A cancer survivor’s journey from patient to medical student reveals what healthcare technology should really be designed to protect: the physician’s attention and the human connection at the heart of care.
“AI should be a tool that empowers physicians, restores
time with patients, and ultimately humanizes healthcare.” — Dr.
Imamu “Mu” Tomlinson, emergency physician and CEO of Vituity
At 18, Tyler Tabor was not thinking about artificial
intelligence.
He wasn't thinking about medical billing.
He wasn't thinking about healthcare innovation.
He was thinking about cancer.
Tabor had been diagnosed with Stage IIB Hodgkin's
lymphoma involving his neck. He began treatment at The University of New
Mexico Hospital in Albuquerque, New Mexico.
He was frightened.
He was young.
And suddenly, instead of preparing for whatever comes next
in life, he was learning how to survive it.
His pediatric oncologist was Jessica Valdez, MD, MPH,
FAAP.
But something unusual happened during that relationship.
Tabor didn't just become Valdez's patient.
He told her he wanted to become a doctor.
And Valdez apparently took that dream seriously.
She told him they would get him there.
Years later, after treatment, relapse and a stem-cell
transplant in Colorado, Tabor survived cancer.
Then came the next chapter.
On July 24, 2026, Tabor put on a white coat as a
first-year medical student at the University of New Mexico School of
Medicine.
The former cancer patient was now entering the profession
that had once cared for him.
He described it beautifully:
He was moving to “the other side of the gurney.”
Think about that for a second.
The patient became the medical student.
The frightened teenager became the future physician.
And the physician who treated him became one of the people
who helped him imagine that future.
That's healthcare at its best.
Not a dashboard.
Not an algorithm.
Not a billing platform.
A relationship.
And that is exactly why I think we are asking the wrong
question about healthcare technology.
We keep asking:
“What can AI do?”
Maybe we should be asking:
“What are we making physicians do that they never should
have been doing in the first place?”
The uncomfortable healthcare problem nobody wants to call
by its real name
We have a strange habit in healthcare.
We say we want physicians to spend more time with patients.
Then we give them more administrative work.
We say we want clinicians to practice at the top of their
license.
Then we ask them to chase documentation.
We say patient experience matters.
Then we make patients navigate confusing billing systems.
We say physicians should listen.
Then we interrupt them with tasks that software could
potentially handle.
We say burnout is a physician wellness problem.
Sometimes it looks suspiciously like a workflow problem.
The American Medical Association continues to identify
administrative burden as something that directly interferes with the
physician-patient relationship.
That's the part we should pay attention to.
Because administrative burden isn't simply annoying.
It competes with something scarce:
human attention.
And attention is one of the most valuable resources in
medicine.
What if physician attention were a clinical resource?
We measure everything.
Visits.
RVUs.
Claims.
Denials.
Days in A/R.
Patient satisfaction.
Length of stay.
Readmissions.
Productivity.
But we rarely ask:
How much of the physician's attention did the system
consume today?
Imagine a physician begins the morning with 100 units of
attention.
A patient needs 20.
Another patient needs 15.
A complicated diagnosis needs 25.
A family needs 10.
A trainee needs 5.
Now add:
Three payer messages.
Two coding questions.
A rejected claim.
A prior authorization.
A documentation clarification.
An insurance portal.
A form.
Another form.
Suddenly the physician isn't short on intelligence.
They're short on attention.
And no productivity seminar can manufacture more of it.
The irony of healthcare AI
Here's my contrarian take:
Healthcare doesn't necessarily need more AI.
It needs less unnecessary work.
That's different.
We have become fascinated with AI because it sounds
futuristic.
But the most valuable application of AI in a medical
practice may be remarkably unglamorous.
Find the denied claim.
Explain why it was denied.
Find the relevant documentation.
Identify the likely correction.
Prepare the next step.
Ask a human to approve it.
Move on.
No robot doctor.
No holographic physician.
No sci-fi soundtrack.
Just fewer things sitting in someone's inbox.
And honestly?
That might be more useful.
The AI arms race may be missing the point
Healthcare organizations are racing to announce AI
initiatives.
AI scribes.
AI assistants.
AI copilots.
AI agents.
AI coding.
AI claims.
AI documentation.
AI everything.
But here's the question I would ask before buying any of it:
What human work disappears?
If the answer is:
“None, but now we have an AI dashboard,”
we haven't solved the problem.
We've added another dashboard.
Congratulations.
The inbox has acquired artificial intelligence.
The inbox is still an inbox.
Tyler Tabor's story exposes something technology cannot
replace
Tabor's story is powerful precisely because it is so human.
He was sick.
Someone cared for him.
Someone encouraged him.
He survived.
He remembered.
And now he wants to become that person for somebody else.
His oncologist, Jessica Valdez, became more than the
person treating his cancer. She became a mentor and role model.
That distinction matters.
Because healthcare isn't simply an exchange of information.
It's an exchange of trust.
A patient is often asking a physician something deeper than:
“What is my diagnosis?”
They're asking:
“Am I going to be okay?”
No software can completely answer that question.
Even when the medical answer is uncertain, the physician can
still say:
“We're going to work through this together.”
That's not inefficiency.
That's medicine.
And yet we're spending enormous amounts of clinician time
on things that aren't medicine
This is where I see the opportunity.
The administrative machinery surrounding medicine has become
incredibly complex.
A typical revenue-cycle journey can look something like:
Patient → documentation → coding → claim → payer → denial
→ correction → appeal → payment → A/R
Every arrow is a handoff.
Every handoff is an opportunity for delay.
Every delay can create more work.
And every additional manual step consumes someone's
attention.
The problem isn't that billing exists.
Billing has to exist.
Clinics have payroll.
They have rent.
They have supplies.
They have staff.
They have technology.
They need revenue to continue providing care.
The problem is that we sometimes confuse necessary
administration with necessary human labor.
Those aren't the same thing.
This is where I think the industry has it backward
We often ask:
“Can AI replace the biller?”
I think that's the wrong question.
Ask instead:
“Which parts of the billing workflow should never have
required a person to perform them manually?”
That's a much more interesting question.
Maybe the future isn't:
AI versus billers.
Maybe it's:
AI + billing expertise.
Let AI search.
Let AI organize.
Let AI identify patterns.
Let AI flag exceptions.
Let AI prepare.
Let humans decide.
That is a much more defensible model.
What I'm building with OnnX
This is the philosophy behind OnnX, the AI-powered
medical billing SaaS I founded.
The goal isn't to replace the people who understand
healthcare.
It's to reduce unnecessary friction in the workflow.
Think about a denied claim.
Traditional workflow:
Someone notices it.
Someone opens the payer portal.
Someone reads the denial.
Someone finds the chart.
Someone checks the documentation.
Someone asks what happened.
Someone figures out the correction.
Someone resubmits it.
Someone tracks it.
Someone follows up.
And eventually someone wonders:
“Why did we spend this much human time on one claim?”
That's the opportunity.
OnnX is built around the idea that AI can help analyze the
problem, retrieve relevant information, recommend the next action and prepare
the work for human review.
The human remains accountable.
The workflow becomes smarter.
And ideally, the physician sees less of it.
That's the point.
Don't automate the mess
Here's another unpopular opinion:
Don't automate a broken workflow.
Fix it first.
If three people manually enter the same information into
three systems, don't immediately build AI to do the same thing faster.
Ask why the information has to be entered three times.
If a denial requires five people to understand, don't
immediately build a five-person AI workflow.
Ask why the process is so difficult.
If a physician is being asked to clarify the same
documentation issue repeatedly, don't just add another notification.
Fix the source.
Automation without workflow redesign is just faster
bureaucracy.
That's the sentence I would put on the wall.
Three questions every clinic owner should ask
Before buying another healthcare technology product, ask:
1. What problem are we actually solving?
Not:
“Where can we use AI?”
Ask:
“Where are we losing time, money or attention?”
2. What happens today?
Map the actual workflow.
Not the PowerPoint version.
The real version.
Who touches the work?
How many times?
How many systems?
How many handoffs?
How many exceptions?
3. What should disappear?
That's the most important question.
Not:
“What new feature should we add?”
But:
“What work should no longer exist?”
The statistics tell an uncomfortable story
Recent healthcare reporting reinforces the pressure.
The latest AMA data show physician burnout has declined
overall, but some specialties continue to report burnout rates above 40%.
Meanwhile, a recent Healthcare IT News report found that
nearly two-thirds of surveyed practice employees said manual data entry
consumes at least an hour of their workday.
That's a lot of human attention.
And here's the interesting part.
We don't necessarily have to solve it with more people.
We can redesign the work.
That's where automation becomes interesting.
But AI doesn't automatically save time
This is where I'm intentionally skeptical.
AI vendors love saying:
“Save hours every week.”
Maybe.
Maybe not.
Recent medical commentary has questioned whether AI tools,
including clinical documentation systems, always deliver the promised time
savings in real-world practice.
Why?
Because implementation matters.
A tool can generate a draft.
Someone still has to review it.
A tool can identify a claim problem.
Someone still needs to validate it.
A tool can automate one task.
But if it creates two new tasks, you've gone backward.
That's why I don't think AI adoption should be the
metric.
Work eliminated should be.
The new ROI question
Forget:
“How many AI features did we deploy?”
Ask:
How many unnecessary human touches did we remove?
Then ask:
What happened to the time we recovered?
That's where ROI becomes interesting.
If staff saved 100 hours and used them to process 100 more
claims, that's one outcome.
If those 100 hours allowed them to answer patient calls
faster, coordinate care, reduce delays and support physicians, that's another.
And if physicians recovered meaningful time with patients?
Now we're talking about something bigger than revenue-cycle
efficiency.
We're talking about care capacity.
Three experts. Three lessons.
Jessica Valdez, MD, MPH, FAAP: don't underestimate the
power of believing in a patient
Valdez treated Tabor when he was a teenager.
But she also encouraged his ambition to become a physician.
The lesson is profound:
A clinician's influence can outlive the clinical
encounter.
Tabor didn't just survive cancer.
He carried something from that experience into his future
profession.
Healthcare leaders should think about that.
Every patient encounter has an emotional component.
Every clinician has an opportunity to shape how a patient
sees the future.
That cannot be reduced to a CPT code.
Richard Holt and the lesson of “boring” quality
Recent commentary in The Permanente Journal
emphasizes patient perceptions of timeliness, coordination, clarity and
kindness as meaningful aspects of cancer care.
Notice something.
None of those words sounds particularly futuristic.
That's the point.
Healthcare doesn't always need to become more complicated to
become better.
Sometimes it needs to become easier to navigate.
Dr. Imamu “Mu” Tomlinson: AI should give physicians time,
not take judgment away
Recent discussion around AI in healthcare has emphasized a
boundary worth preserving:
AI can support physicians.
It should not casually replace human judgment in
consequential medical decisions.
That is particularly important when decisions involve
life-changing treatment, patient context or end-of-life care.
The principle applies to administrative AI too.
Automate the repetitive. Escalate the uncertain. Keep
humans accountable.
Simple.
Not always easy.
But simple.
The myth of “full automation”
Here's a myth I would like healthcare leaders to retire:
The best AI system is the one that requires the least
human involvement.
Not necessarily.
The best system is the one that puts human involvement
where it creates the most value.
If AI can check 10,000 routine data points, let it.
If a physician needs to decide whether a complicated case is
adequately supported, let the physician decide.
If a biller needs to handle an unusual payer situation, let
the biller handle it.
The goal isn't zero humans.
The goal is humans doing human work.
Another myth: “Billing is just back-office work”
I disagree.
Billing is back-office infrastructure.
But infrastructure affects the front office.
A clinic with poor cash flow may delay hiring.
A practice with chronic denial problems may lose resources.
Administrative overload can contribute to burnout.
Billing confusion can frustrate patients.
So yes, billing is administrative.
But administrative doesn't mean irrelevant to patient
care.
The legal and ethical line
AI-powered billing has another reality that should not be
ignored.
Healthcare data is sensitive.
Claims are consequential.
Coding has compliance implications.
Documentation matters.
Payer contracts matter.
Privacy matters.
Auditability matters.
So a responsible system needs more than a clever model.
It needs:
security
access controls
audit trails
human review
data governance
clear accountability
appropriate vendor agreements
transparent workflows
The question isn't merely:
“Can AI do this?”
It is:
“Can AI do this safely, explainably and accountably?”
The workflow I want to see
Imagine this.
A claim is submitted.
The system notices a potential problem.
Instead of waiting for the payer to reject it, the system
flags the issue.
It explains why.
It identifies supporting information.
It gives the billing professional a recommendation.
The professional approves.
The claim moves forward.
If the system isn't confident?
It escalates.
If the issue involves clinical judgment?
It doesn't pretend otherwise.
If the action has significant consequences?
A human remains in control.
That's not AI replacing healthcare workers.
That's AI respecting healthcare workers' time.
A six-step playbook for clinic owners
Step 1: Find your ugliest workflow
Not your most exciting one.
Your ugliest.
The one everyone complains about.
Step 2: Count the human touches
How many people touch it?
How many times?
Step 3: Identify the exception
What causes the workflow to break?
Step 4: Separate routine from judgment
Automate the routine.
Protect the judgment.
Step 5: Pilot one workflow
Don't transform the entire practice on Monday morning.
Start small.
Step 6: Measure what matters
Track:
Denial rate
Clean claim rate
Days in A/R
A/R aging
Staff touches
Time to resolution
First-pass resolution
Administrative minutes
And one more:
Physician attention returned.
What failure looks like
Let's be honest.
Some AI projects will fail.
Some integrations will be painful.
Some models will make mistakes.
Some staff will hate the first version.
Some workflows will turn out to be more complicated than
expected.
That's normal.
The real failure is pretending otherwise.
The better approach is to build feedback loops.
Ask staff:
What did the system get wrong?
Ask physicians:
What interrupted you?
Ask billing teams:
What still requires manual work?
Ask patients:
Did anything actually become easier?
Innovation isn't the absence of failure.
It's learning faster than the failure costs you.
The funniest thing about healthcare innovation
We sometimes spend $500,000 trying to save five minutes.
Then discover the five minutes were spent because someone
had to log into three different systems.
I'm exaggerating.
But only slightly.
Healthcare has accumulated layers of software over decades.
EHR.
Payer portal.
Clearinghouse.
Scheduling system.
Billing platform.
Fax.
Email.
Spreadsheet.
Password manager.
And, somewhere in the corner:
one person who knows how everything actually works.
That person is usually the real operating system.
And everyone is terrified they'll take a vacation.
That's not digital transformation.
That's institutional memory with a login.
The real opportunity for healthcare founders
If you're building healthcare technology, I would challenge
you to stop asking:
“Where can we insert AI?”
Ask:
“Where is human attention being wasted?”
That is a better startup question.
Find repetitive cognitive work.
Find fragmented workflows.
Find expensive handoffs.
Find exception-heavy processes.
Find tasks physicians hate.
Find tasks nurses hate.
Find tasks billing teams hate.
Then design around the workflow.
Not the technology.
The technology is the means.
The workflow is the product.
Why small and midsize clinics matter
Large health systems can absorb inefficiency differently.
Small and midsize practices often cannot.
One employee leaving can matter.
One prolonged denial can matter.
One broken workflow can matter.
One hour of physician time can matter.
One unnecessary software subscription can matter.
That's why I believe healthcare automation needs to become
more practical.
Less:
“Look what our AI can do.”
More:
“Here is the work we removed.”
That's a much harder claim.
It's also much more useful.
What I would measure at OnnX
If you're building an AI medical billing platform, vanity
metrics are easy.
Number of claims processed.
Number of AI interactions.
Number of users.
Number of recommendations.
Those are interesting.
But I care more about:
How many claims required human intervention?
How quickly were denials identified?
How often were recommended corrections accepted?
How much manual work disappeared?
How much revenue moved through the system?
How much physician or staff attention was returned?
That is where the value lives.
The bigger idea: attention is infrastructure
We normally think of infrastructure as roads, buildings,
networks and software.
I think healthcare has another form of infrastructure:
human attention.
And we're consuming it faster than we're replenishing it.
Every unnecessary click takes a little.
Every redundant form takes a little.
Every avoidable denial takes a little.
Every unnecessary notification takes a little.
Every poorly designed workflow takes a little.
Eventually, you have a clinician who is physically present
but mentally fragmented.
That's dangerous.
Because the opposite of patient-centered care isn't
necessarily cruelty.
Sometimes it's distraction.
Tyler Tabor gives us the test
Tyler Tabor's story gives healthcare technology a simple
test.
Imagine Tabor's future patient.
Imagine that patient sitting across from him.
Imagine Tabor trying to listen.
Now imagine someone interrupts him with an unnecessary
administrative task.
Then another.
Then another.
What should technology do?
Not make Tabor faster at multitasking.
Not give him another dashboard.
Not turn him into a more efficient administrator.
Give him his attention back.
Because someday, there may be another 18-year-old sitting on
the other side of that gurney.
And that patient deserves the doctor.
Not the inbox.
The future of medical billing shouldn't look like more
billing
This may sound strange coming from someone who founded an AI
medical billing company.
But I don't want the future to be about making physicians
better at billing.
I want it to be about making billing less visible to
physicians.
That is the difference.
The physician should understand the economics of the
practice.
Absolutely.
The physician should understand documentation and coding.
Yes.
But they shouldn't have to become a human middleware layer
connecting every broken administrative system.
That's what software should be for.
Here's the argument I would make to healthcare leaders:
Stop trying to make physicians more efficient at doing
unnecessary work.
Instead, eliminate the work.
That's harder.
It requires redesign.
It requires uncomfortable conversations.
It may require changing contracts, workflows, staffing
models and software.
But that's where real innovation lives.
Not in adding another tool.
In removing a step.
Final Thoughts: What if the future of healthcare is
actually less technological?
Tyler Tabor survived cancer.
His physician encouraged him.
His mother supported him.
His community helped him.
Now he's learning to become the physician on the other side
of the gurney.
There is something almost beautifully old-fashioned about
that story.
One human being helped another human being.
Then the first person decided to help someone else.
That's healthcare.
Technology should support that chain.
It shouldn't interrupt it.
So perhaps the question isn't:
“How much AI will healthcare use?”
Perhaps the better question is:
“How much unnecessary work can we remove before AI even
becomes necessary?”
And when AI is useful, let's use it.
Let it search.
Let it summarize.
Let it detect patterns.
Let it organize.
Let it predict.
Let it prepare.
But when a patient looks across the room and asks:
“Doctor, what happens now?”
I don't want the system answering.
I want the physician to have enough attention left to
answer.
That's the standard.
And perhaps that's what Tyler Tabor's story really teaches
us.
The future physician may have better technology.
But the patient will still need a human being.
Get Involved
Here's the question I want to leave with physicians and
clinic owners:
If you could permanently eliminate one administrative
task from your practice tomorrow, what would it be?
Don't give me the polished answer.
Give me the task that makes you think:
“Why are we still doing this?”
Tell me in the comments.
And if this perspective resonates with you, repost it
and bring another physician, practice owner, administrator, or healthcare
innovator into the conversation.
Because healthcare doesn't need another slogan about
transformation.
It needs fewer unnecessary steps.
Find one workflow. Fix one bottleneck. Give one clinician
some attention back.
That's where meaningful change starts.
About the Author
Dr. Daniel Cham is a physician, medical consultant
and healthcare entrepreneur focused on the intersection of medical
technology, healthcare operations, medical billing and workflow automation.
He is the founder of OnnX, an AI-powered medical
billing SaaS focused on helping small and midsize medical practices reduce
unnecessary administrative friction.
His approach is deliberately practical:
Don't automate everything. Automate what shouldn't
require human attention.
Connect with Dr. Cham on LinkedIn to
learn more.
Continue the Conversation
Healthcare innovation is not just about building smarter
technology.
It is about asking better questions about the work
surrounding patient care.
For more perspectives on healthcare operations, medical
billing, AI, workflow automation and medical practice innovation, explore:
- Visit
the personal website
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to the podcast on Spotify
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and watch on YouTube
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updates on X (Twitter)
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·
Connect
professionally on LinkedIn
Knowledge creates leverage. Better questions create
better healthcare. Start there.
Check the Featured section of my LinkedIn profile for
a free resource available without an email signup.
And if this article made you rethink the relationship
between physician attention, administrative burden and healthcare technology,
consider reposting it so another physician or clinic owner can join the
conversation.
Disclaimer
This article is intended for general educational and
informational purposes only. It is not legal, medical, compliance, financial or
professional advice. Healthcare organizations should consult appropriately
qualified professionals regarding their specific clinical, legal, regulatory,
privacy, billing and technology circumstances.
References
1. University
of New Mexico Health Sciences — “From Cancer Patient to Healthcare
Provider”
The August 28, 2026 story chronicles Tyler Tabor's journey from Hodgkin's
lymphoma patient at UNM Hospital to first-year medical student and highlights
his relationship with pediatric oncologist Jessica Valdez.
2. American
Medical Association — Administrative Burdens
The AMA identifies administrative burden as a factor that can interfere with
the physician-patient relationship and provides resources aimed at reducing
unnecessary administrative work.
3. Healthcare
IT News — Healthcare practices and AI automation
Recent reporting highlights growing interest in AI and automation to reduce
manual administrative work, while also noting fragmented software environments
and privacy concerns.
#Healthcare #MedicalBilling #HealthcareAI #Physicians
#ClinicOwners #HealthcareInnovation #MedicalPracticeManagement
#RevenueCycleManagement #WorkflowAutomation #HealthTech #PhysicianBurnout
#PatientCare #ArtificialIntelligence #HealthcareLeadership #DigitalHealth
#IndependentPractice #ResponsibleAI #HealthcareOperations #MedicalTechnology
#OnnX
The future of healthcare isn't about putting more
technology between physicians and patients.
It's about using technology to remove the things that
shouldn't be between them in the first place.
The goal isn't to make physicians better administrators.
It's to give them more room to be physicians.
