A rare-disease rescue in Abu Dhabi exposes a surprisingly familiar problem: healthcare can have all the right information and still fail to connect it at the right moment.
“Through accurate diagnosis, close multidisciplinary
collaboration, and a bone marrow transplant from his father, we were able to
rebuild his immune system and give him the opportunity to grow and live a
healthy life.” — Dr. Mansi Sachdev, Consultant Pediatric Hematology,
Oncology and Bone Marrow Transplantation, Abu Dhabi Stem Cells Centre.
A 13-month-old boy. A father. And almost no room for
delay.
A 13-month-old child in Abu Dhabi had already spent much of
his short life in hospitals.
He suffered recurrent, severe infections.
He struggled to gain weight.
His skin became so severely affected by widespread redness
and continuous peeling that it resembled the appearance of severe burns.
Then doctors discovered something much more serious.
He had a rare inherited immunodeficiency caused by a homozygous
RAG1 mutation, associated with Omenn syndrome, a condition that can
leave children dangerously vulnerable to life-threatening infections.
The family's medical history made the situation even more
urgent.
They had previously lost another child to a similar
condition.
The boy needed a transplant.
But there was no fully matched sibling donor.
Testing showed that both parents were half-matched.
The medical team had a decision to make.
Given the urgency, physicians proceeded with a haploidentical
bone marrow transplant using stem cells donated by his father.
The transplant succeeded.
The child achieved engraftment.
His immune function gradually recovered.
His severe skin condition improved.
The recurrent infections resolved.
He was discharged and continued to gain weight.
The publicly reported story does not identify the child
or his parents by name, so I will not invent names for them.
But it does identify the physicians and institutions
involved.
Dr. Mansi Sachdev, consultant in pediatric
hematology, oncology and bone marrow transplantation at Abu Dhabi Stem Cells
Centre, described the case as one in which accurate diagnosis,
multidisciplinary collaboration and the father's donation came together to
rebuild the child's immune system.
Dr. Maysoon Al Karam, Chief Medical Officer at Yas
Clinic, described the case as an example of what specialized expertise and
advanced treatment can accomplish in a complex immunological condition.
The transplant was performed through collaboration between Yas
Clinic, the Abu Dhabi Stem Cells Centre (ADSCC) and the Abu Dhabi
Bone Marrow Transplant Programme.
And this is where the story gets interesting for
physician-owners.
Because this isn't really a story about bone marrow.
It is a story about information.
The uncomfortable question
What if the biggest problem in healthcare isn't that we lack
information?
What if the problem is that we have the information — but
cannot reliably move it to the person who needs it at the moment it matters?
That sounds abstract.
It isn't.
A rare-disease diagnosis depends on connecting symptoms,
history, laboratory findings, genetics and family history.
A transplant depends on connecting patient information with
donor information.
A successful treatment depends on connecting specialists.
A safe discharge depends on connecting inpatient and
outpatient care.
And a healthy medical practice depends on connecting the
clinical encounter to the administrative and financial processes that follow
it.
Different problems.
Same structural challenge.
The right information has to arrive at the right place at
the right time.
That is why this story caught my attention.
Because physicians are accustomed to thinking about
information as a clinical resource.
But physician-owners should also think about information as
an operational asset.
And that is where medical billing becomes much more
interesting than it first appears.
My contrarian view: billing doesn't begin with the bill
I believe one of the biggest mistakes in revenue-cycle
thinking is hiding in plain sight.
We call it medical billing.
But the billing process does not really begin when a biller
submits a claim.
It begins much earlier.
It begins when the patient schedules.
When demographics are entered.
When insurance information is captured.
When eligibility is checked.
When authorization requirements are identified.
When the physician sees the patient.
When the physician documents.
When the diagnosis is established.
When the service is performed.
When clinical information becomes structured administrative
information.
Only then does the claim become possible.
So why do we keep treating billing as though it begins at
the clearinghouse?
Because that is where the failure becomes visible.
Not where the failure necessarily began.
That distinction is enormously important.
The denial is often the crime scene, not the crime
Imagine a claim is denied.
The billing team sees:
DENIED.
Now the investigation begins.
Someone opens the claim.
Someone checks the payer.
Someone looks at the reason code.
Someone goes into the chart.
Someone searches for documentation.
Someone calls the payer.
Someone checks a portal.
Someone asks the physician a question.
Someone corrects the claim.
Someone resubmits it.
Someone waits.
Someone follows up.
Eventually, money arrives.
Everyone celebrates.
But let's stop for a moment.
What actually happened?
The system allowed a problem to travel through multiple
stages before identifying it.
Then it spent additional labor repairing it.
We call that revenue-cycle management.
Sometimes it is more accurately described as:
revenue-cycle recovery.
That is my first provocation.
If your billing operation is excellent at fixing the same
problem repeatedly, you may not have an excellent system. You may have an
excellent repair crew.
Those are not the same thing.
Healthcare has become very good at creating translators
Consider the number of languages inside a modern medical
practice.
The physician speaks clinical medicine.
The coder speaks coding.
The biller speaks payer rules.
The authorization specialist speaks utilization-management
requirements.
The clearinghouse speaks transaction standards.
The payer speaks adjudication.
The practice manager speaks financial performance.
The EHR speaks structured clinical data.
The patient speaks one language:
“I need care.”
Every translation between these worlds creates potential
information loss.
The problem isn't necessarily that people are incompetent.
The problem is that the system asks people to translate
between systems that were never designed to understand one another naturally.
That is expensive.
It is also exhausting.
Recent news makes this problem impossible to ignore
The American Medical Association recently launched an
initiative to map SNOMED CT clinical concepts to CPT terminology for
prior-authorization use cases.
Why does that matter?
Because the AMA itself describes a problem physicians
already know:
clinical information in an EHR and the coding information
required by payers do not always connect cleanly.
The result?
People manually translate between them.
AMA President Willie Underwood III, MD, MSc, MPH put
the issue bluntly: modernizing prior authorization requires more than
electronic connections between software applications; it also requires trusted,
interoperable terminology that supports real clinical and administrative
workflows.
That sentence contains a bigger lesson for healthcare
technology.
Interoperability isn't just about moving data.
It is about preserving meaning.
A system that successfully transfers the wrong
interpretation has not solved interoperability.
It has simply digitized the misunderstanding.
Electronic does not automatically mean intelligent
This is where I get skeptical of some healthcare technology
marketing.
We have spent years replacing paper with screens.
Fax with portals.
Forms with electronic forms.
Phone calls with electronic messages.
Spreadsheets with dashboards.
And increasingly:
manual workflows with AI.
But digitization and intelligence are not the same thing.
A terrible workflow can be digital.
A fragmented workflow can be digital.
A confusing workflow can be digital.
You can automate a bad process and make the bad process
happen faster.
That is not transformation.
That is acceleration.
The prior-authorization numbers should make physicians
angry
The AMA's 2026 survey of 1,000 practicing physicians
found that physicians complete about 40 prior authorization requests per
week, consuming roughly 13 hours of physician and staff time each week.
94% said prior authorization contributes to burnout. 95% said it
delays access to necessary care. 32% reported that requests are often or
always denied.
There is an even more disturbing finding.
26% of physicians reported that prior authorization had
contributed to a serious adverse event, including hospitalization,
permanent impairment or death.
And 74% said denials have increased over the past
five years.
Meanwhile, 60% expressed concern that augmented
intelligence could actually increase denial rates.
That last statistic deserves more attention.
Healthcare professionals are not automatically assuming AI
will save them.
Some are asking whether it could make the administrative
problem worse.
They are right to ask.
Here's the question every healthcare founder should
answer
Before saying:
“We use AI.”
Ask:
“What exactly are we making smarter?”
Is the system better at understanding clinical context?
Better at detecting missing information?
Better at predicting risk?
Better at identifying preventable errors?
Better at routing exceptions?
Better at learning from previous outcomes?
Or is it simply better at generating another alert?
Because physicians don't need more alerts.
They need fewer problems.
The father donated cells.
Healthcare organizations need another kind of donor.
Information donors.
The physician supplies clinical information.
The front desk supplies patient and insurance information.
The authorization team supplies payer information.
The coder translates clinical information into standardized
terminology.
The biller supplies claim information.
The payer supplies adjudication information.
Each contributes a piece.
But if those pieces cannot travel cleanly through the
workflow, someone has to manually reconstruct the picture.
That person becomes the human middleware.
And healthcare has thousands of them.
The hidden workforce inside your practice
There is an entire workforce whose job description rarely
appears on an organizational chart.
They are the people who:
- copy
information from one system into another;
- search
payer websites;
- reconcile
spreadsheets;
- call
insurance companies;
- resend
documents;
- find
missing notes;
- chase
signatures;
- check
claim status;
- explain
denials;
- ask
physicians for clarification;
- re-enter
data;
- reconcile
payments;
- remember
obscure payer rules.
They are not necessarily inefficient.
They are often compensating for inefficient
infrastructure.
That distinction matters.
Because if you tell these people to “work harder,” you may
increase throughput temporarily.
You have not fixed the system.
The dangerous employee: the person who knows every
workaround
Here's a counterintuitive problem.
Your best billing employee may be masking your worst
operational problem.
She knows everything.
She knows which payer portal works.
Which representative answers.
Which code gets rejected.
Which physician tends to forget a modifier.
Which claims need attachments.
Which spreadsheet to open.
Which phone number to call.
Which workaround nobody documented.
She is a hero.
And that is exactly why the organization is vulnerable.
Her knowledge lives inside her head.
When she leaves, the practice discovers that it didn't have
a system.
It had a person.
Tribal knowledge is not infrastructure
A resilient practice turns tribal knowledge into institutional
knowledge.
Institutional knowledge becomes:
rules.
workflows.
documentation.
decision support.
automation.
audit trails.
feedback loops.
The goal isn't to eliminate experienced employees.
It is to make their expertise scalable.
If the only way your organization knows how to prevent a
denial is because one employee remembers it, you haven't really prevented the
denial.
You've just remembered it.
What the rare-disease story teaches us about revenue
cycle
Let's return to the child.
Doctors did not simply look at one symptom.
They connected a pattern.
Severe infections.
Poor weight gain.
Skin manifestations.
Family history.
Genetic findings.
The diagnosis emerged from relationships between pieces
of information.
That is the key.
Information becomes more valuable when it is connected to
context.
The same is true in revenue cycle.
One denied claim may tell you very little.
But 27 similar denials from the same payer, for the same
service, with the same documentation gap?
That is no longer noise.
That is a pattern.
And a pattern is intelligence.
The real opportunity is upstream
Most revenue-cycle technology focuses heavily on what
happens after the claim is generated.
That makes sense.
The claim is measurable.
The denial is measurable.
The A/R is measurable.
The payment is measurable.
But by then, the organization may already be paying for the
mistake.
The more interesting opportunity is upstream.
Before submission.
Before denial.
Sometimes before the encounter.
Can the system recognize risk before the problem becomes
a claim?
That is the question I would build around.
Think about the revenue cycle as a pipeline
Traditional model
Encounter → Claim → Denial → Investigation → Correction →
Appeal → Payment
The organization is constantly looking backward.
Now consider:
Preventive model
Encounter → Validation → Risk detection → Correction →
Claim → Payment
The organization is looking forward.
And ultimately:
Learning model
Clinical context → Administrative intelligence →
Preventive action → Clean claim → Payment → Learning
That last word matters.
Learning.
The outcome of yesterday's claim should improve tomorrow's
workflow.
Otherwise the organization keeps rediscovering the same
problem.
A denial should teach the system something
Suppose a payer repeatedly rejects a particular service
because a required element is missing.
Traditional response:
Work the denial.
Better response:
Find the root cause.
Even better:
Detect the missing element before submission.
Best:
Change the workflow so the missing element becomes harder
to omit.
That's the difference between:
denial management
and
denial prevention.
This is where I challenge “best practices”
Healthcare loves best practices.
But sometimes “best practice” means:
“This is the way we've always done it, except now we have
a policy document explaining it.”
A process isn't good because it is standardized.
It is good because it produces a reliable outcome with
minimal unnecessary friction.
So I would challenge every physician-owner to question the
following:
Why do we need this step?
Who benefits from it?
What information does it create?
What decision does it enable?
Could it happen earlier?
Could the system do it?
Could it disappear entirely?
That last question is rarely asked.
It should be.
The “zero-touch” fantasy
I'm also skeptical of another industry promise:
100% automated billing.
Healthcare is too messy for that claim to be credible.
There will always be exceptions.
Payer changes.
Clinical ambiguity.
Unusual documentation.
Contractual complexity.
Patient-specific circumstances.
Human judgment.
The goal shouldn't be zero humans.
It should be zero unnecessary human touches.
That is a much more useful goal.
Humans should handle exceptions
Imagine a system where routine claims move through
automatically.
But unusual cases get elevated.
That means the human is no longer searching for the problem.
The system brings the problem to the human.
That's a profound workflow change.
Instead of:
human → search → discover → investigate
you get:
system → detect → prioritize → human reviews
The human becomes the decision-maker.
Not the detective.
This is what AI should actually do
If AI is going to be useful in revenue cycle, I believe its
most important role isn't writing clever messages.
It is connecting signals.
For example:
A payer.
A service.
A diagnosis.
A documentation pattern.
A historical denial.
A previous authorization.
A contract rule.
A patient encounter.
A claim.
A payment.
A denial.
Individually, these are data points.
Together, they can become a prediction.
This claim looks risky.
That's useful.
But then comes the critical next step:
Why?
An AI system that says “high risk” without an explanation
creates another black box.
A useful system says:
This is high risk because similar claims from this payer
and service combination were denied for this specific reason, and the current
encounter appears to be missing the relevant information.
Now the human can act.
Explainability matters more than hype
Physician-owners should ask vendors:
Why did the system flag this?
What data did it use?
Can I audit the decision?
Can I correct the system?
What happens when it is wrong?
Who remains accountable?
Can the recommendation be traced back to source
information?
These are better questions than:
How many AI models do you use?
Ethical boundary: don't automate fiction
There is a bright ethical line.
Technology should help practices capture what is true.
It should not manufacture clinical justification.
It should not encourage unsupported coding.
It should not manipulate documentation.
It should not turn an ambiguous clinical record into an
artificially confident claim simply because reimbursement is at stake.
Automation should improve accuracy.
Not manufacture certainty.
That distinction matters enormously.
Legal and compliance implications
Physician-owners should also remember that automation does
not transfer responsibility.
Depending on the workflow, practices must consider:
HIPAA and privacy
business associate agreements
coding compliance
payer contracts
Medicare and Medicaid rules
documentation requirements
False Claims Act exposure
auditability
data security
vendor oversight
human review
A technology vendor can help a practice execute a workflow.
It does not automatically make the workflow compliant.
That remains a management responsibility.
The biggest mistake: buying software before understanding
the problem
I see this constantly.
A practice experiences denials.
It buys denial software.
The practice has authorization problems.
It buys authorization software.
It has A/R problems.
It buys another dashboard.
Soon the organization has seven applications.
And twelve passwords.
And three dashboards.
And a spreadsheet.
And someone still calls the payer.
That isn't transformation.
That's software accumulation.
Start with the workflow
Before buying anything, take one service line.
Choose perhaps:
orthopedics
neurology
cardiology
gastroenterology
behavioral health
or another high-volume area.
Then follow one encounter from:
appointment → registration → eligibility → authorization
→ visit → documentation → coding → claim → adjudication → payment.
Write down every handoff.
Every manual step.
Every portal.
Every spreadsheet.
Every phone call.
Every correction.
Every delay.
You will probably discover something surprising.
The biggest problem may not be where you thought it was.
The 30-day physician-owner experiment
Week 1: Map
Document one complete patient-to-payment workflow.
Don't optimize it.
Just observe it.
Week 2: Measure
Track:
claim touches
denials
preventable denials
manual hours
authorization volume
A/R aging
days to payment
Week 3: Diagnose
Find the largest combination of:
frequency + preventability + labor + financial impact.
Week 4: Redesign
Ask:
Can we eliminate the step?
If not:
Can we move it upstream?
If not:
Can we standardize it?
If not:
Can we automate it?
If not:
Can we make it easier for a human to perform?
That's the order I would use.
Not:
AI first.
Metrics that actually matter
Physician-owners don't need another 100-metric dashboard.
Start with a small operational scorecard.
1. Clean claim rate
How many claims are right the first time?
2. Preventable denial rate
How many denials could reasonably have been prevented?
3. Claim-touch rate
How many human interventions does a claim require?
4. Days in A/R
How long is revenue outstanding?
5. A/R over 90 days
How much money is aging?
6. Denial turnaround time
How quickly does someone act?
7. Appeal recovery rate
How much denied revenue is recovered?
8. Manual administrative hours
How much staff capacity is being consumed?
9. Dollars at risk
How much revenue is currently exposed?
10. Recurrence rate
How often does the same problem happen again?
That final metric may be the most revealing.
Because if the same denial keeps returning, the organization
is not learning.
A metric I want to see more often
Administrative friction per encounter
Take:
total unnecessary administrative actions ÷ total
encounters.
It isn't a perfect metric.
But it forces an important question:
How much work does our infrastructure demand for every
patient we serve?
Two practices can see the same number of patients.
Generate similar revenue.
Have similar reimbursement.
Yet one can require dramatically more administrative effort.
That practice has a structural disadvantage.
What should physicians stop doing?
Physicians should stop becoming the final escalation
point for routine administrative ambiguity.
If the billing team repeatedly asks:
“Can you clarify this?”
“Can you add this?”
“Did you mean this diagnosis?”
“Why was this service performed?”
“Can you sign this?”
Sometimes that's appropriate.
But if the same question occurs repeatedly, it is a workflow
problem.
The physician should not be the human API between the
clinical and billing systems.
What should billing teams stop doing?
They should stop spending valuable time repeatedly fixing
the same root cause.
If the same payer denial appears 50 times, working claim 51
faster isn't the answer.
The question is:
What changes before claim 52?
What should technology companies stop doing?
Stop selling more screens.
Physicians don't need another screen.
They need fewer reasons to open one.
Stop selling “AI-powered” as the product.
Explain the outcome.
Stop promising complete automation.
Explain where human judgment remains.
And stop assuming that large organizations are the only
customers worth serving.
Small practices have some of the clearest operational
problems because there are fewer layers between the workflow and the
physician-owner.
Why small and medium-sized practices matter
A large health system can absorb inefficiency across
departments.
A smaller physician-owned clinic often cannot.
If one employee spends two hours each day on avoidable
administrative work, that's not just a productivity issue.
It may affect:
patient access
staff morale
physician workload
cash flow
hiring
growth
practice autonomy
This is why I believe the future of healthcare technology
should not only focus on large enterprise systems.
The physician-owned practice deserves intelligent
infrastructure too.
What OnnX is trying to build
This is the problem that led me to build OnnX.
Not another dashboard.
Not another outsourced billing layer.
Not another system designed primarily around the assumption
that people will manually clean up problems afterward.
The goal is to create an AI-powered medical billing
operating layer for small and medium-sized physician-owned clinics.
The thesis is simple:
Revenue-cycle performance should become more predictable
when the system understands the encounter earlier.
That means looking for opportunities to:
capture better information
identify risk earlier
reduce unnecessary handoffs
prevent recurring errors
prioritize exceptions
surface operational patterns
improve visibility
The technology is not the point.
The workflow is.
“Eliminate middlemen” needs a qualification
I often describe the opportunity as eliminating unnecessary
middlemen.
But let's be precise.
Not every intermediary is waste.
Some provide real expertise.
The problem is the intermediary whose primary purpose is
compensating for disconnected infrastructure.
If information has to pass through five people because two
systems cannot communicate, perhaps the fifth person isn't creating value.
They're creating a workaround.
The future shouldn't be:
more intermediaries with better software.
It should be:
fewer unnecessary handoffs because the systems themselves
are more capable.
The recent regulatory direction points the same way
CMS has continued pushing toward more electronic
health-information exchange and administrative simplification.
Its interoperability and prior-authorization framework is
designed to improve health information exchange and reduce friction around
access to information.
CMS has also been advancing electronic standards around
health-care attachments, recognizing that supporting clinical documentation
remains an important part of administrative transactions.
The direction is clear.
Healthcare is moving toward:
more electronic exchange
more standards
more structured information
more automation
But that creates a new challenge.
If we simply digitize fragmented processes, we will end up
with digital fragmentation.
The next step must be intelligent orchestration.
The future isn't “AI billing”
I'm skeptical of that phrase.
It sounds like the future is a robot replacing the billing
department.
I don't think that is the interesting future.
The interesting future is:
clinical information becoming more useful to
administrative workflows.
Administrative outcomes becoming feedback for clinical
and operational workflows.
Systems identifying preventable problems before
submission.
Humans handling exceptions rather than routine searches.
Physicians seeing meaningful signals rather than
administrative noise.
That is a more mature vision.
Three experts. Three lessons.
Dr. Mansi Sachdev: patterns save time — and sometimes
lives
The Abu Dhabi transplant story demonstrates the power of accurate
diagnosis and multidisciplinary coordination.
The lesson for operations is simple:
Don't look at isolated events.
Look for relationships.
A claim is not just a claim.
It belongs to a patient, service, payer, clinician,
documentation pattern and historical outcome.
Connect the dots.
Dr. Maysoon Al Karam: expertise matters when the system
can coordinate it
Dr. Maysoon Al Karam, Chief Medical Officer at Yas Clinic,
emphasized the combination of specialized expertise and advanced treatment
capabilities in the successful case.
That is important for physician-owned practices.
Technology should not replace expertise.
It should make expertise easier to deploy.
The best operational system does not make your smartest
people less important.
It makes their knowledge available to more of the
organization.
Willie Underwood III, MD, MSc, MPH: interoperability
requires meaning
The AMA's Willie Underwood has argued that modernizing prior
authorization requires more than electronic bridges. It requires interoperable
terminology capable of supporting real clinical and administrative workflows.
That is a critical distinction.
An API can move data.
It cannot automatically guarantee that two workflows
understand that data the same way.
Meaning is the missing layer.
The myth: “More data equals better decisions”
Not necessarily.
More data can mean more noise.
A physician doesn't need every available data point.
A biller doesn't need every clinical detail.
A payer doesn't need the entire patient chart for every
transaction.
The objective is:
the right information
in the right context
at the right time
for the right decision.
That is intelligence.
The myth: “More automation equals fewer employees”
Not necessarily.
Good automation can make employees more valuable.
Instead of spending four hours on repetitive work, a billing
professional can spend that time analyzing recurring payer behavior.
Instead of searching for missing information, they can
manage exceptions.
Instead of correcting the same errors, they can improve the
workflow.
The question isn't:
How many people can we eliminate?
It is:
How much unnecessary work can we eliminate?
The myth: “Denials are just a billing problem”
Wrong.
A denial can originate in:
registration
eligibility
authorization
documentation
coding
payer policy
contracting
timely filing
clinical workflow
That means denial management is often cross-functional.
If the billing department owns the entire problem, it may be
asked to fix problems it did not create.
The myth: “Physicians don't care about billing”
I don't believe that.
Physicians care deeply about billing.
They just don't want to spend their lives doing billing.
There is a difference.
A physician-owner cares when:
Revenue disappears.
Staff burn out.
A/R grows.
Hiring becomes difficult.
The practice loses autonomy.
A payer repeatedly changes rules.
The physician's inbox fills with administrative questions.
So the solution isn't to turn physicians into billing
experts.
It is to give them visibility without additional
administrative burden.
The myth: “The best practice is the most efficient
practice”
Not always.
A practice can be extremely efficient at doing the wrong
thing.
You can process claims very quickly.
If the claims are wrong, you've simply accelerated the
problem.
You can answer authorization requests rapidly.
If unnecessary authorizations are being generated, you've
optimized the wrong process.
Efficiency without effectiveness is just faster waste.
That is one of the most important distinctions in healthcare
operations.
A practical “information autopsy”
Take one recurring denial.
Then work backward.
Question 1
What exactly happened?
Question 2
Why did it happen?
Question 3
When could the problem first have been detected?
Question 4
Who had the information at that moment?
Question 5
Why didn't the next person receive it automatically?
Question 6
What manual workaround compensated for the gap?
Question 7
Can the gap be eliminated?
This exercise often produces more insight than another
vendor demonstration.
The “touch count” experiment
Take 100 claims.
Count every human interaction.
Don't just count biller touches.
Count:
front desk
clinical staff
physician
coder
authorization team
biller
practice manager
payer representative
Then ask:
How many touches were necessary?
And:
How many existed only because another step failed?
That's your avoidable touch rate.
Now multiply it by annual volume.
You may discover an enormous hidden labor cost.
The “same denial twice” rule
Here is a simple operational rule I would introduce:
If the same preventable denial occurs twice, it becomes a
process problem rather than an employee problem.
The first occurrence might be an error.
The second is a signal.
The third is a system failure.
At that point, telling staff to “be more careful” is not
leadership.
It is avoidance.
Build feedback loops
Every denial should have a destination.
Not just:
resolved.
But:
what did we learn?
Create categories.
Track recurrence.
Assign ownership.
Measure whether interventions work.
Then close the loop.
The goal is not a larger denial database.
It is a smaller future denial database.
Tools and resources physician-owners can use
You do not need sophisticated software to begin.
Start with:
EHR reporting
practice-management reports
clearinghouse reports
payer portals
denial reason codes
A/R aging reports
authorization logs
coding audits
workflow maps
simple spreadsheets
The technology comes later.
First determine what the data is telling you.
For standards and administrative simplification, physician
practices should also follow developments from CMS and the AMA,
particularly around electronic prior authorization, interoperability and
standardized transactions.
Future outlook: from transaction processing to
operational intelligence
I think the next phase of healthcare technology will be less
about adding applications and more about creating intelligence between
applications.
Imagine a practice where the system understands:
The encounter happened.
The documentation is incomplete.
This payer usually requires additional information.
A similar claim was denied last month.
The authorization is approaching expiration.
This service has a high-risk pattern.
The biller should review it.
The physician does not need to be interrupted unless a
genuine clinical question exists.
That is much closer to what an operating system should do.
The most important word is not AI
It is:
context.
AI without context is autocomplete.
Automation without context is workflow acceleration.
Data without context is noise.
But:
data + context + timing + action
can become intelligence.
That is the opportunity.
Why this matters beyond billing
A financially healthy practice is not the goal by itself.
Financial stability gives physicians options.
Options to:
Hire.
Expand access.
Invest in equipment.
Support staff.
Add services.
Spend more time with patients.
Remain independent.
Innovate.
A physician practice that constantly loses time and money to
administrative friction has fewer options.
That makes revenue-cycle infrastructure a strategic issue.
Not merely an accounting issue.
The patient's experience is the ultimate test
Patients don't care whether the problem originated in:
the EHR,
the payer,
the clearinghouse,
the billing department,
the authorization team,
or the coding workflow.
They experience one healthcare organization.
If their appointment is delayed because authorization was
missed, they experience the delay.
If their bill is wrong, they experience the confusion.
If staff are overwhelmed, they experience the rushed
interaction.
If physicians are buried in administrative work, patients
experience less physician attention.
This is why operational design ultimately matters to the
human experience of healthcare.
The boy's story brings us back to the beginning
A 13-month-old child had a devastating condition.
His family had already suffered an unimaginable loss.
The medical team had limited time.
The child needed the right diagnosis.
The right donor.
The right procedure.
The right expertise.
The right coordination.
His father became the donor.
The transplant succeeded.
His immune system recovered.
He began to heal.
There is something deeply human about that story.
A father gave his son cells that helped give him another
chance.
But there is also something operationally profound about it.
The outcome depended on connections.
Clinical information connected to diagnosis.
Diagnosis connected to treatment.
Treatment connected to donor selection.
Donor selection connected to the transplant.
The transplant connected to recovery.
No single component created the outcome.
The connections did.
That is the lesson I want physician-owners to take away
Your practice is also a network of connections.
Patient.
Physician.
Documentation.
Code.
Authorization.
Payer.
Claim.
Payment.
Denial.
Staff.
Technology.
If those connections are weak, the practice compensates with
labor.
If they are strong, the system becomes more resilient.
That is why I don't believe the future of medical billing is
simply:
more billers
or
more software
or
more AI.
The future is better information architecture.
The provocative conclusion
We have spent decades trying to make people work harder
inside broken workflows.
Then we called the result:
healthcare administration.
We should be more ambitious.
The question shouldn't be:
“How do we process this claim faster?”
It should be:
“Why did this claim require so much work in the first
place?”
The question shouldn't be:
“How do we recover this denial?”
It should be:
“What did the system know—or fail to know—before the
denial happened?”
And the question shouldn't be:
“Where can we add AI?”
It should be:
“Where can better intelligence remove friction without
removing judgment?”
That is a much harder question.
It is also a much more valuable one.
Final Thoughts
The 13-month-old boy in Abu Dhabi never saw a claim.
He never saw an A/R report.
He never dealt with prior authorization.
He never opened a payer portal.
He simply needed someone to understand what was happening to
him.
His physicians did.
His father stepped forward.
The medical team coordinated.
And the child got another chance.
That is what healthcare is supposed to do.
Connect knowledge to action.
For physician-owners, the same principle applies to the
business side of medicine.
Your practice does not need more administrative activity.
It needs better information flow.
It needs fewer unnecessary handoffs.
It needs earlier detection.
It needs systems that learn.
And it needs technology that serves the people doing the
work instead of creating another layer of work.
The best revenue cycle is not the one that cleans up the
most mistakes.
It is the one that makes fewer mistakes possible.
And the best healthcare technology is not the technology
that looks the smartest. It is the technology that makes the humans doing the
important work more effective.
Get Involved — Start the Conversation
I want to hear from physicians and clinic owners.
Here is the provocative question:
What is the most ridiculous administrative task your
practice has simply learned to tolerate?
Is it a payer portal?
A spreadsheet?
A fax?
A repetitive authorization request?
A denial that happens every month?
A report nobody reads?
A physician being pulled into a billing problem?
Or something else?
Leave a comment and tell me what it is.
Not what your vendor says the problem is.
Not what a consultant says.
What you actually experience.
If this perspective resonates with you, share this
article with another physician-owner or healthcare leader.
And if you believe physician-owned practices deserve better
infrastructure, join the conversation, raise your voice and help shape what
comes next.
Question the workflow. Challenge the assumptions. Build
something better.
Frequently Asked Questions
Is this story about billing?
No.
The child's story is fundamentally about rare disease,
diagnosis, family, transplantation and multidisciplinary medical care.
The billing connection is an operational analogy: both
clinical care and revenue-cycle performance depend on information reaching the
right people at the right time.
What happened to the child?
He had a rare inherited immunodeficiency caused by a homozygous
RAG1 mutation associated with Omenn syndrome. He underwent a haploidentical
bone marrow transplant using stem cells donated by his father and subsequently
achieved engraftment and improving immune function.
What were the child's parents' names?
The current public reports I found do not identify the
child or his parents by name. I have intentionally not invented names or
attributed names from unrelated cases to this family.
Who were the doctors publicly identified?
Dr. Mansi Sachdev, Consultant Pediatric Hematology,
Oncology and Bone Marrow Transplantation at ADSCC, was quoted about the case.
Dr. Maysoon Al Karam, Chief Medical Officer at Yas
Clinic, also commented publicly on the case.
What is the main business lesson?
Revenue-cycle problems should be detected upstream
whenever possible.
A denial is an outcome. The more valuable question is what
information was missing, misunderstood or disconnected before the claim was
submitted.
Does this mean physician practices should eliminate
billing staff?
No.
The goal is to eliminate unnecessary administrative work,
not professional expertise.
Humans should increasingly focus on exceptions, judgment,
analysis and process improvement.
Does AI solve medical billing?
Not by itself.
AI can identify patterns, prioritize work and support
decision-making. But AI applied to a poor workflow can simply accelerate a poor
workflow.
What should a practice measure first?
Start with:
clean claim rate
preventable denial rate
claim-touch rate
A/R aging
denial turnaround time
manual administrative hours
dollars at risk
and especially:
recurrence of the same problem.
What is the best first step?
Map one patient-to-payment workflow from scheduling
through payment.
Count the handoffs.
Count the manual touches.
Identify where information disappears.
Then decide what should be eliminated, moved upstream,
standardized or automated.
Myth Busters
Myth: “Billing starts after the visit.”
Reality: Revenue-cycle performance is influenced by
scheduling, registration, eligibility, authorization, documentation and coding
before a claim is submitted.
Myth: “A denial is a billing problem.”
Reality: A denial may originate much earlier in the
workflow.
Myth: “AI automatically creates efficiency.”
Reality: AI is only as useful as the workflow, data
and decision context surrounding it.
Myth: “Electronic means interoperable.”
Reality: Systems can exchange information
electronically while still failing to exchange meaning effectively.
Myth: “The best employee can compensate for a bad
process.”
Reality: A great employee can temporarily mask a
structural problem. A resilient organization converts that person's knowledge
into a repeatable system.
Myth: “The answer is more automation.”
Reality: Sometimes the best automation is eliminating
the step entirely.
Practical Checklist for Physician-Owners
Before purchasing another healthcare technology product,
ask:
1. What exact problem are we solving?
2. Where does the problem first appear?
3. Where does it actually originate?
4. How many human touches does it require?
5. How much does the problem cost in labor?
6. How much revenue is exposed?
7. How often does the problem repeat?
8. Could we prevent it upstream?
9. Could we eliminate the step?
10. If we automate it, what happens when the system is
wrong?
11. Can a human audit the decision?
12. Will this reduce work—or merely move work somewhere
else?
That last question may be the most important.
Three References Worth Reading
1. The human story — Gulf News
Ali Al Hammadi's report describes the 13-month-old child's
rare immune disorder, the family's history, the father's donation and the
successful transplant at Yas Clinic in collaboration with ADSCC.
2. The physician burden — American Medical Association
The AMA's 2026 survey documents the administrative burden of
prior authorization, including approximately 40 requests per physician each
week, about 13 hours of weekly physician/staff time and significant concerns
about delays and denials.
3. The interoperability problem — AMA
The AMA's SNOMED CT-to-CPT mapping initiative directly
addresses the disconnect between clinical terminology and administrative coding
in prior authorization.
Continue the Conversation
Healthcare innovation becomes meaningful when physicians,
operators, founders and patients can talk honestly about what is
working—and what isn't.
I share practical perspectives on healthcare operations,
medical billing, AI, physician entrepreneurship, healthcare technology and the
future of medical practice.
Visit the personal website:
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Knowledge drives progress—but only when it changes what
we do. Keep learning. Keep questioning. Keep building.
Free Resource
Check the Featured section of my LinkedIn profile for
a free resource for physicians, clinic owners and healthcare professionals.
No signup required.
If this article gave you a useful idea, take the next step: explore
the resource, test the idea in your practice and share it with someone who
could benefit.
If this perspective resonates, consider reposting this
article so more physicians and clinic owners can rethink how administrative
friction affects the practice of medicine.
About the Author
Dr. Daniel Cham is a physician, healthcare consultant
and entrepreneur focused on the intersection of medical practice, healthcare
technology, healthcare management, operations and medical billing.
He is the founder of OnnX, an AI-powered medical
billing SaaS platform focused on helping small and medium-sized physician-owned
clinics reduce administrative friction, improve revenue-cycle visibility and
build more intelligent operational workflows.
His work explores a practical question:
How can technology make healthcare easier for the people
actually delivering it?
Dr. Cham combines a physician's perspective with an interest
in healthcare technology, operational design and revenue-cycle transformation.
His focus is not technology for technology's sake.
It is better systems, better information and better
outcomes for the people working inside healthcare.
Connect with Dr. Cham on LinkedIn to
learn more.
Disclaimer
This article is intended for general educational and
informational purposes. It is not medical, legal, coding, compliance,
reimbursement or financial advice.
Healthcare rules, payer policies, contracts and
regulatory requirements can change and may vary by circumstance. Readers should
consult appropriately qualified professionals before making decisions involving
patient care, documentation, coding, reimbursement, compliance or healthcare
operations.
Final Provocation
The healthcare industry has become extraordinarily
sophisticated at treating disease.
But we remain surprisingly primitive at moving information
through the systems that support that care.
That contradiction is an opportunity.
The 13-month-old boy in Abu Dhabi needed a team that could connect
the dots.
Physician-owned practices need the same discipline.
Not because a denied claim is equivalent to a
life-threatening disease.
It isn't.
But because the underlying principle is the same:
Information only creates value when it reaches the right
person in time to change what happens next.
That is the future I believe healthcare technology should
pursue.
Not more noise.
Not more dashboards.
Not more administrative layers.
Better signals. Earlier action. Fewer unnecessary
touches. More human attention where it actually matters.
And perhaps that is the most important lesson hidden inside
this remarkable story:
The best healthcare systems don't simply have more
information. They know what to do with it.
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#PhysicianEntrepreneur #PriorAuthorization #HealthcareTechnology #DenialPrevention
#RCM #PatientCare #HealthcareLeadership #ClinicalOperations #AIinHealthcare
