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?
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.
