A mother survived sepsis, lost all four limbs, went on dialysis—and then received a kidney from her brother. Her story exposes a problem hiding in plain sight across healthcare: the crisis we see is often only the final symptom.
“We’re trying to get out of the theoretical, and into
real clinical impact.” — Sammy
Chouffani El Fassi, Duke University, quoted in the Financial Times
THE HUMAN STORY
Brie Bauer's Life Changed in Hours
Brie Morgan Bauer was pregnant with her third child when
everything changed.
She was just twenty-seven weeks pregnant.
Then came an emergency C-section.
Then infection.
Then septic shock.
Then multiple organ failure.
Brie spent ten days in a coma.
Doctors ultimately had to amputate both arms and both legs
to save her life.
Her baby survived.
Brie survived.
But survival came with an extraordinary price.
Her kidneys had been severely damaged.
She became dependent on dialysis.
For hours every week, a machine became part of her life.
Then came another problem.
She needed a kidney transplant.
Her family began looking for a donor.
Her older brother, George Morgan, was tested.
He was a perfect match.
George donated his kidney to Brie in March twenty
twenty-six.
The transplant was successful.
Brie was able to stop dialysis and focus on rehabilitation,
her children and rebuilding her life.
The story is extraordinary.
But there is another lesson hiding inside it.
The most visible crisis was not the beginning of the story.
It was the consequence of everything that came before it.
That distinction matters enormously in healthcare.
It also matters in medical billing.
THE CONTRARIAN TAKE
The Denial May Be the Crime Scene
A denial appears at the end of a process.
That makes it visible.
It does not make it the cause.
A claim is denied.
The billing team sees it.
Someone opens the account.
Someone checks the payer portal.
Someone looks at the documentation.
Someone calls the payer.
Someone sends a corrected claim.
Someone asks the physician for additional information.
Someone enters something again.
Someone waits.
Someone follows up.
Someone documents the follow-up.
Eventually, someone gets paid.
Everyone celebrates.
But here is the uncomfortable question:
Why did the claim become a problem in the first place?
Maybe eligibility information was wrong.
Maybe authorization was missing.
Maybe the authorization existed but did not match the
service.
Maybe documentation did not contain the information the
payer required.
Maybe the clinical note was incomplete.
Maybe the wrong payer information moved through the system.
Maybe a handoff failed.
Maybe nobody owned the transition between scheduling,
authorization, clinical documentation and billing.
The denial was merely where the failure became visible.
The fire may have started much earlier.
The denial is the smoke. The fire started somewhere else.
The Hidden Lesson in Brie’s Story
Brie's story is not a metaphor for billing.
It is a reminder about systems.
A visible crisis can be the final manifestation of a much
longer chain of events.
In medicine, clinicians are trained to ask:
Where did this problem begin?
Not merely:
Where do I see it now?
That distinction is fundamental to diagnosis.
Yet healthcare administration often does the opposite.
The denial arrives.
The denial team handles the denial.
The problem disappears from the dashboard.
The organization calls that improvement.
But did the underlying process improve?
Or did the organization simply become better at cleaning up
after itself?
That is the question worth asking.
THE HEALTHCARE FIX-IT ECONOMY
The Denial Is Not Your Enemy
Here is the contrarian part.
Stop treating denials as merely a nuisance.
A denial can be valuable information.
It can tell you where your system is leaking.
It can reveal a broken handoff.
It can expose inconsistent documentation.
It can identify payer-specific friction.
It can show that your staff is repeatedly performing the
same corrective action.
It can reveal that physicians are being pulled into
administrative work that should never have reached them.
In other words:
Your denial queue may be an operational X-ray.
The mistake is assuming that the X-ray is the disease.
It is not.
It is evidence.
The question is what you do with the evidence.
Welcome to the Healthcare Fix-It Economy
Healthcare has become extraordinarily good at fixing things.
We have denial teams.
Appeals teams.
Coding teams.
Authorization teams.
Eligibility teams.
Revenue-cycle consultants.
Outsourced billing companies.
Clearinghouses.
Scrubbers.
Dashboards.
Work queues.
Payer portals.
Fax systems.
Spreadsheets.
And now AI.
We have built an enormous ecosystem around correcting
information after it has already gone wrong.
Sometimes those tools are necessary.
Sometimes they are essential.
But there is an uncomfortable possibility:
We may be getting very good at managing the consequences
of bad system design.
Healthcare has created an entire economy around the
sentence:
“Something went wrong. Who can fix it?”
What if the better question is:
“Why does this keep going wrong?”
The Invisible Employee
There is another cost hiding inside every correction loop.
Human time.
A claim does not repair itself.
Someone has to touch it.
Someone has to investigate it.
Someone has to search for information.
Someone has to make a phone call.
Someone has to open a portal.
Someone has to upload a document.
Someone has to send a fax.
Someone has to wait for a response.
Someone has to follow up.
That person is often invisible in the financial analysis.
The organization sees the denial.
It sees the dollar amount.
It sees the eventual payment.
It does not always see the labor required to make the
payment happen.
That labor is real.
And it is expensive.
WHERE THE MONEY REALLY DISAPPEARS
The Claim That Cost More Than It Earned
Imagine a relatively modest claim.
The clinical work is complete.
The patient was treated.
The physician documented the encounter.
The claim is submitted.
Then something goes wrong.
A missing authorization triggers a denial.
The biller investigates.
The front desk is contacted.
The physician's office is contacted.
A document is located.
The claim is corrected.
It is resubmitted.
The payer asks for something else.
The process repeats.
Eventually, the claim gets paid.
The accounting system records revenue.
But the revenue-cycle team sees something else.
Work.
The payment may look successful.
The process may still be economically irrational.
This is why simply measuring collections can be misleading.
You should also measure the human effort required to
collect.
The Hidden FTE Problem
Many practices have what could be called a hidden staffing
problem.
Not because the organization officially employs another
person.
Because enough administrative friction has accumulated to
create the equivalent workload of another employee.
A few minutes here.
A correction there.
An authorization phone call.
A portal message.
A documentation request.
A claim resubmission.
A physician signature.
A follow-up.
Then another follow-up.
None of these tasks looks enormous.
Together, they become a job.
And sometimes that job does not exist because the practice
needs more people.
It exists because the system creates unnecessary work.
That distinction matters.
Adding another person can increase capacity.
It does not necessarily reduce friction.
THE PATIENT JOURNEY
The Patient Doesn't Experience Your Org Chart
Patients do not experience your departments.
They experience your system.
They do not care whether the problem belongs to:
Scheduling.
Front desk.
Clinical staff.
Prior authorization.
Coding.
Billing.
Revenue cycle.
IT.
Compliance.
The payer.
The clearinghouse.
From the patient's perspective, it is simply:
“The healthcare system.”
That is why internal boundaries can become invisible sources
of patient frustration.
The organization says:
“That isn't our department.”
The patient hears:
“Nobody owns this.”
The Front Desk Is Part of Revenue Cycle
This is one of the most underappreciated ideas in
independent practice.
Revenue cycle does not begin when the claim reaches billing.
It begins when patient information enters the system.
Insurance.
Demographics.
Coverage.
Referral requirements.
Authorization requirements.
Scheduling details.
Clinical information.
Documentation.
Every downstream transaction inherits the quality of the
information that came before it.
A billing department can be extraordinarily competent and
still spend its day correcting problems created upstream.
That does not mean the front desk is doing a bad job.
It means the system may be asking humans to compensate for
variability that the system itself should prevent.
The Biller Is Not the Problem
This point deserves emphasis.
Your biller may be your most reliable employee.
That does not mean your process is reliable.
In fact, exceptional billers can sometimes hide broken
systems.
They remember payer quirks.
They know which portal to use.
They know who to call.
They know which physician needs which reminder.
They know how to reconstruct missing information.
They know the workaround.
They carry institutional memory inside their heads.
That makes them valuable.
It also creates risk.
Because when the hero leaves, the system suddenly appears
broken.
Maybe the system was always broken.
The employee was simply compensating for it.
DENIALS AS DIAGNOSTIC DATA
Your Denial Queue Is an Operational X-Ray
Start looking at denials differently.
Do not merely ask:
“How much did we recover?”
Ask:
“Where did this problem originate?”
That single question changes the conversation.
Suppose the same denial appears repeatedly.
Do not celebrate the team's recovery rate.
Investigate the pattern.
Was eligibility wrong?
Was authorization incomplete?
Was the wrong information captured?
Was documentation missing?
Was a payer requirement misunderstood?
Was a clinical workflow disconnected from an administrative
workflow?
Was information entered multiple times?
Was information copied manually?
Was the same information requested by multiple people?
Those questions turn the denial queue into an improvement
system.
The Question That Changes the Meeting
The typical revenue-cycle meeting asks:
“How many denials did we clear?”
Try asking:
“How many of these denials should have existed at all?”
That is a very different question.
It moves the organization from productivity to prevention.
It changes the conversation from:
“Are our people working hard enough?”
to:
“Why are our people having to work this hard?”
That is where meaningful operational improvement begins.
The Denial Autopsy
Every recurring denial deserves an autopsy.
Not blame.
Not finger-pointing.
An autopsy.
Trace the information backward.
Where did the patient enter the system?
Where was insurance captured?
Where was eligibility checked?
Where was authorization determined?
Where was clinical information documented?
Where did the information change hands?
Where was information re-entered?
Where did someone have to make a judgment manually?
Where did someone have to search for information that should
already have been available?
Where did the correction begin?
Then ask the most important question:
Could the system have prevented this?
If yes, you have found an upstream opportunity.
WHAT CURRENT HEALTHCARE NEWS IS TELLING US
Insurance Denials Are More Complicated Than the Number
Suggests
The problem is not theoretical.
Current healthcare reporting continues to show how much
administrative friction exists between clinical decisions and actual access to
care.
Recent reporting from the Los Angeles Times found
that patients who appeal insurance denials frequently prevail, with some plans
showing very high reversal rates. The reporting also highlighted substantial
prior-authorization denial activity across major insurers.
The important operational lesson is not that every denial is
wrong.
It is more basic.
A denial creates work.
Someone has to interpret it.
Someone has to decide whether to appeal.
Someone has to gather information.
Someone has to communicate.
Someone has to wait.
That friction eventually reaches patients and clinicians.
Prior Authorization Has Become a Workflow Problem
Prior authorization is often discussed as an insurance
problem.
It is also a workflow problem.
A physician decides treatment is appropriate.
The patient needs the treatment.
The practice needs authorization.
Information must be assembled.
The information must reach the payer.
The payer evaluates it.
The payer responds.
The response must return to the practice.
The practice must act.
Every handoff creates an opportunity for friction.
The more fragmented the process, the more humans become the
integration layer.
That is expensive.
And it is exhausting.
Some Payers Are Beginning to Simplify the Journey
There are also signs of movement in the other direction.
Recent reporting indicates that some insurers are
experimenting with reducing or bundling certain authorization requirements.
Aetna, for example, announced plans involving bundled
cancer-treatment authorizations beginning in twenty twenty-seven.
The concept is straightforward.
Instead of repeatedly asking for approval throughout a
treatment pathway, simplify the administrative journey for certain patients and
treatments.
That points toward a larger principle:
Good healthcare administration should reduce unnecessary
decisions, not multiply them.
The fewer unnecessary handoffs, the fewer opportunities for
information to disappear.
THE AI PROBLEM
AI Won't Save a Broken Workflow
Now we arrive at the favorite word in healthcare technology:
AI.
AI can be useful.
AI can extract information.
AI can summarize documentation.
AI can identify missing data.
AI can classify claims.
AI can prioritize work.
AI can automate repetitive tasks.
But AI can also make a broken process faster.
That is not necessarily improvement.
If you automate a bad workflow, you may simply produce bad
outcomes more efficiently.
The Financial Times recently examined this problem in
healthcare AI, highlighting the gap between technical validation and evidence
of real-world clinical impact.
The same principle applies to administrative AI.
Do not ask only:
“Can the model do this?”
Ask:
“Does doing this actually improve the system?”
Stop Asking Whether AI Works
The question is too vague.
Works for what?
Works where?
Works under what conditions?
Works for whom?
Works with what data?
Works compared with what?
Works after implementation?
Works without creating new review work?
Works without increasing the number of exceptions?
Works without forcing staff to monitor another dashboard?
Works without creating another correction loop?
The useful question is:
What measurable work disappears because this technology
exists?
That is a much harder question.
It is also a much better one.
AI Should Remove Work, Not Merely Move It
Imagine a system that claims to automate claims.
But staff still review every AI recommendation.
Someone still checks the data.
Someone still corrects the output.
Someone still moves information between systems.
Someone still handles exceptions.
Someone still watches another dashboard.
Is the work gone?
Or did the work move?
Technology should not receive credit simply because the
human task changed location.
The goal is less unnecessary work.
Not more sophisticated work queues.
THE ONNX THESIS
Medical Billing Is Not Really a Billing Problem
This is where the OnnX thesis begins.
Medical billing appears to be about claims.
But claims are downstream.
The actual problem often begins earlier.
Patient information.
Insurance verification.
Authorization.
Documentation.
Coding.
Claim creation.
Payment.
Each stage depends on the quality of what came before it.
If information is incomplete upstream, downstream systems
compensate.
If information is inconsistent, downstream systems
compensate.
If information is fragmented, downstream systems compensate.
If information has to be manually re-entered, downstream
systems compensate.
Eventually someone says:
“We need better billing software.”
Maybe.
But perhaps the deeper problem is:
The organization is asking billing to repair information
that should have been correct before billing ever saw it.
The Upstream Revenue Cycle
Think of the revenue cycle as a chain:
Patient information → insurance verification →
authorization → documentation → claim → payment
Every arrow matters.
Most organizations spend enormous energy optimizing the
final arrow.
But a weak early arrow can contaminate everything
downstream.
This is why OnnX starts upstream.
Not because downstream billing does not matter.
It does.
But because the cheapest error to fix is often the one you
prevent before it travels through the organization.
Eliminate the Correction Loop
Healthcare contains countless correction loops.
Enter.
Review.
Correct.
Re-enter.
Submit.
Reject.
Investigate.
Correct again.
Submit again.
Wait.
Follow up.
Repeat.
Every loop creates cost.
Every loop creates delay.
Every loop creates another opportunity for human error.
The strategic goal should therefore be simple:
Reduce the number of times information has to be
corrected after it enters the system.
That is not glamorous.
It is not futuristic.
It is operationally important.
And boring is underrated.
Boring is what reliable systems feel like.
THE PRACTICAL PLAYBOOK
Start With a Representative Denial Sample
You do not need a massive transformation program.
Start small.
Take a representative sample of recent denials.
Do not begin by buying software.
Do not begin by blaming the payer.
Do not begin by blaming billing.
Trace the cases.
Ask where each problem began.
Look for patterns.
Maybe most problems originate in eligibility.
Maybe authorization is the largest source.
Maybe documentation creates the bottleneck.
Maybe one payer creates a disproportionate amount of manual
work.
Maybe the same physician receives repeated requests.
Maybe one workflow creates dozens of downstream corrections.
The pattern is the prize.
Measure the Human Cost
Most practices measure dollars.
Also measure minutes.
How much staff time does a denial consume?
How many people touch it?
How many systems are opened?
How many phone calls occur?
How many messages are exchanged?
How many times is the same information entered?
How many times does the physician become involved?
How many days does the issue remain unresolved?
The organization should know not only the financial cost
of failure but also the human cost of failure.
Introduce the Preventable Work Ratio
One useful internal metric is the Preventable Work Ratio:
Hours spent correcting preventable problems ÷ total
revenue-cycle labor hours
You do not need an industry benchmark to make this useful.
You need consistency.
Track it over time.
If the ratio falls, your system may be getting better.
If your staff becomes faster at correcting the same mistakes
while the ratio stays high, you may have improved productivity without
improving the underlying process.
That distinction is critical.
Measure Touches Per Claim
Another simple metric:
Touches per claim.
How many people interact with the claim?
How many times does the claim move between queues?
How many times does information get re-entered?
How many manual decisions occur?
A claim that moves cleanly through the system is
fundamentally different from a claim that becomes an administrative relay race.
Your goal should not merely be faster touches.
It should be fewer unnecessary touches.
THE UPSTREAM AUDIT
Map the Journey
Write down the actual workflow.
Not the workflow in the policy manual.
The real workflow.
What happens when a patient schedules?
What happens when insurance information arrives?
What happens before the visit?
What happens during documentation?
What happens after the visit?
What happens before billing?
Where does information move?
Where does it get copied?
Where does someone make a manual decision?
The truth usually lives in the gaps between departments.
Identify the Handoffs
Every handoff is a potential failure point.
Front desk to clinical staff.
Clinical staff to authorization.
Authorization to scheduling.
Clinical documentation to coding.
Coding to billing.
Billing to payer.
Payer back to billing.
The more handoffs you have, the more important information
continuity becomes.
Find Repeated Corrections
Look for repetition.
Same payer.
Same physician.
Same denial type.
Same missing field.
Same documentation request.
Same portal.
Same manual correction.
Repetition is evidence.
Separate Preventable From Unavoidable
Not every denial is preventable.
Not every payer rule is unreasonable.
Not every administrative problem can be eliminated.
That distinction matters.
The goal is not to pretend healthcare can become
frictionless.
The goal is to identify friction that should not exist.
Fix One Thing
Do not redesign everything at once.
Pick one recurring failure.
Fix the upstream cause.
Measure the result.
Then move to the next.
That is how operational improvement becomes sustainable.
THE HUMAN COST
Healthcare's Hidden Currency Is Time
Money is visible.
Time is not.
A physician loses fifteen minutes.
A biller spends twenty minutes chasing a document.
A front-desk employee spends ten minutes on a payer portal.
A practice administrator spends an hour investigating a
recurring issue.
Multiply those moments across weeks and months.
Suddenly the organization has created an invisible
department.
Except nobody budgeted for it.
The work simply appeared.
Administrative Burden Becomes Patient Burden
Administrative friction does not stay administrative.
It can delay care.
It can delay payment.
It can delay scheduling.
It can frustrate clinicians.
It can frustrate patients.
It can create additional calls.
It can create additional paperwork.
It can consume time that could have been spent with
patients.
That is why revenue-cycle improvement is not merely a
financial exercise.
It can also be a patient-experience exercise.
WHAT WE GET WRONG
Myth: More Billers Will Fix It
More staff can help when volume is the problem.
But if the process itself creates unnecessary work, more
staff can simply increase the capacity to process unnecessary work.
You have built a faster conveyor belt for the wrong boxes.
The better question is:
What work should disappear?
Myth: A Clean Claim Means a Clean System
A clean claim is good.
It is not proof of upstream excellence.
You can have a high clean-claim rate while staff spend
enormous amounts of time creating those clean claims.
The final output does not always reveal the complexity
required to produce it.
Myth: Outsourcing Solves the Problem
Outsourcing can be useful.
Specialization can create efficiencies.
But moving a broken process outside the organization does
not automatically fix the process.
Sometimes the logo changes.
The problem does not.
If information is poor before it reaches the outsourced
partner, someone still has to deal with that problem.
Myth: More Technology Means Better Operations
Technology is a tool.
It is not a strategy.
A practice can have sophisticated technology and terrible
workflows.
It can have basic technology and excellent operational
discipline.
The question is not:
“How much technology do we have?”
The question is:
“How much unnecessary work does our technology
eliminate?”
ETHICS, COMPLIANCE AND ACCOUNTABILITY
Technology Does Not Transfer Responsibility
Automation does not eliminate accountability.
If software makes a recommendation, someone must understand
how that recommendation is used.
If AI extracts information, someone must know whether the
extraction is reliable enough for the decision being made.
If a workflow is automated, the practice still owns the
consequences.
Technology can change who performs the task.
It does not automatically change who is responsible for the
outcome.
The Ethical Question
Healthcare administration has an ethical dimension.
When administrative friction delays care, the burden does
not fall equally on everyone.
Patients with more time, knowledge, confidence or resources
may be better positioned to navigate complexity.
Others may simply give up.
That makes administrative simplicity more than an efficiency
goal.
It can also be a question of access.
The ethical goal is not to eliminate every control.
Controls exist for legitimate reasons.
The goal is to distinguish necessary friction from
unnecessary friction.
FAILURE IS INFORMATION
Stop Hiding Workarounds
Here is another uncomfortable idea.
Your workarounds are data.
When employees create spreadsheets, sticky notes, personal
checklists and private tracking systems, do not immediately tell them to stop.
Ask why they created them.
The workaround may be compensating for a missing capability
in the official workflow.
The spreadsheet is not necessarily the problem.
It may be the evidence.
Heroic Employees Can Hide Broken Systems
Every practice has someone who knows how everything works.
The person who remembers every payer rule.
The person who knows which number to call.
The person who can fix almost any claim.
The person everyone asks when something breaks.
These people are invaluable.
But organizations should be careful about confusing heroic
performance with system quality.
A great system does not require heroes every afternoon.
A great system makes ordinary work ordinary.
A LITTLE HEALTHCARE HUMOR
The Seven-Step Solution to a Four-Step Problem
Healthcare sometimes solves a simple problem with a
committee.
Then the committee creates a workflow.
The workflow creates an exception.
The exception requires a spreadsheet.
The spreadsheet creates a meeting.
The meeting creates a dashboard.
The dashboard requires a new employee.
The new employee asks why the process exists.
Someone replies:
“That is just how we've always done it.”
And somewhere, quietly, another fax machine turns on.
We laugh because it is familiar.
But the joke contains a serious operational lesson.
Complexity has a way of becoming institutionalized.
Eventually nobody remembers the original reason.
They only remember the workaround.
THE FUTURE
The Future of Medical Billing Is Less Billing
The future should not be about creating increasingly
sophisticated people to chase increasingly sophisticated problems.
It should be about reducing the number of problems that
reach them.
That means better data capture.
Better information continuity.
Better eligibility verification.
Better authorization workflows.
Better documentation alignment.
Better handoffs.
Better exception management.
Better visibility into where errors originate.
And yes, better technology.
But technology should support the architecture.
Not substitute for it.
From Reactive to Deterministic
A reactive revenue cycle asks:
“What went wrong?”
A more deterministic revenue cycle asks:
“How do we make this class of problem less likely to
happen?”
That is a profound difference.
Reactive systems depend on people noticing problems.
Deterministic systems reduce the number of problems that
require noticing.
The first model needs more firefighters.
The second model needs fewer fires.
The goal is not better firefighters. Fewer fires.
WHAT BRIE'S STORY REALLY TEACHES US
The Visible Crisis Is Rarely the Whole Story
Brie Bauer's story is ultimately about something much larger
than transplantation.
It is about the difference between treating the visible
crisis and understanding the chain that produced it.
Her medical team had to respond to an emergency.
They had to save her life.
Then they had to deal with the consequences.
Then rehabilitation.
Then dialysis.
Then transplantation.
Then recovery.
Each stage inherited circumstances created by what happened
earlier.
That is how complex systems work.
And that is how revenue cycle works.
The denial at the end of the process inherits decisions made
much earlier.
The billing department inherits the quality of the
information that entered the system.
The physician inherits documentation requirements.
The patient inherits administrative friction.
The organization inherits all of it.
Stop Celebrating the Wrong Victory
A claim gets paid.
Great.
But ask:
How many people touched it?
How much time did it consume?
How many corrections were required?
How many messages were exchanged?
How many payer interactions occurred?
Did anyone have to involve the physician?
Could the problem have been prevented?
If the answer is yes, then payment was the end of the story.
Not the beginning of improvement.
QUESTIONS FOR EVERY CLINIC OWNER
Where Does the Work Really Begin?
Where does your billing team spend time fixing information
that should have been correct earlier?
That question can reveal more than another denial report.
Which Problems Are Actually Upstream?
Which recurring denials are symptoms of upstream workflow
failures?
Look beyond the final denial code.
Look at the journey that produced it.
What Work Could Disappear?
What administrative work could disappear if you redesigned
the process instead of adding another person to it?
That may be the most important operational question of all.
ACTIONS FOR TOMORROW
Pull the Denials
Pull a representative sample.
Trace each case backward.
Do not begin with blame.
Begin with evidence.
Find the Origin
Identify the earliest point where the problem could have
been prevented.
That is where improvement begins.
Calculate the Human Cost
Measure more than dollars.
Measure minutes.
Touches.
Calls.
Messages.
Corrections.
Physician interruptions.
Days delayed.
That is your real operational picture.
FINAL THOUGHTS
Stop Admiring the Fire Department
Healthcare loves heroes.
The physician who stays late.
The nurse who finds the missing information.
The biller who rescues the claim.
The administrator who knows exactly who to call.
The staff member who somehow makes the impossible happen.
We should appreciate those people.
But we should also ask a harder question.
Why does the system require so many heroes?
The strongest organization is not the one with the most
heroic employees.
It is the one that makes heroics less necessary.
That is what good systems do.
They absorb complexity so humans do not have to.
What Should We Remember?
Don't just work the denial. Find where the problem began.
Don't just automate the workflow. Question whether the
workflow deserves to exist.
Don't measure how hard your team works. Measure how much
unnecessary work your system creates.
GET INVOLVED
The Provoking Question
What if your biggest revenue-cycle problem is not the
denial?
What if the denial is simply the first place your
organization can finally see the problem?
That changes everything.
Because once you stop treating the denial as the disease,
you can start using it as evidence.
And evidence can lead you upstream.
Share the Conversation
If you are a physician, clinic owner, practice administrator
or medical biller, look at your recent denials.
Do not start with the dollar amount.
Start with the origin.
Ask where the information first went wrong.
Then ask how many people had to compensate for that mistake.
What did you find?
Share your experience in the comments.
If you know someone running an independent medical practice
who is buried in denials, prior authorization, payer portals or administrative
correction loops, share this article with them.
The conversation should not be about how to become better at
fixing broken workflows.
It should be about how to build fewer broken workflows.
ABOUT THE AUTHOR
Dr. Daniel Cham
Dr. Daniel Cham is a physician, healthcare strategist
and founder of OnnX, an AI-powered medical billing SaaS designed to
eliminate middlemen and reduce administrative correction loops for small and
medium-sized physician-owned clinics.
His work focuses on the intersection of clinical operations,
healthcare administration, revenue cycle management and practical AI.
The central OnnX thesis is simple:
Most of the problem starts upstream.
When clinical and operational information is structured
correctly at the point of capture, downstream billing becomes more predictable.
The objective is not to replace physicians.
It is to reduce the friction surrounding them.
CONTINUE THE CONVERSATION
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REFERENCES AND FURTHER READING
Human Story
The reporting on Brie Morgan Bauer's medical journey and
kidney donation from her brother George Morgan provides the human foundation
for this article.
People
— Brie Bauer receives kidney from her brother
KCTV
— Living organ transplants give new hope
Insurance Denials and Prior Authorization
Current reporting continues to document the administrative
complexity surrounding insurance denials and prior authorization.
Los
Angeles Times — Patients who fight health insurance denials often win
KFF
— Medicare Advantage prior authorization data
Practice Administrative Burden
MGMA reporting illustrates the continuing difficulty
practices face with prior-authorization turnaround despite requirements
intended to accelerate decisions.
MGMA
— Prior authorization turnaround
Medical AI
Recent Financial Times reporting examines the gap
between technical validation and real-world healthcare impact.
Financial
Times — Medical AI has a proof problem
IMPORTANT NOTE
This article is educational and informational.
It does not provide legal, medical, coding, billing or
reimbursement advice.
Healthcare reimbursement rules, payer requirements,
documentation standards and authorization policies vary by payer, jurisdiction,
specialty and patient circumstances.
Practices should verify applicable requirements with
appropriate clinical, legal, compliance, coding and revenue-cycle
professionals.
The operational concepts described here are intended to
encourage process analysis and discussion, not to replace professional advice.
HASHTAGS
#MedicalBilling #RevenueCycleManagement
#HealthcareOperations #HealthcareAI #MedicalPracticeManagement
#PriorAuthorization #ClaimsDenials #PhysicianPractice #IndependentClinics
#HealthcareInnovation #HealthcareAutomation #ClinicalWorkflow #HealthcareLeadership
#PracticeManagement #HealthTech
