A mother gave her teenage son a kidney in 1978. Nearly five decades later, it still works. The bigger lesson for physicians may be about something healthcare routinely loses: continuity.
“The pathway can be complete. The clinical assessment may
not be.” — Lourdes
G. Bahamonde, DO, MS
The kidney lasted nearly 50 years. Why does the
information behind a single healthcare encounter sometimes disappear before the
claim is even submitted?
Dr. Bahamonde, a solo-practice gastroenterologist in Los
Angeles, wrote this week about the tension between standardized healthcare
pathways and individualized clinical judgment. Her observation is bigger than
gastroenterology.
It describes modern healthcare surprisingly well.
A pathway can be complete.
Every box can be checked.
Every field can be populated.
Every task can be marked “done.”
And the patient can still fall through the cracks.
That is where this story begins.
The kidney that refuses to retire
In March 1978, Elizabeth “Betty” Vetuskey gave one of
her kidneys to her 16-year-old son, Raymond “Ray” Vetuskey, at Strong
Memorial Hospital in Rochester, New York.
Ray was suffering from kidney failure.
A virus had severely damaged his kidneys.
Dialysis was taking a toll.
He was losing weight.
He was losing strength.
His kidney function was worsening.
A transplant became his only chance.
Then his mother stepped forward.
Betty was 52.
She was a near-perfect match.
On March 2, 1978, mother and son went into surgery.
They were on separate gurneys.
They held hands.
Betty cried.
Ray tried to reassure her.
He had a concert to attend.
He wasn't planning on missing it.
Three weeks later, he didn't.
He went to see Genesis at the Rochester Community War
Memorial.
He kept the ticket stubs.
That tiny detail may be the most important part of the
entire story.
Because medicine had just done something extraordinary.
But Ray didn't spend the next 48 years thinking about
medicine.
He went back to living.
He worked.
He grew older.
He had birthdays.
He had ordinary days.
He became a retired sheet-metal fabricator.
His mother continued to be part of his life.
Then Betty died in 2008.
But something she gave her son kept going.
Her kidney.
Nearly five decades later, it is still functioning.
In September 2026, the University of Rochester Medicine
Transplant Institute reported that the kidney has reached approximately 100
years of biological life and that Ray is the program's longest-surviving
kidney transplant recipient. He continues to receive annual follow-up.
Ray put the emotional truth more simply:
“Every day I think of her... She's right by my side, all
the time.”
That is the human story.
But there is another story hiding inside it.
And this one has everything to do with how we run medical
practices.
The real miracle may be continuity
When we hear “100-year-old kidney,” we naturally think about
transplantation.
The surgery.
The organ.
The immunosuppression.
The medical expertise.
The technology.
But there is another word that deserves attention:
continuity.
The transplant happened once.
The care did not.
Ray has been monitored for decades.
His kidney has been followed.
His clinical information has continued to matter.
The relationship between patient and healthcare system
didn't end when the operating room doors closed.
The procedure was the beginning.
Not the outcome.
The outcome was everything that happened afterward.
That distinction is incredibly important for modern
healthcare.
Because we have become very good at completing tasks.
We are less consistently good at connecting them.
A referral is completed.
An authorization is completed.
A visit is completed.
A note is completed.
A claim is submitted.
A payment is posted.
A denial is processed.
The boxes are checked.
The workflow is “complete.”
But is the patient's story still connected?
That is a different question.
And it may be one of the most important questions healthcare
leaders should be asking.
Here is the uncomfortable part
A claim denial may not actually be a billing problem.
It may be a continuity problem.
The denial is simply where the continuity failure becomes
visible.
Think about what happens in a typical practice.
A patient calls.
The front desk schedules the appointment.
Insurance information is entered.
The patient arrives.
The nurse gathers information.
The physician evaluates the patient.
The physician documents.
Someone codes.
Someone requests authorization.
Someone submits a claim.
The payer reviews it.
The claim is denied.
Then everyone becomes interested.
Suddenly there is urgency.
Someone opens the chart.
Someone searches the note.
Someone checks the payer portal.
Someone sends a message to the physician.
Someone asks:
“Can you add more documentation?”
The physician thinks:
“I already documented that.”
The biller thinks:
“I can't find it.”
The authorization specialist thinks:
“The payer needs something else.”
The patient thinks:
“Why is this taking so long?”
Everyone is working.
Nobody is necessarily failing.
And yet the system is failing to move information cleanly.
That is the distinction.
Activity is not the same as progress.
Healthcare has a strange addiction to the downstream
problem
We tend to manage problems where they become visible.
The denial happens in billing.
So we improve billing.
The authorization gets stuck.
So we hire more authorization staff.
The inbox grows.
So we buy an inbox tool.
The claim needs correction.
So we create a correction queue.
The staff is overwhelmed.
So we hire another person.
The cycle continues.
There is nothing inherently wrong with any of those
interventions.
Sometimes they are necessary.
But there is a contrarian question worth asking:
What if we are repeatedly adding people and software to
compensate for information problems created earlier in the workflow?
That changes the diagnosis.
And when the diagnosis changes, the solution changes.
Most revenue-cycle problems don't begin in the revenue
cycle
Consider prior authorization.
A payer requires certain clinical information.
The practice submits an authorization request.
The payer asks for more documentation.
The practice searches the chart.
The physician gets interrupted.
A staff member copies information from one system into
another.
The request is resubmitted.
Maybe it is approved.
Maybe it isn't.
Where did the problem begin?
Was it the payer?
Possibly.
Was it the authorization team?
Possibly.
But perhaps the real issue started when the patient was
scheduled and the practice did not capture a critical piece of information that
would later become necessary.
Or perhaps the clinical rationale existed in the physician's
note but wasn't structured in a way that the next workflow could easily use.
Or perhaps the information existed in three places but
nowhere was clearly designated as the source of truth.
The payer sees the final request.
The payer doesn't see the administrative archaeology that
happened before it.
The denial becomes the headline.
The root cause remains invisible.
This is why I keep coming back to “upstream”
My thesis as a physician and founder of OnnX is
straightforward:
Most of the problem starts upstream.
Not at the claim.
Not at the denial.
Not at the appeal.
Earlier.
At the moment information is captured.
At the handoff.
At the transition between front desk and clinical staff.
At the transition between clinical documentation and
authorization.
At the transition between authorization and billing.
At the transition between billing and payer requirements.
That is where small inconsistencies become expensive
problems.
Healthcare tends to treat those inconsistencies as separate
administrative issues.
The practice experiences them as one thing.
Rework.
Rework is the silent tax on independent practices
Nobody puts “rework” on the practice's income statement as a
line item.
But it is there.
It is hiding in:
Physician inbox time.
Nurse messages.
Biller corrections.
Authorization resubmissions.
Payer phone calls.
Patient callbacks.
Chart reviews.
Faxing.
Scanning.
Uploading.
Downloading.
Copying.
Pasting.
Searching.
Waiting.
Following up.
And then following up on the follow-up.
It is the administrative version of compound interest.
One tiny inefficiency isn't catastrophic.
Multiply it by hundreds of encounters.
Then thousands.
Now it becomes payroll.
Now it becomes burnout.
Now it becomes delayed cash.
Now it becomes lost physician attention.
Now it becomes a patient experience problem.
The 1.2-FTE nobody hired
This is why I think about what I call the 1.2-FTE problem.
A small practice may not think it needs another employee.
But the work exists.
Someone has to find the missing information.
Someone has to check the authorization.
Someone has to correct the claim.
Someone has to answer the payer.
Someone has to ask the physician.
Someone has to document the response.
Someone has to resubmit.
No one person owns the entire problem.
So the work gets distributed across the organization.
The MA does 15 minutes.
The nurse does 20.
The physician does 10.
The biller does 45.
The practice manager does 30.
The front desk does 15.
Congratulations.
You just created an employee.
You simply didn't give them an employee ID.
This is why headcount alone doesn't tell you whether a
practice is operationally efficient.
You need to understand how much labor is being consumed
by correction loops.
The best healthcare workflow may be the one nobody
notices
This is where healthcare technology often gets interesting.
We love visible technology.
Dashboards.
Alerts.
AI assistants.
Analytics.
Portals.
Chatbots.
Predictive models.
Automation.
But the best workflow may be the one that disappears.
A physician shouldn't have to admire the authorization
workflow.
The physician should simply know that the required
information was captured.
A biller shouldn't need an exciting dashboard.
The biller should have a clean claim.
A patient shouldn't need to understand the revenue cycle.
The patient should receive care without becoming an unpaid
project manager.
This is a provocative idea:
The best healthcare technology may make itself less
visible, not more visible.
Three expert perspectives reinforce the same problem
1. Lourdes G. Bahamonde, DO, MS: completion is not the
same as clinical judgment
Dr. Bahamonde's September 30 article in The DO is
striking because she describes a problem familiar to many physicians: a
standardized pathway can contain all the expected steps while still failing to
preserve individualized clinical judgment.
Her line deserves to be remembered:
“The pathway can be complete. The clinical assessment may
not be.”
That principle applies to revenue-cycle workflows too.
A claim can be complete.
The information behind the claim may not be.
An authorization request can be complete.
The clinical story may not be.
A checklist can be complete.
The patient's needs may not be.
Completion is not continuity.
That distinction is central to this article.
2. John Whyte, MD, MPH: medicine is more than a list of
tasks
Earlier this month, John Whyte, MD, MPH, CEO of the
American Medical Association, challenged the idea that medicine can be reduced
to individual tasks that can simply be automated.
His argument is important for healthcare technology:
“Medicine has never simply been the completion of tasks.”
That is exactly the warning healthcare technology needs.
If a system automates a task but creates more fragmentation
around the task, have we really improved healthcare?
If AI writes the note but nobody knows what information the
authorization team needs, what changed?
If coding becomes faster but the clinical documentation is
poorly structured, did we solve the problem?
If claims are submitted faster but more of them require
correction, is speed actually the metric we should celebrate?
Automation is useful.
But automation without workflow intelligence can simply
create faster rework.
3. Adam P. Sawatsky, MD, MS: what happens when efficiency
changes the profession?
A September 29, 2026 JAMA Perspective by Adam P.
Sawatsky, MD, MS, and Andrea N. Leep Hunderfund, MD, MHPE, examines tension
between physicians' professional values and modern pressures involving market,
managerial and platform-driven healthcare.
The article is particularly relevant to clinic owners
because it raises a difficult question:
What happens when efficiency becomes the dominant
organizing principle?
Efficiency matters.
A practice cannot survive without it.
But healthcare is not manufacturing.
A patient is not a widget.
A physician is not merely a production unit.
A clinical encounter is not simply a transaction.
When efficiency becomes disconnected from judgment,
relationships and professional purpose, something important can be lost.
That is why the goal shouldn't be:
“How do we make everyone work faster?”
It should be:
“How do we remove work that never needed to exist?”
Those are very different strategies.
The statistic that should make clinic owners
uncomfortable
The University of Rochester Medicine report says the average
survival after living-donor kidney transplantation is approximately 15 to 20
years.
Ray's transplanted kidney has functioned for 48 years.
That doesn't mean every kidney transplant should last 48
years.
It doesn't.
Ray's age at transplantation, familial match and long-term
care all contributed to this extraordinary outcome, according to University of
Rochester Medicine.
But the broader lesson is powerful.
Long-term outcomes are built from multiple connected
factors.
There is no single magic event.
The surgery mattered.
The donor mattered.
The match mattered.
The medications mattered.
The monitoring mattered.
The follow-up mattered.
The patient mattered.
The chain mattered.
Healthcare operations work the same way.
Your claim is a chain
Think about a claim as a chain.
Eligibility.
Scheduling.
Referral.
Authorization.
Clinical encounter.
Documentation.
Coding.
Claim creation.
Submission.
Payer adjudication.
Payment.
Denial.
Appeal.
Every link depends on information from somewhere else.
Break one link and someone downstream gets the bill.
That is why I don't think of medical billing as a standalone
department.
I think of it as the final expression of everything that
happened before it.
The claim is the receipt.
It is not the entire transaction.
The contrarian question: are we measuring the wrong
thing?
Most practices know their:
A/R.
Collection rate.
Denial rate.
Days in A/R.
Charges.
Payments.
Write-offs.
Those numbers matter.
But what about:
How many times did this claim have to be touched?
How many people had to intervene?
How many times did someone search for missing information?
How many times did the physician get interrupted?
How many times did a payer request information the practice
already had?
How many times did the patient have to call?
Those are friction metrics.
And friction is often where hidden cost lives.
A better way to study denials
Don't start with the denial.
Start with the patient.
Pick 20 recent denials.
For each one, trace the journey backward.
Ask:
Where was the information first created?
Who created it?
Where did it go next?
Who changed it?
What was missing?
When could the missing information have been identified?
Who could have fixed it before submission?
This changes the conversation.
You stop asking:
“Why did the payer deny it?”
And start asking:
“Why did our workflow allow a predictable problem to
reach the payer?”
That is a much more interesting question.
Treat the denial like a crime scene
Here's a little humor for a very unfun topic.
If your practice has recurring denials, don't immediately
blame the biller.
Treat the claim like a crime scene.
Work backward.
Who touched it?
When?
What changed?
Where did the evidence disappear?
Which system had the missing information?
Who knew something was missing?
Who assumed somebody else had it?
And perhaps the most important question:
Why did everyone discover the problem at the most
expensive possible moment?
The answer is often the real process problem.
Myth Buster #1: “The EHR has everything”
Maybe.
That doesn't mean the workflow can use everything.
An EHR is excellent at storing information.
Storage is not the same as orchestration.
A chart can contain:
The diagnosis.
The clinical rationale.
The procedure.
The medical history.
The previous treatment.
The imaging.
The referral.
The insurance information.
And yet the next person can still ask:
“Where is it?”
That is not necessarily an information shortage.
It may be an information accessibility problem.
Myth Buster #2: “More documentation means better
documentation”
No.
More words are not automatically better medicine.
More words are not automatically better billing.
More words are not automatically better compliance.
The objective should be accurate, clinically meaningful,
appropriately structured documentation.
The question isn't:
“How much can we document?”
It is:
“What information needs to be captured so the next
legitimate step can happen correctly?”
That's a much better question.
Myth Buster #3: “AI will solve the revenue cycle”
AI can help.
But AI is not a substitute for process design.
If the underlying workflow is chaotic, AI may simply produce
a more sophisticated version of chaos.
Garbage in.
Garbage out.
Now with a beautiful user interface.
That isn't transformation.
The better question is:
Where can AI reduce human rework without replacing human
accountability?
That is where the opportunity gets interesting.
What AI should do in the practice
AI can be useful at several points.
It can identify missing information.
It can extract structured data from clinical documentation.
It can compare requirements against available information.
It can summarize records.
It can identify potential inconsistencies.
It can prioritize work.
It can route exceptions.
It can reduce repetitive administrative work.
But there should be a boundary.
AI should not invent clinical facts.
It should not manufacture medical necessity.
It should not fabricate documentation.
It should not turn uncertainty into false certainty.
And it should not become an excuse to remove humans from
decisions that require judgment.
The best model is often:
AI detects.
Humans decide.
The system remembers.
That last part matters
“The system remembers.”
Think about Ray's kidney.
The human body carried the biological memory of Betty's gift
for decades.
Healthcare systems are not that elegant.
We repeatedly ask them to remember.
Sometimes the EHR remembers.
Sometimes the payer portal remembers.
Sometimes the spreadsheet remembers.
Sometimes the biller remembers.
Sometimes the physician remembers.
Sometimes nobody remembers.
And then the patient gets asked to explain it again.
That is not a technology problem alone.
It is a system-design problem.
The upstream framework
If you own a clinic, try this five-part framework.
1. Capture
What information is created?
Who creates it?
When?
Where?
2. Structure
Is the information captured consistently enough to be
reused?
Or does every person interpret it differently?
3. Connect
Where does that information need to go next?
Authorization?
Coding?
Billing?
Referral?
Patient communication?
4. Validate
Can the system identify missing or conflicting information
before the workflow moves forward?
5. Act
Who owns the next action?
Not “someone.”
A specific person or workflow.
This is how you move from reactive billing to deterministic
revenue workflows.
A Monday-morning experiment
Don't buy anything.
Don't launch a transformation initiative.
Don't schedule 17 meetings.
Pick one denial.
Just one.
Trace it.
Then trace another.
Then another.
After 10 or 20, patterns will appear.
Maybe 30% involve authorization.
Maybe several involve documentation.
Maybe one payer creates a disproportionate number of
problems.
Maybe the same missing field appears repeatedly.
Maybe physicians are repeatedly asked the same question.
Maybe the front desk is collecting information differently
depending on who is working.
You now have something much more valuable than a generic
“workflow problem.”
You have evidence.
Measure these things
Start tracking:
First-pass claim acceptance
How often does the claim move through without correction?
Preventable denial rate
Which denials could reasonably have been prevented?
Authorization rework
How often does an authorization require additional work?
Average claim touches
How many human interventions occur?
Physician clarification requests
How frequently does the physician have to reconstruct
information?
Time from encounter to clean claim
How quickly can the practice create a claim that doesn't
require correction?
Correction-loop frequency
How often does work move backward?
Administrative minutes per encounter
How much staff time is consumed outside direct patient care?
These metrics tell you something collections alone cannot.
They tell you how hard your system has to work to produce
the same result.
The hidden cost of physician attention
There is another metric that deserves more attention:
physician attention.
A physician gets a message.
“Can you clarify this?”
Five minutes.
Another message.
“Payer needs additional documentation.”
Seven minutes.
Another.
“Please add the diagnosis.”
Three minutes.
Another.
“Claim denied.”
Ten minutes.
Individually, these tasks look harmless.
Multiply them across hundreds of encounters.
Now your highest-cost employee is doing work that may not
require a physician.
That's not just a productivity issue.
It's a design failure.
A physician's scarce resource is not merely time.
It is attention.
And healthcare wastes an astonishing amount of it.
The physician should not be the integration layer
This may be one of the most important ideas in the entire
article.
When healthcare systems don't communicate, people become the
integration layer.
The nurse connects systems.
The biller connects systems.
The manager connects systems.
The physician connects systems.
The patient connects systems.
The patient should never have to become the middleware.
And neither should the physician.
Where OnnX fits
This is the problem I am working on with OnnX.
The thesis is not:
“Let's build another billing platform.”
There are plenty of those.
The thesis is:
Let's move revenue-cycle intelligence upstream.
If a missing piece of information can be identified before
the claim is created, why wait for the payer to tell us?
If documentation can be structured closer to the point of
capture, why reconstruct it later?
If a predictable payer requirement can be recognized
earlier, why discover it after submission?
If information already exists, why make another human hunt
for it?
The goal is not to replace the people doing the work.
It is to reduce the unnecessary work surrounding them.
Less correction.
Less searching.
Less re-entry.
Less backtracking.
Less physician interruption.
More time for care.
But there is a trap for healthcare founders
Healthcare founders should be careful here.
It is incredibly easy to build a beautiful solution around
the wrong problem.
You see a denial.
You build denial software.
You see prior authorization.
You build authorization software.
You see documentation.
You build documentation software.
You see an inbox.
You build another inbox.
Soon the clinic has 11 solutions for the same patient.
That's not interoperability.
That's software sprawl.
The better question is:
What information moves through all of these workflows?
That's where the architecture gets interesting.
Legal and compliance considerations
There is no shortcut around healthcare's legal and
compliance environment.
Clinical and billing workflows can involve protected health
information, payer requirements, documentation standards and state and federal
obligations.
Automation should therefore be designed with appropriate:
Access controls
Audit trails
Data security
Human oversight
Role-based permissions
Vendor agreements
Documentation standards
Change management
And clear accountability.
AI should assist with information handling.
It should not manufacture medical facts.
That distinction is essential.
A system that confidently invents a justification is not
intelligent.
It is dangerous.
Ethical considerations
There is also an ethical question that gets overlooked when
we talk about efficiency.
Efficient for whom?
The payer?
The practice?
The physician?
The patient?
Everyone?
Sometimes those interests align.
Sometimes they don't.
A faster denial process isn't necessarily better.
A faster prior authorization isn't necessarily better if the
wrong information is used.
A faster claim isn't necessarily better if it contains
inaccurate information.
The goal should be friction reduction without truth
reduction.
That's an important distinction.
We should make healthcare easier.
We should not make it less honest.
What healthcare leaders may be missing
Here is my contrarian view:
The next major healthcare efficiency gains may not come
from doing more things faster.
They may come from eliminating the things that should never
have been done.
That means:
Fewer duplicate entries.
Fewer clarification messages.
Fewer authorization resubmissions.
Fewer claim corrections.
Fewer phone calls.
Fewer manual searches.
Fewer handoffs without ownership.
Fewer situations where the patient has to tell the same
story again.
That is not as exciting as announcing a new AI model.
But it may matter more to the people actually running
practices.
The human ROI
Healthcare leaders talk constantly about financial ROI.
Fair enough.
But there is another ROI:
human ROI.
What happens when a nurse gets 30 minutes back?
What happens when a physician gets 20 messages removed from
the inbox?
What happens when a biller no longer has to chase
information?
What happens when the patient doesn't need to call twice?
What happens when the practice manager can spend an
afternoon improving the business instead of repairing yesterday's mistakes?
Those are real returns.
They simply don't always fit neatly into a financial
dashboard.
The future isn't “more AI”
That's too easy.
The future is likely to be better-connected workflows,
with AI becoming one component.
AI will increasingly help interpret information.
Automation will increasingly move information.
Humans will increasingly focus on exceptions and judgment.
But the foundation remains the same:
Good information.
At the right time.
In the right place.
With clear ownership.
That's not futuristic.
That's basic operational hygiene.
Healthcare just hasn't mastered it yet.
And now, back to Ray
Ray Vetuskey has a kidney from his mother.
He has had it for 48 years.
The kidney has now reached approximately 100 years of
biological life.
His mother died in 2008.
But her gift continues.
Ray still thinks about her every day.
He still has the ticket from that Genesis concert.
That is what successful healthcare ultimately looks like.
Not another completed claim.
Not another dashboard.
Not another metric.
A patient gets to go live.
That is the outcome.
What is your practice giving back?
This is the question I would leave with every physician and
clinic owner:
What could your practice give back if you eliminated the
administrative friction that never needed to exist?
Maybe it's 30 minutes.
Maybe it's an hour.
Maybe it's a full evening.
Maybe it's fewer weekends spent catching up.
Maybe it's a nurse who stops dreading the authorization
queue.
Maybe it's a biller who stops opening Monday morning to 47
preventable problems.
Maybe it's a patient who doesn't have to call three times.
Maybe it's simply the ability to finish clinic and go home.
Healthcare often measures what it takes.
We should also measure what it gives back.
Recent News: the bigger healthcare conversation
This week provides a useful backdrop for this discussion.
The University of Rochester Medicine story about Ray
Vetuskey demonstrates the extraordinary long-term value that can come from a
successful intervention followed by decades of monitoring and care.
On September 30, physician Lourdes G. Bahamonde wrote about
another side of healthcare: standardized pathways can become so focused on
completion that individualized clinical judgment risks getting lost.
And a September 29 JAMA Perspective by Adam P.
Sawatsky, MD, MS, and Andrea N. Leep Hunderfund, MD, MHPE, examines the tension
between professional values and the market, managerial and platform pressures
shaping contemporary medical practice.
These stories are different.
But they point toward the same question:
Are we designing healthcare around the patient journey—or
around the completion of individual tasks?
That may be one of the defining operational questions of
modern medicine.
Three practical lessons
Lesson 1: Find the earliest failure point
Don't start with the denial.
Trace backward.
The earlier you identify the problem, the cheaper it usually
is to fix.
Lesson 2: Separate information from action
Knowing something exists is not enough.
Someone needs to know:
What is it?
Does it matter?
Is it complete?
What happens next?
Who owns that next step?
Lesson 3: Optimize for fewer correction loops
A workflow that requires constant correction is telling you
something.
Listen to it.
Don't simply hire more people to compensate for it.
FAQ
Is Ray Vetuskey's kidney really 100 years old?
University of Rochester Medicine reported that the kidney
donated by his mother, Elizabeth “Betty” Vetuskey, has reached approximately
100 years of biological age. Ray received the kidney in 1978 when he was 16.
How long has Ray had the kidney?
Approximately 48 years as of 2026.
Is this a world record?
The University of Rochester describes Ray as the longest-surviving
kidney transplant recipient in its program. The article does not establish
that his case is the world's longest-surviving transplant.
What does a transplant story have to do with medical
billing?
The connection is not the medical procedure itself.
It is continuity.
A successful healthcare journey requires information, people
and decisions to remain connected across time.
Does better information eliminate denials?
No.
Payer policies, clinical complexity, eligibility, coding,
documentation and other factors can all contribute to denials.
But practices can often identify predictable failure points
and reduce preventable rework.
Is AI the answer?
AI can be part of the answer.
It can help extract, organize, compare and prioritize
information.
But it should not replace clinical judgment or
accountability.
What should a clinic owner measure first?
Start with a manageable set:
Preventable denials.
Average claim touches.
Authorization rework.
Physician clarification requests.
Time to clean claim.
Correction-loop frequency.
These metrics can expose hidden operational costs.
What is the biggest mistake practices make?
Treating every downstream problem as an isolated event.
The denial becomes a billing problem.
The authorization becomes an authorization problem.
The documentation becomes a documentation problem.
Sometimes they are actually different symptoms of the same
upstream information problem.
Tools and resources
You don't need to start with another software platform.
Start with what you already have.
Your EHR.
Your clearinghouse reports.
Your payer portals.
Your authorization logs.
Your denial reports.
Your staff.
Your physician inbox.
Your patient complaints.
Then build simple operational tools:
Denial root-cause log
Authorization checklist
Information ownership map
Exception queue
Claim-touch tracker
Physician interruption log
Pre-submission validation rules
The objective isn't more administration.
It's better visibility.
The 30-day practice experiment
Week 1: Observe
Choose one service line or payer.
Track every denial, correction and authorization problem.
Don't fix anything yet.
Just observe.
Week 2: Categorize
Group problems by root cause.
Missing information.
Wrong information.
Late information.
Duplicate information.
Unclear ownership.
Payer-specific requirement.
Clinical documentation.
Eligibility.
Coding.
Week 3: Trace
Pick the three largest categories.
Trace each one backward to the earliest point where the
problem could have been prevented.
Week 4: Change one thing
Don't redesign everything.
Fix one upstream failure.
Then measure whether downstream rework changes.
That's how you learn whether you've actually improved the
system.
Final Thoughts
Betty Vetuskey gave her son something priceless.
She gave him a kidney.
Ray gave the story something else.
He lived.
He went to a concert.
He worked.
He grew older.
He remembered his mother.
The kidney kept working.
Forty-eight years later, it still does.
The story is remarkable because of the transplant.
But it is also remarkable because of what happened after the
transplant.
Continuity.
That word deserves more attention in healthcare.
Because healthcare can perform the right procedure and still
lose the thread.
It can complete the pathway and miss the patient.
It can submit the claim and lose the information.
It can document the encounter and fail to communicate what
matters.
It can have all the data and still not know what to do next.
That is the paradox.
We have never had more healthcare data.
Yet people are still searching for information.
We have never had more software.
Yet people still fax documents.
We have never had more automation.
Yet physicians still receive messages asking them to explain
something they already documented.
We have never had more sophisticated revenue-cycle
technology.
Yet predictable problems still become denials.
Maybe the next breakthrough isn't another tool.
Maybe it's a better chain.
Capture the right information.
Connect it to the next decision.
Catch the problem before it becomes expensive.
Keep humans responsible for judgment.
And then get out of the way.
Because the best healthcare system is not the one that keeps
the patient inside the system forever.
It is the one that helps the patient get back to life.
Ray had a concert to attend.
Maybe that is the real KPI.
Get Involved: Start the Conversation
Here's the question I want to put to physicians and clinic
owners:
What problem in your practice looks like a billing
problem but actually begins somewhere earlier?
Maybe it's prior authorization.
Maybe it's documentation.
Maybe it's scheduling.
Maybe it's eligibility.
Maybe it's the handoff between clinical and billing teams.
Maybe it's something nobody has named yet.
Tell me in the comments.
Your experience may help another physician recognize the
same pattern in their practice.
Share this article with a physician, practice
administrator or clinic owner who spends too much time fixing problems that
should have been prevented upstream.
And if this perspective resonates, repost it so more
healthcare professionals can join the conversation.
Ask the uncomfortable question.
Find the upstream problem.
Build the workflow that prevents the correction loop.
Continue the Conversation
The conversation doesn't end with one article.
I write and speak about healthcare operations, medical
billing, health technology, physician entrepreneurship and the practical side
of innovation.
The goal is simple:
Less theory. More useful ideas.
Explore additional perspectives and practical resources
through my website, podcast, videos and social channels.
Knowledge drives progress. Start with one better
question.
Check the Featured section of my LinkedIn profile for
a free practical resource on medical billing and the revenue cycle. No
signup required.
Listen to the
podcast on Spotify
Subscribe and
watch on YouTube
About the Author
Dr. Daniel Cham is a physician, healthcare strategist
and medical consultant focused on the intersection of medical practice,
healthcare management, medical technology and medical billing.
He is the founder of OnnX, an AI-powered medical
billing SaaS focused on helping small and medium-sized clinics reduce
administrative friction, improve information flow and address revenue-cycle
problems closer to where they begin.
His central thesis is straightforward:
Most downstream healthcare problems have an upstream
cause.
His work focuses on helping independent practices reduce
correction loops, improve operational visibility and allow clinicians to spend
more attention on patients rather than preventable administrative work.
Connect with Dr. Cham on LinkedIn to
learn more.
Disclaimer
This article is provided for general educational and
informational purposes only. It is not medical, legal, coding, compliance,
reimbursement or financial advice.
Healthcare regulations, payer requirements and
documentation standards vary by circumstance and may change.
Physicians, healthcare organizations and other
professionals should consult qualified professionals for guidance concerning
their particular clinical, legal, compliance or financial circumstances.
References
1. University of Rochester Medicine
“Webster Man Thrives with a ‘Rare’ Century-Old Kidney” —
September 28, 2026.
Primary source for Raymond Vetuskey, his mother Elizabeth “Betty” Vetuskey, the
1978 transplant, and the kidney's extraordinary longevity.
Read the University of Rochester Medicine article
2. Lourdes G. Bahamonde, DO, MS
“The Elephant in the Room: What Medicine Misses When Care
Becomes Fragmented” — September 30, 2026.
Dr. Bahamonde discusses how standardized healthcare pathways can miss
individualized clinical judgment and what happens when care becomes fragmented.
Read Dr. Bahamonde’s article in The DO
3. Adam P. Sawatsky, MD, MS & Andrea N. Leep
Hunderfund, MD, MHPE
“Health Care’s Identity Crisis—Is Medicine Still a
Profession?” — JAMA, September 29, 2026.
The Perspective examines tensions between physicians' professional values and
market, managerial, and platform pressures shaping contemporary healthcare.
Final Invitation
What if your next revenue-cycle improvement didn't begin
with the denial?
What if it began with the first piece of information that
made the denial possible?
Tell me where information gets lost in your practice.
Then share this article with another physician or clinic
owner who may be fighting the same problem.
Because sometimes the biggest healthcare improvement isn't
doing more.
It's making sure the right information survives the
journey.
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#DigitalHealth #IndependentPractice #OnnX
