This one has an insurance ID.

A CPT code.

An ICD-10 code.

A modifier.

A payer.

A claim number.

A status.

A denial code.

A deadline.

And eventually, perhaps, an appeal.

Nobody invited this patient.

But suddenly your staff is spending 20 minutes taking care of it.

Then 40.

Then an hour.

Sometimes the physician gets involved.

Someone says:

“Doctor, the insurance company wants more information.”

You sigh.

You open the chart.

You look at the note.

You wonder why the payer couldn't simply read what you already documented.

Then you remember:

Because apparently the healthcare system has invented a second patient who exists entirely inside the billing department.

And that patient needs care too.


HERE'S MY CONTRARIAN TAKE

We don't have a physician productivity problem.

We have a system design problem disguised as a productivity problem.

That distinction matters.

For years, healthcare has responded to administrative overload by telling clinicians to:

Work faster.

Document better.

Learn the new rule.

Use the new portal.

Check another box.

Hire another staff member.

Try another vendor.

Download another app.

Attend another training.

And, naturally, take care of yourself.

Because nothing says “wellness” quite like another mandatory 45-minute webinar.

We keep asking:

How can physicians become more efficient?

I think the better question is:

Why are physicians being asked to perform so much work that should have been prevented upstream?

That is a different question.

And it leads to a different kind of healthcare technology.


THE OTHER 166 HOURS EXISTS INSIDE YOUR PRACTICE

The caregiver story is powerful because the wife became the invisible infrastructure.

The healthcare system provided professional services.

She provided continuity.

She provided context.

She noticed changes.

She managed the ordinary moments.

She was there when nobody else was.

The same phenomenon happens in physician practices.

Your staff becomes the invisible infrastructure.

They remember payer quirks.

They know which claims are always problematic.

They know which physicians document differently.

They know which payer portal is broken.

They know which authorization department never answers the phone.

They know which denial code means:

“Good luck.”

They compensate.

They improvise.

They create workarounds.

They keep the practice moving.

And because they are good at their jobs, leadership sometimes assumes everything is fine.

That is one of the most dangerous illusions in healthcare.

A system can look functional because excellent people are constantly repairing it.


THE HUMAN COST OF “MAKING IT WORK”

Think about that phrase:

“We make it work.”

It sounds positive.

In medicine, it can be a warning sign.

“We make the schedule work.”

“We make the staffing work.”

“We make the billing work.”

“We make the payer work.”

“We make the old software work.”

“We make the new regulation work.”

“We make the denial process work.”

Translation:

Humans are absorbing the defects of the system.

And humans have limits.

That is where burnout enters the conversation.

The AMA's latest data show that 41.9% of physicians reported at least one symptom of burnout in 2025. That is an improvement from 43.2% in 2024 and 48.2% in 2023.

Improvement is good.

But 41.9% is still roughly four out of ten physicians.

That is not a rounding error.

And here's the part I find interesting:

We often talk about burnout as if it were an emotional problem.

Sometimes it is.

But much of the time, burnout is also an operations problem.

If the system generates unnecessary work every day, eventually somebody pays for it.

Usually with time.

Sometimes with money.

Often with both.


THE RCM MACHINE HAS A STRANGE BUSINESS MODEL

Let's imagine another industry.

A customer buys something.

The company delivers it.

Then the company intentionally creates paperwork that prevents itself from getting paid.

The customer says:

“Please prove you delivered it.”

The company provides proof.

The customer says:

“Please provide it in another format.”

The company does that.

Then the customer says:

“We still can't process it.”

The company hires 14 people to investigate.

Eventually everyone celebrates because the company successfully received payment for the thing it already delivered.

We would call that business model insane.

In healthcare, we call it:

Revenue Cycle Management.

I'm not saying billing is inherently broken.

I'm saying we've normalized an astonishing amount of post-service administrative friction.

And then we built an entire industry around cleaning it up.

That should make us uncomfortable.


THE DENIAL IS NOT THE PROBLEM

Here's another contrarian idea:

A denial is often not the problem.

It is the symptom.

The real problem happened earlier.

Maybe eligibility wasn't verified.

Maybe an authorization requirement wasn't identified.

Maybe documentation wasn't structured properly.

Maybe coding didn't reflect the clinical work.

Maybe the claim failed a payer-specific rule.

Maybe information was lost between systems.

Maybe nobody knew the rule had changed.

By the time the denial arrives, the system is essentially saying:

“Congratulations. We found your problem.”

Thank you.

Could we have known this yesterday?

That is the question.


DOWNSTREAM HEALTHCARE IS EXPENSIVE

The traditional revenue-cycle model is largely reactive.

Something happens.

Then somebody fixes it.

Claim denied.

Work denial.

Missing documentation.

Chase physician.

Wrong code.

Correct code.

Payer requests information.

Find information.

Authorization missing.

Start calling.

This is the healthcare equivalent of waiting for the smoke alarm before installing a fire extinguisher.

We need to move upstream.

Instead of:

Denial → correction

we should aim for:

Clinical encounter → validation → clean claim

Instead of:

Missing information → physician interruption

we should aim for:

Missing information → early identification

Instead of:

Payer rejection → investigation

we should aim for:

Payer requirements → pre-submission intelligence

That is the difference between reactive RCM and preventive RCM.


AND THE DATA ARE GETTING HARDER TO IGNORE

MGMA's 2026 Regulatory Burden Report found that approximately 95% of medical groups reported increased regulatory burden over the previous three years.

The report identified audits and appeals as the leading burden, while Medicare Advantage prior authorization, denials and automatic downcoding were also among the top issues.

That isn't a technology problem alone.

It is a workflow problem.

A staffing problem.

A financial problem.

And eventually, a patient-access problem.

MGMA explicitly connects rising administrative burden and declining reimbursement with physician burnout, consolidation and difficulty maintaining patient access.

So when we talk about medical billing, we need to stop treating it as the boring corner of healthcare.

It isn't boring.

It is infrastructure.


THE BILLING DEPARTMENT IS PART OF CLINICAL CAPACITY

This may sound strange.

But hear me out.

Suppose your billing team spends hundreds of hours every month correcting avoidable claims.

That is labor.

If your physicians spend evenings answering documentation queries, that is labor.

If your practice manager spends Friday afternoon fighting payer portals, that is labor.

If your medical assistant spends 30 minutes tracking an authorization, that is labor.

Every administrative task consumes capacity.

And capacity is finite.

Which means:

Administrative friction is a clinical resource problem.

Every hour spent fighting a preventable denial is an hour that cannot be spent improving the practice somewhere else.

Maybe with patients.

Maybe with staff.

Maybe with growth.

Maybe with quality.

Maybe with sleep.

Yes.

Sleep.

We don't put that on the balance sheet.

Perhaps we should.


WHAT I BELIEVE ABOUT AI

I am a physician.

I am also building a healthcare technology company.

So naturally I have an opinion about AI.

Here it is:

AI is not magic.

Sorry.

There goes the keynote.

AI will not eliminate payer policies.

It will not make every claim payable.

It will not replace clinical judgment.

It will not automatically make a poorly designed workflow intelligent.

And it certainly should not be used as an excuse to put more work onto physicians.

The real opportunity is much less glamorous.

And much more valuable.

Use AI to prevent humans from having to do repetitive work in the first place.

That's it.

Not sexy.

Very useful.


THE BEST AI MAY BE THE AI YOU NEVER NOTICE

Imagine an AI system that quietly notices:

“This documentation may not support the selected code.”

“Eligibility changed.”

“This payer requires additional information.”

“This claim has a pattern associated with previous denials.”

“This modifier combination deserves review.”

“This physician consistently encounters the same denial.”

That is not science fiction.

It is workflow intelligence.

And the best version of it does not shout:

LOOK WHAT AI CAN DO!

It quietly prevents the problem.

That is the kind of AI healthcare needs.

Less theater.

More infrastructure.


THIS IS WHY I BUILT ONNX

The thesis behind OnnX is simple.

The healthcare industry has spent enormous energy optimizing what happens after the claim fails.

I believe we should spend more energy asking:

Why did the claim become vulnerable in the first place?

That moves the conversation upstream.

From billing to clinical-to-claims intelligence.

From correction to prevention.

From manual work to intelligent workflow.

From:

“Who can fix this?”

to:

“Why did we create this problem?”

That is a much more interesting question.

And frankly, it is the question I think healthcare technology has avoided for too long.


THE THREE QUESTIONS EVERY PRACTICE OWNER SHOULD ASK

Forget the vendor demo for a minute.

Ask these first.

QUESTION ONE:

Where are we losing money?

Not theoretically.

Show me the last 90 days.

 

QUESTION TWO:

Why are we losing it?

Group the denials.

Look for patterns.

Do not accept:

“Insurance denied it.”

That's not a root cause.

That's a sentence.

 

QUESTION THREE:

Where was the problem first created?

This is the big one.

Because the place where you discover a problem is often not the place where you created it.


A DENIAL DASHBOARD IS NOT ENOUGH

This is another industry habit I would challenge.

A practice installs a dashboard.

Beautiful charts.

Green arrows.

Red arrows.

Trend lines.

Someone presents it at the monthly meeting.

Everyone nods.

Then the same denial happens next month.

And the month after.

Congratulations.

You have successfully visualized the problem.

You have not solved it.

Analytics without intervention is expensive wallpaper.

The dashboard needs to lead somewhere.

A root cause.

An owner.

An intervention.

A measurable change.


FIVE METRICS I WOULD WATCH

1. CLEAN CLAIM RATE

How often does the claim get through the first time?

Simple.

Important.

 

2. DENIAL RATE

But don't stop there.

Break it down by:

payer, provider, procedure, diagnosis, modifier and denial reason.

Patterns matter.

 

3. DENIAL TOUCHES

How many people touch the claim before it is resolved?

One?

Three?

Six?

If a $100 claim requires $200 worth of human labor to recover, you have discovered something important.

 

4. PHYSICIAN ADMINISTRATIVE TIME

How many minutes per week do physicians spend dealing with billing-related questions?

Track it.

You may not like the answer.

That's okay.

Bad information is still better than comfortable assumptions.

 

5. DAYS IN A/R

Watch the trend.

Not just the number.

A rising A/R curve can be the smoke before the fire.


THE 30-DAY PRACTICE EXPERIMENT

Don't overhaul everything.

Pick one problem.

Just one.

DAYS 1–5

Pull 90 days of claims.

Find your top three denial categories.

DAYS 6–10

Choose the largest category.

Trace it backward.

Where did it begin?

DAYS 11–15

Interview the people who actually touch the workflow.

Not just executives.

Ask the person who fixes the problem every day.

They usually know more than the dashboard.

DAYS 16–20

Change one upstream step.

DAYS 21–30

Measure the result.

Did the denial rate fall?

Did staff touches fall?

Did physician interruptions fall?

Did A/R improve?

If yes, keep going.

If no, congratulations again.

You learned something.

That is better than pretending the first solution worked.


WHAT NOT TO AUTOMATE

This is important.

Do not automate everything simply because you can.

Clinical judgment should remain with clinicians.

Compliance decisions need appropriate oversight.

Exceptions need human review.

High-risk decisions need escalation.

And automated coding should never become a license to inflate reimbursement.

The ethical goal is:

accurate representation of care.

Not:

maximum possible reimbursement.

Those are not synonyms.


THE LEGAL AND ETHICAL LINE

Healthcare technology lives in a world of privacy, compliance and accountability.

If your system handles protected health information, appropriate safeguards matter.

If AI influences coding or billing, auditability matters.

If a vendor touches sensitive data, contracts and responsibilities matter.

If automation produces recommendations, someone must be accountable for reviewing them when appropriate.

And if a system encourages unsupported documentation or coding, that's not innovation.

That's a problem.

Technology should help practices become more accurate, not merely more aggressive.

The best revenue-cycle system is not the one that finds the most money.

It is the one that helps the practice accurately capture the value of legitimate care it already provided.


HERE'S ANOTHER UNCOMFORTABLE TRUTH

Small practices are often told they need to behave like large health systems.

More software.

More processes.

More dashboards.

More departments.

More infrastructure.

I'm not convinced.

Small practices have an advantage large organizations often envy:

They can move quickly.

The problem is that they have less room for waste.

A large system can hide inefficiency inside a giant organization.

A five-physician practice cannot.

If one employee spends half a day every week fixing the same problem, you feel it.

If the physician spends two hours every Friday dealing with claims, you feel it.

If $100,000 sits in avoidable A/R, you feel it.

The smaller the practice, the more valuable operational clarity becomes.


THE REAL COMPETITIVE ADVANTAGE

I don't think the future belongs to the practice with the most technology.

I think it belongs to the practice with the least unnecessary work.

Think about that.

Not:

Who has the most AI?

Who has the newest EHR?

Who has the biggest billing department?

Who has the fanciest dashboard?

Instead:

Who can deliver excellent care with the least administrative friction?

That's a better competitive question.


THE CAREGIVER WASN'T THE BILLING DEPARTMENT

Let's be clear.

The wife in the original story was not dealing with claims.

She was caring for her husband.

Her story is not proof that RCM causes caregiver burden.

That would be a ridiculous leap.

But her story illustrates something important:

Healthcare systems often count formal services while families experience the total workload.

That distinction matters.

A nurse's visit is counted.

The spouse's midnight work often isn't.

A physical therapy session is documented.

The hours of supervision between visits aren't.

Healthcare measures encounters extremely well.

It is often much worse at measuring everything that happens between encounters.

And that is exactly where a huge amount of healthcare work lives.


BETWEEN THE VISITS

Healthcare happens between visits.

Between appointments.

Between claims.

Between payer decisions.

Between authorization requests.

Between phone calls.

Between portal messages.

Between discharge and follow-up.

Between documentation and reimbursement.

Those gaps are where friction hides.

And wherever friction hides, opportunity usually follows.

That's where healthcare founders should look.

Not necessarily at another flashy front-end app.

Look at the spaces between systems.

Look at the handoffs.

Look at the moments where information gets lost.

Look at the places where humans repeatedly compensate.

That's where the real infrastructure opportunity may be.


THE NEXT GENERATION OF HEALTHCARE TECHNOLOGY

I think we are moving toward a different model.

The first generation of healthcare software digitized paperwork.

The second generation automated workflows.

The next generation should understand context.

It should know:

What happened clinically.

What needs to happen operationally.

What the payer expects.

What historically goes wrong.

What requires human judgment.

And what can safely happen automatically.

That's more than automation.

That's workflow intelligence.


THE FUTURE IS NOT “NO HUMANS”

That's the wrong goal.

Healthcare is human.

Always will be.

The goal should be:

fewer humans doing unnecessary work.

More humans doing work that requires judgment.

More physician attention where it matters.

More staff attention where it matters.

Less clicking.

Less chasing.

Less duplicate entry.

Less “Can you resend that?”

Less “The payer says they never received it.”

Less Friday-afternoon claims archaeology.

And, ideally:

fewer reasons for a physician to stare at a billing portal after seeing patients all day.


THE QUESTION I WOULD ASK EVERY PHYSICIAN-OWNER

If you could eliminate one administrative task from your practice tomorrow, what would it be?

Prior authorization?

Denials?

Eligibility?

Documentation queries?

Claim status?

Coding?

Payer portals?

Something else?

And here's the more important question:

Why does that task exist in the first place?

That second question is where innovation begins.


THREE THINGS I WOULD DO THIS MONTH

ONE: Find your most expensive recurring denial.

Not your most annoying one.

Your most expensive one.

TWO: Calculate the human labor required to fix it.

Staff time.

Physician time.

Manager time.

THREE: Move the intervention upstream.

Don't simply hire someone to work the denial faster.

Ask whether the next denial can be prevented.

That is the difference between scaling labor and scaling intelligence.


THE BIGGEST MYTH IN MEDICAL BILLING

The myth is that the solution to administrative burden is more administrative capacity.

Sometimes it is.

But not always.

If the system creates 1,000 unnecessary tasks and you hire people to complete those 1,000 tasks, you have not solved the problem.

You've just become better at tolerating it.

Efficiency is not doing more work faster.

Sometimes efficiency means making the work disappear.


FINAL THOUGHTS

The husband in this story went home.

His wife stayed on call.

The healthcare system provided professional services.

She provided the rest.

There is something uncomfortable about that.

Not because the system necessarily failed.

But because the system's definition of “care” was smaller than the family's reality.

Physician practices face a similar challenge.

The patient encounter may be 20 minutes.

But the administrative life of that encounter can stretch for days.

The work doesn't disappear because the patient walked out the door.

Someone carries it.

A biller.

A medical assistant.

A practice manager.

A physician.

Someone.

So perhaps the question isn't:

“How do we get our staff to work harder?”

Perhaps it is:

“How much of this work should exist at all?”

That is the question I want healthcare leaders to ask.

Because the future of healthcare won't be built simply by adding more people to broken workflows.

It will be built by designing workflows that need fewer unnecessary interventions in the first place.


THREE SENTENCES TO REMEMBER

Stop measuring how much unnecessary work your people can tolerate.

Start measuring how much unnecessary work your system can eliminate.

Give healthcare professionals their most valuable resource back: attention.


GET INVOLVED

Now I want to hear from physicians and clinic owners.

What is the one administrative task in your practice that makes absolutely no sense anymore—but everyone has simply learned to live with it?

Tell me in the comments.

Don't give me the polished executive answer.

Give me the real one.

The annoying one.

The absurd one.

The task your staff complains about every Friday.

Share this article with another physician or practice owner who has ever wondered why healthcare requires so much work to get paid for work already completed.

And if you're building something better in healthcare, join the conversation.

Question the workflow.

Challenge the “best practice.”

Measure the friction.

Fix the source.


FREQUENTLY ASKED QUESTIONS

Is the “Other 166 Hours” story about a real patient?

Yes. The August 16, 2026 24/7 Wall St. story describes an unnamed husband discharged home with intermittent home-health services and his wife providing the majority of his ongoing care. The publication does not identify the couple by name.

Why use this story in an article about medical billing?

Because it illustrates the broader concept of hidden healthcare labor. The caregiver experiences the full workload of care even when the formal healthcare system measures only specific professional services.

The RCM connection is an analogy, not a claim that the two situations are identical.

Is physician burnout improving?

Yes, according to the AMA's latest data. But 41.9% of physicians reported at least one symptom of burnout in 2025, so the problem remains substantial.

What is currently one of the biggest administrative burdens for medical groups?

MGMA's 2026 Regulatory Burden Report identifies audits and appeals as the leading burden and lists Medicare Advantage prior authorization, denials and automatic downcoding among the major burdens.

Does AI eliminate denials?

No.

AI can help identify patterns, flag potential problems and automate repetitive workflows.

But payer policies, clinical judgment, documentation and human oversight remain essential.

Should physicians be responsible for billing?

Physicians should understand the connection between clinical documentation, coding and reimbursement.

They should not have to become billing specialists.

The objective should be to make the system work better around clinical care.

What should a practice measure first?

Start with:

clean claim rate, denial rate by root cause, denial touches, days in A/R and physician administrative time.

Is outsourcing medical billing a bad idea?

Not necessarily.

The problem is outsourcing without visibility.

A practice should still understand its denial patterns, collections, A/R, vendor performance, contracts and escalation processes.

What is upstream RCM?

Upstream RCM means identifying and preventing revenue-cycle problems before they become denials, rework or delayed payment.


EXPERT PERSPECTIVES

CHRISTINE SINSKY, MD

Dr. Sinsky's work on physician well-being has emphasized the relationship between clinician burnout and the systems in which physicians practice.

The lesson for practice owners is straightforward:

Don't treat a system problem as a resilience problem.

If the workflow generates unnecessary administrative work, redesign the workflow.


ANDERS GILBERG, MGMA

MGMA's senior vice president of government affairs has highlighted the growing burden that regulatory requirements, Medicare Advantage processes, denials and other administrative demands place on medical practices.

The broader lesson:

Administrative burden is no longer a side issue. It is a practice sustainability issue.


THE AMA'S PHYSICIAN WELL-BEING RESEARCH

The AMA's current data show that physician burnout is moving in the right direction, but remains widespread.

The lesson is not that healthcare can declare victory.

It is that system-level improvements can matter—and that continued work is necessary.


THREE REFERENCES

MGMA — 2026 Regulatory Burden Report

MGMA's report documents the growing administrative burden experienced by medical groups, including audits, appeals and Medicare Advantage-related processes.

Read the MGMA 2026 Regulatory Burden Report

American Medical Association — Physician Burnout

The AMA's latest data show 41.9% of physicians reported at least one burnout symptom in 2025.

Read the AMA physician burnout report

24/7 Wall St. — The Other 166 Hours

The original human-interest story that inspired this article describes the gap between intermittent professional home-health visits and the family's ongoing caregiving responsibilities.

Read the original caregiver story


ABOUT THE AUTHOR

Dr. Daniel Cham is a physician, medical consultant and healthcare entrepreneur focused on the intersection of medical technology, healthcare operations, medical billing and practice sustainability.

He is the founder of OnnX, an AI-powered medical billing platform focused on helping small and medium-sized medical practices reduce administrative friction and improve the connection between clinical documentation, coding, claims and reimbursement.

His work centers on a simple question:

What if healthcare technology stopped asking physicians to work around broken systems—and started making those systems work around physicians?

Connect with Dr. Daniel Cham on LinkedIn


DISCLAIMER

This article is intended for general educational and informational purposes and should not be interpreted as medical, legal, compliance, coding or reimbursement advice.

Healthcare requirements, payer policies, contracts and regulations vary.

Physicians, practice owners and healthcare organizations should obtain advice from appropriately qualified professionals regarding their individual circumstances.


CONTINUE THE CONVERSATION

The healthcare conversation should not end with the article.

Explore more perspectives on healthcare operations, physician entrepreneurship, medical technology, revenue-cycle management and healthcare innovation:

Visit Dr. Cham's website

Listen to the podcast on Spotify

Watch on YouTube

Follow Dr. Cham on X

Follow Dr. Cham on Facebook

Knowledge creates leverage.

Better questions create better systems.

Better systems give healthcare professionals more time to do the work only they can do.

Start there.


FREE RESOURCE

PS: A free resource is available in the Featured section of my LinkedIn profile. No additional signup is required. If you are working to improve your practice operations, take a look.

If this article made you think differently about administrative work, repost it.

Another physician may need to see it.

Another practice owner may recognize their own Friday-afternoon billing nightmare in it.

And maybe the next healthcare innovation won't be another tool that adds work.

Maybe it will be the tool that finally removes some.

#Healthcare #Physicians #MedicalBilling #RevenueCycleManagement #HealthcareInnovation #PhysicianBurnout #MedicalPractice #PracticeManagement #HealthTech #HealthcareTechnology #MedicalCoding #ClaimsManagement #DenialManagement #HealthcareLeadership #PhysicianEntrepreneur #IndependentPractice #ClinicalOperations #AIinHealthcare #OnnX

 

Mark and Madi Turley: Two Preemies, 30 Years Apart—and What Their Story Reveals About the Broken Translation Between Medicine and Money

The patient’s story begins in the exam room. Somewhere between clinical care and the claim, we keep losing it. “The white coat symbolizes ...