When healthcare connections fail, the burden does not disappear. It moves to the patient, physician, staff—or eventually, the billing department.
“Redesigning workflows attacks the source of distress
instead of giving people skills to cope with it.” — Dr.
Liz Harry, Chief Well-Being Officer, Michigan Medicine
Source: American Medical Association, AMA STEPS Forward,
September 16, 2026.
Fatouma kept going
Fatouma Mahdi Ahmed Saeed had cervical cancer.
To receive treatment, she traveled hundreds of miles through
war-torn Sudan.
She had been diagnosed in Nyala, South Darfur.
Then the healthcare system around her began collapsing.
Hospitals were attacked.
Healthcare infrastructure was disrupted.
Cancer treatment became increasingly difficult to access.
So Fatouma left.
She traveled with her sister and her son.
She faced checkpoints.
She avoided drone strikes.
She traveled through dangerous territory.
When she became exhausted, she rested on dirt.
Eventually, she reached Mother of Mercy Hospital in
the Nuba Mountains.
There, Dr. Tom Catena, an American physician and
medical missionary, was trying to provide cancer care under extraordinary
conditions.
There was no oncologist.
Some diagnostic equipment was unavailable.
Tissue samples sometimes had to be sent to the United States
for analysis.
The process could take months.
And yet Fatouma received treatment.
Then she went home.
Then she came back.
Then she returned again.
She kept going.
STAT reported that Fatouma described herself as being in
significant pain and desperate for treatment. Her journey was difficult, but
she continued.
Her story is extraordinary.
But it is not the only story.
Ifrah Ahmed, only 10 years old, traveled with her
grandmother from Babanusa after developing osteosarcoma.
By the time she reached Mother of Mercy Hospital, doctors
had to amputate her leg at the hip.
She received chemotherapy.
Her wish was simple:
To be healthy.
And to be with her mother in a safe place.
Then there was Abasst Abonja, 76, who traveled from
South Sudan with colon cancer.
He was extremely weak.
He had not eaten for four days.
He died shortly after STAT visited the hospital.
His wife was beside him.
And then there was Dr. Tom Catena, working inside a
healthcare system devastated by war, trying to provide care without many of the
specialists, diagnostic resources and infrastructure that modern cancer
treatment normally requires.
Four names.
Four human beings.
Four very different journeys.
Fatouma Mahdi Ahmed Saeed.
Ifrah Ahmed.
Abasst Abonja.
Tom Catena.
Their circumstances are profoundly different from those of
patients walking into an American physician practice.
A U.S. insurance denial is not a war zone.
A payer portal is not a battlefield.
A missing authorization is not comparable to a destroyed
hospital.
We should not pretend otherwise.
But there is a systems lesson here that every physician and
clinic owner should examine.
Healthcare is a journey made of connections.
Diagnosis has to connect to treatment.
Treatment has to connect to follow-up.
A referral has to connect to a specialist.
A test has to connect to a result.
A physician's decision has to connect to an authorization.
A clinical note has to connect to the right billing
information.
And the claim eventually has to connect to payment.
When those connections work, nobody notices.
When they fail, somebody carries the burden.
Sometimes the patient carries it.
Sometimes the physician.
Sometimes the medical assistant.
Sometimes the medical biller.
Sometimes the practice owner.
And sometimes everybody does.
That is where Fatouma's story becomes unexpectedly relevant
to American healthcare.
Because we have become very good at treating the place where
the problem becomes visible.
We are not always as good at finding where the problem
began.
And that brings us to a provocative question:
What if the denial isn't the problem?
What if the denial is simply the first place you can see the
problem?
That sounds like semantics.
It isn't.
Imagine this:
A patient arrives.
Insurance is entered.
The patient is verified.
The physician sees the patient.
The physician documents the encounter.
A claim is created.
The claim is submitted.
The payer rejects it.
Everyone looks at the claim.
Naturally.
That's where the money stopped moving.
So the billing team investigates.
Maybe the diagnosis is wrong.
Maybe the modifier is missing.
Maybe authorization was required.
Maybe documentation does not support the service.
Maybe the insurance information was incorrect.
Maybe a payer rule changed.
Maybe information existed somewhere in the practice but
never made it to billing.
The denial is real.
But the denial may have started long before the claim was
created.
The claim may simply be the messenger.
And healthcare has a long history of shooting the messenger.
Medical billing has a plumbing problem
MGMA used a useful metaphor earlier this year:
Revenue-cycle management has leaks.
Not necessarily one giant leak.
Small leaks.
A wrong insurance digit.
A missing modifier.
A denial that nobody categorizes correctly.
A documentation gap.
A missed authorization.
An eligibility problem.
A delayed charge.
A payer-specific requirement nobody noticed.
MGMA's January 2026 poll found that medical-group leaders
identified denials and appeals as the largest source of revenue-cycle
leakage at 48%, followed by front-end issues at 23%, billing and
collections at 14%, coding at 13%, and charge posting at 2%.
The obvious reaction is:
“We need to work the denials harder.”
Maybe.
But that is the equivalent of mopping the floor while the
pipe is still leaking.
The more interesting question is:
Why are these denials happening repeatedly?
And then:
Where did the information failure begin?
That second question is where things get uncomfortable.
Because it can lead directly into scheduling.
Registration.
Eligibility.
Authorization.
Documentation.
Coding.
Clinical workflow.
Physician behavior.
Staff workflow.
EHR design.
Payer requirements.
In other words:
The denial department may not own the problem.
It may merely inherit it.
Your best biller may be hiding your worst workflow
Every medical practice has one.
The person who knows everything.
She knows which payer is impossible.
She knows which portal hides the authorization status behind
three clicks and a password reset.
She knows which payer wants the clinical note attached.
She knows which diagnosis tends to trigger a denial.
She knows which physician forgets which piece of
documentation.
She knows which claims are worth appealing.
She knows who to call.
She knows when to call.
She knows what to say.
And she remembers all of it.
That sounds like an incredible employee.
It is.
It is also a warning.
Because if your revenue cycle depends on one employee's
memory, you may not have a sophisticated revenue-cycle system.
You may have institutional knowledge wearing a name
badge.
And institutional knowledge has a nasty habit of taking
vacations.
Sometimes it retires.
Sometimes it changes jobs.
Sometimes it gets recruited by the practice down the street.
Then everyone discovers that the “system” was actually
Susan.
Or Maria.
Or James.
Or whoever your best biller happens to be.
That is not a people problem.
It is a system-design problem.
Your best employee should be making the system better.
She should not have to be the system.
The contrarian truth about denials
Here is the idea I want physicians and clinic owners to
challenge:
A high denial rate may tell you less about your billing
team than you think.
It may be telling you something about the entire practice.
The denial is downstream.
The causes may be upstream.
Think about a patient encounter as a relay race.
Scheduling starts with the baton.
Registration receives it.
Eligibility handles it.
Authorization may receive it.
The clinical team takes it.
Documentation carries it.
Coding receives it.
Billing takes it across the finish line.
The payer is waiting at the end.
Now imagine the baton is missing pieces every time it
changes hands.
One person knows the insurance.
Another knows the authorization.
Another knows what the physician documented.
Another knows what the payer requires.
Nobody sees the whole picture.
Then the baton reaches billing.
And the biller gets blamed because the baton fell.
That is a terrible relay strategy.
It is also remarkably common.
The revenue cycle starts before billing
This should be obvious.
Yet much of the healthcare industry behaves as though
revenue cycle begins when the claim is created.
It doesn't.
The revenue cycle begins earlier.
It begins with the information that eventually becomes the
claim.
That means:
Scheduling is revenue cycle.
Eligibility is revenue cycle.
Authorization is revenue cycle.
Documentation is revenue cycle.
Coding is revenue cycle.
Charge capture is revenue cycle.
Claim submission is revenue cycle.
Payment posting is revenue cycle.
Denial management is revenue cycle.
The departments are separate.
The patient's experience is not.
That distinction is critical.
The patient sees one healthcare system
Your organizational chart may have seven departments.
The patient does not care.
The patient sees:
the practice.
They don't know that the front desk belongs to one workflow,
authorization to another, billing to another, and payer relations to someone
else.
They know they gave the practice their insurance card.
They know the physician ordered something.
They know they were told it was covered.
They know someone called them.
They know the appointment happened.
Then they get a letter saying:
Denied.
That is the patient experience.
And suddenly a complex internal process becomes one very
simple question:
“Why?”
The practice may have 14 answers.
The patient wants one.
Prior authorization is the perfect example
Prior authorization is one of healthcare's most obvious
demonstrations of what happens when information fails to move cleanly.
The AMA's latest physician survey found that physicians
complete an average of 40 prior authorizations per week, consuming about
13 hours of physician and staff time. The survey also found that 94% of
physicians said prior authorization contributes to burnout.
The AMA separately reported that 95% of physicians
surveyed said prior authorization delays necessary care, while 79% said
patients sometimes abandon treatment because of authorization challenges.
Now consider the absurdity.
The physician knows what the patient needs.
The patient knows what the physician recommended.
The practice has the clinical information.
The payer has requirements.
And everyone spends time moving information around trying to
make those facts agree.
The information already exists.
The problem is getting it into the right place, in the right
form, at the right time.
That is not primarily an intelligence problem.
It is a workflow problem.
And the workflow is still not moving fast enough
MGMA reported in September 2026 that 44% of medical-group
leaders said payer prior-authorization turnaround became slower in 2026
compared with 2025, while fewer than one in ten reported faster turnaround.
Pause there.
We have more portals.
More electronic systems.
More APIs.
More automation.
More dashboards.
More AI.
And many practices are still saying:
“It's taking longer.”
This should force us to ask a harder question.
Maybe the problem isn't that healthcare lacks technology.
Maybe healthcare has accumulated technology without
sufficiently redesigning the underlying workflow.
We digitized the fax.
Then we called it innovation.
The fax became a portal.
The portal became an inbox.
The inbox became a dashboard.
The dashboard created another task.
And now we're considering adding AI to the dashboard.
At some point we have to ask:
Are we removing work—or merely changing its font?
Dr. Liz Harry's point matters beyond burnout
The current-week AMA STEPS Forward discussion featuring Dr.
Liz Harry, chief well-being officer at Michigan Medicine, makes a broader
point about healthcare workflow.
The problem is not always that clinicians need better coping
skills.
Sometimes the workflow itself is creating the distress.
As Harry put it:
“Redesigning workflows attacks the source of distress
instead of giving people skills to cope with it.”
The AMA's September 16, 2026 episode argues that reducing
administrative burden and unnecessary cognitive load can return time and mental
bandwidth to clinicians and care teams.
That principle applies beautifully to revenue cycle.
If your staff repeatedly fixes the same mistake, you can:
Option A: Tell them to work faster.
Option B: Hire another person.
Option C: Buy another dashboard.
Option D: Fix the workflow that keeps generating the
mistake.
Healthcare often chooses A, B or C.
The interesting opportunity is D.
More automation can create less automation
This sounds contradictory.
But consider the math.
Suppose an automated system generates 1,000 claims.
Great.
Now suppose 100 require manual intervention.
You have not eliminated the work.
You have moved it.
Now imagine the automation generates alerts.
The biller must review the alerts.
Then document the action.
Then enter the correction.
Then resubmit.
Then monitor the outcome.
The system is technically automated.
The workflow is not.
This is why the right metric is not:
“How much did we automate?”
The better metric is:
“How much unnecessary human work disappeared?”
That is a much harder question.
It is also a much more useful one.
The “1.2 FTE” nobody budgets for
Independent practices often have a hidden employee.
You just don't put them on payroll.
They are the combined hours of everyone performing
administrative rework.
The physician spends 15 minutes correcting a note.
The medical assistant spends 20 minutes finding information.
The front desk spends 10 minutes fixing insurance data.
The biller spends 30 minutes figuring out why the claim
failed.
The office manager spends 25 minutes calling the payer.
Nobody owns the total.
But the practice pays for all of it.
Call it the 1.2 FTE problem.
You may think you have five people doing the work.
But your broken workflows are quietly consuming the
equivalent of another employee.
The invisible employee has no badge.
No salary.
No vacation.
No performance review.
But it works overtime.
Every day.
The real cost of rework
Let's use deliberately simple math.
Suppose a preventable problem requires 15 minutes of staff
time.
It happens 20 times a week.
That's five hours.
Over 50 weeks, that's:
250 hours.
More than six full-time workweeks.
And that is one problem.
Add:
- authorization
rework
- eligibility
corrections
- documentation
requests
- coding
changes
- denial
appeals
- payer
follow-up
- underpayment
review
- patient-balance
corrections
Suddenly the practice isn't just managing a revenue cycle.
It is operating a revenue-cycle repair shop.
The industry rarely measures that repair shop.
It should.
The biller isn't the firewall
Medical billers are often treated as the last line of
defense.
That is useful.
But it can also become an excuse.
If every problem is expected to be caught by billing, the
organization has created a human firewall.
And firewalls eventually get overloaded.
The biller should catch exceptions.
The biller should not have to reconstruct the entire patient
journey after the fact.
That is the difference between:
exception management
and
information archaeology.
If your biller spends the morning digging through old notes,
faxes, portals and spreadsheets to figure out what happened three weeks ago,
that's not billing.
That's archaeology.
And Indiana Jones had a whip.
Your biller has Outlook.
Myth #1: “My biller catches everything”
No.
Your biller catches what the workflow allows her to
discover.
There is a difference.
If information never reached her, she cannot correct what
she cannot see.
If the problem appears only after submission, the practice
has already missed the cheapest point of intervention.
The goal should be to move error detection closer to the
moment the information is created.
Not closer to the moment the payer rejects it.
Myth #2: “We need a better clearinghouse”
Maybe.
But the clearinghouse receives the output.
If the input is wrong, the clearinghouse is not a time
machine.
It cannot travel backward and ask the physician:
“Did you mean this?”
It cannot walk over to the front desk and say:
“Your insurance information was entered incorrectly.”
It cannot ask:
“Was authorization obtained before the appointment?”
It can only work with what reaches it.
That's why upstream structure matters.
Myth #3: “The payer is the entire problem”
Payers absolutely contribute to revenue-cycle complexity.
MGMA's recent revenue-cycle reporting identifies
payer-driven issues among major sources of leakage, including medical
necessity, utilization management, eligibility, timely filing and payer policy
changes.
But blaming the payer for every problem is operationally
lazy.
You cannot control every payer rule.
You can control whether your practice knows the rules it
encounters repeatedly.
You can control how information is captured.
You can control your internal handoffs.
You can control how recurring failures are analyzed.
You can control whether the organization keeps fixing the
same problem.
The payer may create the obstacle.
Your workflow determines how much of the obstacle becomes
your problem.
Myth #4: “AI will fix it”
This one is fashionable.
It is also incomplete.
AI can be extraordinarily useful.
It can extract information.
Summarize documentation.
Identify missing data.
Recognize patterns.
Prioritize work.
Surface inconsistencies.
But AI does not magically transform fragmented information
into a coherent workflow.
If the inputs are poor, AI may simply make the wrong process
faster.
Garbage in. Intelligence out.
Still garbage.
Just more confidently delivered.
What AI should actually do
A practical architecture for healthcare revenue cycle could
be:
AI extracts.
Rules validate.
The system explains.
Humans handle judgment.
That's different from:
AI decides everything.
Healthcare needs judgment.
Payers have rules.
Clinical documentation has context.
Coding has compliance implications.
Patients are not spreadsheets.
AI should reduce the cognitive burden around those decisions
without pretending every healthcare decision can be reduced to a prediction.
The future is not “AI billing”
That phrase is too broad.
The better question is:
Where can intelligence prevent rework?
Can the system identify missing information before the
claim?
Can it detect that authorization may be required?
Can it recognize inconsistent information across workflows?
Can it surface documentation gaps?
Can it identify recurring denial patterns?
Can it help the biller understand why a claim is at risk?
Can it learn from previous corrections?
Those are practical questions.
They lead to practical products.
And they move the industry from:
reactive recovery
toward:
proactive prevention.
The most valuable claim may be the one you never have to
fix
This sounds almost too obvious.
But it changes the economics.
A denial recovered is visible.
Everyone celebrates it.
A denial prevented is invisible.
Nobody sees it.
There is no appeal.
No phone call.
No follow-up.
No resubmission.
No angry patient.
No aging A/R.
Nothing happens.
That is the point.
Prevention is operationally boring.
And boring is underrated.
If your revenue cycle becomes boring because fewer things go
wrong, you may have built something excellent.
Stop celebrating heroic employees
Healthcare loves heroes.
The physician who stays late.
The nurse who works through lunch.
The biller who clears 300 denials.
The office manager who knows every payer.
We celebrate them.
Then we build systems that require more heroes.
That's backward.
A good system should reduce the need for heroics.
If the only way to make the system work is for exceptional
people to compensate for ordinary workflow, you don't have a high-performing
system.
You have a system being rescued.
What physicians should own
Physicians should not become billers.
Please don't.
Healthcare has enough problems.
But physicians do need to understand that clinical
documentation is part of the revenue infrastructure.
That does not mean documenting for money.
It means documenting clearly, accurately and sufficiently to
represent the care provided.
Physicians should ask:
- What
information repeatedly causes downstream questions?
- What
documentation gaps create rework?
- Which
parts of the workflow create unnecessary administrative burden?
- What
do staff repeatedly ask me to clarify?
- What
information do I enter once that someone else has to enter again?
Those questions are not about becoming a billing expert.
They are about understanding the system surrounding clinical
care.
What clinic owners should own
Clinic owners need a broader view.
Don't ask only:
“How much did we collect?”
Ask:
“What did it cost us to collect it?”
Then ask:
“How much of that cost came from preventable rework?”
Then:
“Where did that rework originate?”
Now you are managing a system.
Five metrics that deserve more attention
1. Clean claim rate
How many claims leave the practice correctly the first time?
2. Recurring denial rate
Not merely total denials.
Repeated causes.
3. Rework hours
How many staff hours are spent correcting preventable
issues?
4. Authorization failure rate
How often does the practice discover an authorization
problem too late?
5. Prevented leakage
How much revenue risk was identified and resolved before
becoming a denial?
That last metric may eventually become one of the most
important measures in modern revenue-cycle management.
Because:
recovery tells you what went wrong.
prevention tells you what you learned.
Run a 30-day revenue-cycle autopsy
Don't buy anything yet.
For the next 30 days, record every preventable issue.
Create seven buckets:
Eligibility
Authorization
Documentation
Coding
Charge capture
Claim submission
Payer processing
Then record:
What happened?
Where did it begin?
How much staff time did it consume?
How much money was at risk?
Did the same thing happen before?
At the end of 30 days, you may discover something powerful.
You don't have 100 problems.
You have five problems happening 20 times.
That is a much more solvable problem.
Use the five-whys test
Suppose a claim was denied.
Don't stop at:
Why was the claim denied?
Ask:
Why?
Missing authorization.
Why?
Authorization was not obtained.
Why?
The service was not flagged during scheduling.
Why?
The workflow did not identify the payer requirement.
Why?
The relevant information was not connected to scheduling.
Now you have found something interesting.
The denial did not begin in billing.
It began in workflow design.
That is exactly the kind of problem that technology should
help solve.
The information relay
Think of your practice as an information relay.
At every handoff, ask:
What does the next person need to know?
Then:
Does the next person actually have it?
Then:
Do they have it in a usable form?
Then:
Are they forced to enter it again?
Then:
Does anyone verify it?
This exercise alone can uncover enormous amounts of hidden
friction.
The hidden tax of re-entering information
Healthcare is full of duplicate entry.
The same information may appear in:
- scheduling
- registration
- EHR
- authorization
forms
- payer
portals
- billing
systems
- spreadsheets
- fax
cover sheets
- patient
communications
Every duplicate entry creates another chance for
inconsistency.
The irony is that we call these systems “integrated.”
Sometimes they are integrated in the same way that several
people standing in the same parking lot are a transportation system.
Technically, everyone is connected.
Nobody is going anywhere.
The practice should have one version of the truth
This does not mean one giant database solves everything.
It means the organization should know:
Which information matters?
Where is the authoritative source?
Who owns it?
When does it change?
Who needs it next?
That is information governance at the practical level.
Not a committee.
Not a 90-page policy.
Just clarity.
The patient's journey and the claim's journey are
connected
This is where Fatouma's story returns.
Fatouma's physical journey was extraordinarily difficult
because the healthcare infrastructure around her had broken down.
The distance between diagnosis and treatment became
enormous.
American patients may not face that kind of physical
distance.
But they can experience another form of distance.
Administrative distance.
The doctor knows.
The staff doesn't.
The payer needs something.
The biller doesn't have it.
The authorization exists.
The claim doesn't know about it.
The documentation exists.
The payer cannot find what it needs.
Everyone is technically connected.
But the information is not moving.
That is the hidden problem.
Access is more than having a doctor
We often define healthcare access geographically.
Do you have a physician nearby?
Can you get an appointment?
Can you reach a hospital?
Those questions matter.
But access also has an operational dimension.
Can the patient move through the system successfully?
Can the authorization happen?
Can the documentation support the care?
Can the claim move?
Can the payment process correctly?
Can follow-up happen?
A healthcare system can have excellent clinicians and still
create extraordinary friction.
The clinical capability can be there.
The infrastructure can be there.
The information flow can still fail.
The physician-owner advantage
Independent practices have one major advantage:
proximity.
The physician owner can see the entire chain.
Patient.
Front desk.
Clinical team.
Billing.
Cash flow.
Staff frustration.
Patient complaints.
That makes independent practices unusually capable of fixing
workflow problems.
You don't need a 20-person transformation office.
You need someone willing to ask:
“Where exactly does the information break?”
And then keep asking until the answer becomes uncomfortable.
The 20-minute revenue-cycle meeting
Try this once a week.
Twenty minutes.
No PowerPoint.
No corporate language.
Ask five questions:
1. What denied this week?
2. What was the root cause?
3. Has this happened before?
4. Where should the information have been captured?
5. What can we change before the next patient?
That's it.
The objective is not to discuss every claim.
It is to find patterns.
Because individual errors are expensive.
Recurring errors are strategic.
What your best biller knows that your software doesn't
This may be one of the most valuable discovery questions for
a practice owner.
Ask your biller:
“What do you know from experience that the system doesn't
tell you?”
Listen carefully.
That answer may reveal:
- undocumented
payer behavior
- recurring
authorization problems
- physician
workflow gaps
- common
documentation issues
- hidden
payer rules
- repetitive
claim defects
- information
that staff routinely reconstruct manually
That knowledge is valuable.
But knowledge trapped in one person's head is fragile.
The opportunity is to turn tribal knowledge into structured
workflow.
This is where OnnX starts
This is the premise behind OnnX.
I believe healthcare billing has been treated too heavily as
a downstream problem.
Most of the problem starts upstream.
The question is not simply:
How do we work more denials?
It is:
How do we reduce the number of claims that need to be
worked?
That requires looking earlier.
At the information.
At the handoffs.
At the workflow.
At the point where a missing or inconsistent fact first
appears.
The thesis is simple:
Healthcare billing is fundamentally a data-structure
problem before it becomes a denial-management problem.
If the information is structured correctly early enough,
downstream work can become simpler.
Not zero.
Simpler.
That distinction matters.
Eliminating middlemen does not mean eliminating humans
There is another misconception worth clearing up.
When I talk about reducing middlemen, I do not mean
eliminating people.
Medical billers are not the problem.
Physicians are not the problem.
Front-desk staff are not the problem.
The problem is unnecessary correction loops between
people.
A better system should make humans more effective.
The biller should spend time on exceptions.
The physician should spend time on patients.
The office manager should spend time improving the practice.
The system should handle predictable information movement.
That is a healthier division of labor.
The future of healthcare billing may be upstream
The industry has spent years building tools around:
coding
claims
denials
appeals
A/R
collections
Those functions matter.
But the next generation of revenue-cycle technology may
increasingly move upstream.
Before the claim.
Before the denial.
Before the appeal.
Before the A/R problem.
The question becomes:
Can we identify the risk while there is still time to do
something about it?
That is a much more interesting problem.
From denial management to denial prevention
The language matters.
Denial management asks:
“How do we recover this money?”
Denial prevention asks:
“Why did this happen?”
Upstream revenue intelligence asks:
“What information was missing or inconsistent before the
claim was created?”
The third question is where the leverage becomes
interesting.
Because if you can prevent the same defect 100 times, you
don't need to recover those 100 claims.
You never lose the time.
You never create the A/R.
You never create the appeal.
You never create the follow-up.
You never create the patient confusion.
The best denial is the denial that never exists.
A practical AI architecture
For independent physician practices, I would think about AI
in four layers.
Layer 1: Extract
Pull useful information from clinical and operational
sources.
Layer 2: Structure
Turn scattered information into usable fields and
relationships.
Layer 3: Validate
Compare the information against deterministic requirements
and known patterns.
Layer 4: Escalate
Send genuine exceptions to the human who needs to make the
judgment.
That is very different from:
“Let AI run the billing department.”
That sounds exciting.
It also sounds like the beginning of a very interesting
compliance meeting.
The goal isn't fewer employees
This matters.
The goal should not be:
“How many people can we eliminate?”
The better question is:
“How much unnecessary work can we eliminate?”
A practice may choose to use the recovered capacity for
growth.
More patients.
Better patient communication.
Faster authorization.
More accurate follow-up.
Better staff retention.
Or simply less overtime.
Technology creates options.
The practice decides how to use them.
The best technology may be invisible
Healthcare often celebrates visible technology.
A new dashboard.
A new AI assistant.
A new application.
A new portal.
A new interface.
But the most valuable technology may be the thing the staff
barely notices.
The authorization is identified earlier.
The missing information is surfaced before submission.
The biller no longer has to hunt through five systems.
The physician gets fewer clarification messages.
The same denial stops recurring.
Nobody throws a parade.
That's fine.
Boring is often what operational excellence looks like.
What should physicians stop doing?
Stop assuming revenue cycle is purely an administrative
function.
Stop assuming the biller can fix everything downstream.
Stop celebrating heroic rework as evidence of a strong
process.
Stop measuring success only by collections.
Stop buying technology simply because it has AI in the
product description.
Stop accepting repeated problems as “just how healthcare
works.”
And stop asking:
“Who made the mistake?”
Start asking:
“Why did the system make the mistake easy to make?”
That question produces better answers.
What should clinic owners start doing?
Start measuring recurring failure.
Start measuring rework hours.
Start identifying where information disappears.
Start documenting payer-specific patterns.
Start involving billing earlier in workflow design.
Start asking physicians what documentation creates
unnecessary clarification.
Start asking billers what information they wish they had
earlier.
Start looking at the revenue cycle as one system.
Because it is one system.
The org chart is not the workflow.
The uncomfortable question
Here is the question I would ask every physician owner:
If your best biller quit tomorrow, how much of your
revenue cycle would actually function?
Don't answer quickly.
Think about it.
If the answer is:
“Pretty much everything.”
Excellent.
If the answer is:
“Honestly, we'd be in trouble.”
Then your biller is not the problem.
Your system is dependent on tribal knowledge.
That is fixable.
Another uncomfortable question
Ask:
How many hours did your practice spend last month
correcting information that already existed somewhere in your systems?
Not creating new information.
Correcting information.
Searching for information.
Re-entering information.
Confirming information.
Sending information again.
If the answer is large, you have discovered a hidden labor
expense.
And perhaps a technology opportunity.
One more
Ask your biller:
“What are the three problems you are tired of seeing?”
Do not ask for a list of 50.
Three.
Then ask:
“Which one could we prevent?”
That is where your next operational improvement may be
hiding.
Fatouma's journey gives us the metaphor
Fatouma had to travel because the connection between her
diagnosis and treatment had been broken by circumstances far beyond her
control.
Her story should remind us that healthcare is not simply
about whether treatment exists.
It is about whether the patient can successfully move
through the chain required to receive it.
In Sudan, that chain was shattered by war.
In American practices, the chain can fracture for very
different reasons.
Insurance.
Authorization.
Documentation.
Eligibility.
Coding.
Technology.
Workflow.
Human handoffs.
The consequences are not equivalent.
But the principle remains:
When the connection breaks, someone carries the burden.
The claim is not the patient
This sounds obvious.
But sometimes our workflows make us forget.
The patient came first.
The care came first.
The clinical decision came first.
The documentation came first.
The claim came later.
So when the claim fails, we should not lose sight of the
sequence.
The question should not simply be:
“How do we fix the claim?”
It should be:
“What happened before the claim that made it fail?”
That is a much more powerful question.
The five-minute denial investigation
Take one denial.
Not 1,000.
One.
Ask:
What happened?
Then reconstruct the timeline.
Patient scheduled.
Insurance captured.
Eligibility checked.
Authorization requested.
Patient seen.
Documentation completed.
Coding performed.
Claim created.
Claim submitted.
Claim denied.
Now mark the exact moment the information became wrong,
incomplete or disconnected.
You may be surprised.
The denial may have occurred on Monday.
The actual failure may have happened two weeks earlier.
That is the entire point.
The revenue cycle is a story
Every claim tells a story.
Where did the patient enter?
What did they need?
What did the practice know?
What did the physician document?
What did the payer require?
What information moved?
What information didn't?
Where did the story change?
Where did someone have to guess?
Where did someone have to re-enter information?
Where did someone have to call?
Where did someone have to appeal?
The claim is the final chapter.
If you only read the final chapter, you may never understand
the book.
What if we designed billing like clinical medicine?
Physicians do not normally wait until a patient is
critically ill before collecting basic information.
They take a history.
They examine the patient.
They order tests.
They assess risk.
They intervene.
They monitor.
They adjust.
Revenue cycle should increasingly operate the same way.
Don't wait for the claim to become critically ill.
Assess it earlier.
Identify risk.
Intervene.
Monitor.
Learn.
That is preventive revenue cycle management.
The biggest opportunity may be prevention
The healthcare industry has become extraordinarily good at
recovering money.
Appeals.
Denials.
A/R.
Follow-up.
Collections.
But recovery is expensive.
Prevention is usually cheaper.
If a $500 claim requires 45 minutes of staff work to
recover, the practice may technically recover $500 while quietly spending a
meaningful portion of its value in labor.
If the problem could have been prevented in 30 seconds at
scheduling, the economics change dramatically.
That is why upstream intervention matters.
Three lessons for independent practices
Lesson 1: Find the earliest point where the problem could
have been prevented
Don't start with the denial.
Walk backward.
Lesson 2: Turn tribal knowledge into system knowledge
If one employee knows the answer, the organization does not
yet own the answer.
Lesson 3: Measure friction
Track the work nobody wants to measure:
Re-entry.
Correction.
Follow-up.
Clarification.
Portal work.
Appeals.
Manual review.
Those are the hidden costs of a fragmented revenue cycle.
The future of RCM is not another queue
Healthcare already has enough queues.
Inbox queues.
Authorization queues.
Denial queues.
Appeal queues.
A/R queues.
Task queues.
Work queues.
If the answer to every workflow problem is another queue,
eventually the organization becomes one giant queue.
The future should be different.
The system should increasingly prevent work from entering
the queue when the work was unnecessary in the first place.
That's the opportunity.
And that brings us back to Fatouma
Fatouma kept going.
She traveled because she needed care.
She returned because continuity mattered.
She crossed extraordinary distances because the connection
between patient and treatment had been broken.
Her story should not be reduced to a metaphor for American
billing.
It deserves to remain what it is:
the story of a woman with cancer who kept searching for
treatment in a healthcare system devastated by war.
But her journey can still make us ask a question about our
own systems.
How much unnecessary distance are we creating?
Not physical distance.
Information distance.
The distance between what the physician knows and what the
biller receives.
The distance between what the payer requires and what the
practice captures.
The distance between a documentation problem and the moment
someone discovers it.
The distance between a patient encounter and payment.
Every unnecessary mile costs something.
Sometimes money.
Sometimes time.
Sometimes attention.
Sometimes trust.
The provocative conclusion
Healthcare does not necessarily need more people working
harder at the bottom of the revenue cycle.
It may need better information moving through the top.
That is the contrarian idea.
The denial queue may be a symptom of upstream design.
The exhausted biller may be a symptom of fragmented
information.
The physician's administrative burden may be a symptom of
workflow design.
The revenue leak may be a symptom of a data-structure
problem.
And AI may be most valuable not when it replaces people, but
when it helps the right information reach the right person before the problem
becomes expensive.
That is a very different vision of healthcare automation.
It is less glamorous.
More practical.
And potentially much more valuable.
The claim should not have to take the journey
Fatouma had to travel hundreds of miles to reach cancer
treatment.
Your claim should not have to travel through six people,
four portals, three spreadsheets and two inboxes before someone discovers that
a piece of information was missing.
The patient should not have to carry the consequences of a
disconnected workflow.
The physician should not have to become a part-time
insurance specialist.
The biller should not have to become an information
archaeologist.
And the practice owner should not need a spreadsheet called:
FINAL_FINAL_USE_THIS_ONE_v9.xlsx
to understand where the money went.
The system should simply work better.
Not perfectly.
Better.
Earlier.
More predictably.
With fewer correction loops.
That is what upstream revenue-cycle thinking is about.
And that is why the most important billing question may no
longer be:
“How do we recover this denial?”
It may be:
“Why did we allow this denial to be created?”
That question changes the entire conversation.
Five questions every physician owner should ask this week
1. What is our most common denial?
Not the biggest denial.
The most common.
2. Where did that problem actually begin?
Not where it was discovered.
Where did it originate?
3. How many staff hours do we spend fixing it?
Calculate the labor.
4. What information could have prevented it?
Identify the missing connection.
5. Can we move that information upstream?
If yes, start there.
Three things to measure for the next 30 days
Rework hours.
How much time is spent correcting preventable problems?
Recurring failure patterns.
Which problems keep appearing?
Prevented leakage.
How many potential denials were identified before
submission?
If those numbers improve, your practice may be becoming
healthier even before your collection report shows it.
The question I want to leave you with
What is the one revenue-cycle problem your practice keeps
fixing over and over again?
And the more uncomfortable question:
Why does your system keep creating it?
Tell me in the comments.
If you have seen the same problem inside your practice, repost
this article so another physician, clinic owner or medical biller can add
their experience.
Because the next major improvement in medical billing may
not come from working harder on the claim.
It may come from finally fixing what happened before the
claim existed.
Free resource for independent clinics
I have placed a free revenue-cycle resource in the
Featured section of my LinkedIn profile for physicians and independent
clinic owners.
There is no signup required there.
If you are trying to identify where revenue leakage actually
begins inside your practice, start with the workflow—not the denial queue.
About the Author
Dr. Daniel Cham is a physician, healthcare strategist
and medical technology consultant focused on the intersection of clinical
practice, healthcare operations and medical billing.
He is the founder of OnnX, an AI-powered medical billing
SaaS focused on eliminating unnecessary middlemen and reducing revenue-cycle
friction for small and medium-sized clinics.
His work focuses on a simple premise:
Most of the problem starts upstream.
Instead of building more technology around correction loops,
OnnX explores how better data structure, workflow intelligence and earlier
intervention can make the revenue cycle more predictable.
Connect with Dr. Cham on LinkedIn and explore his healthcare
work through his profile and website.
References
- Neiman,
Sophie. “In Sudan, attacks on hospitals force patients to make
dangerous journeys.” STAT, September 18, 2026. The primary source
for the stories of Fatouma Mahdi Ahmed Saeed, Ifrah Ahmed, Abasst
Abonja, and Dr. Tom Catena.
- American
Medical Association. “Small Workflow Changes Can Make a Big
Impact: Pearl of the Month.” AMA STEPS Forward, September 16, 2026.
Includes the current-week statement from Dr. Liz Harry, chief
well-being officer at Michigan Medicine, on redesigning workflows to
address the source of distress.
- Medical
Group Management Association. “Detecting and fixing leaks across
the revenue cycle.” MGMA Stat, January 7, 2026. Reports the MGMA
poll in which 48% of medical-group leaders identified denials and
appeals as their largest revenue-cycle leakage category, followed by
front-end issues at 23%.
This article is intended for educational discussion and
does not constitute legal, coding, billing, compliance or medical advice.
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#ClinicManagement #OnnX
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