She knew how healthcare worked. Then she experienced it from the other side. What she learned should make every healthcare leader rethink innovation, physician time, and the work technology should actually remove.
“Kedar has spent his career helping healthcare
organizations deliver better outcomes for the people they serve.” — Pamela
DeCoste, Board Chair, Blue Shield of California, August 21, 2026
Kourtney B. Martin, CNM, knew exactly what was supposed to
happen.
That was the problem.
She was not a first-time observer of pregnancy, labor or
delivery.
She was a certified nurse midwife with Norton Women’s
Care in Louisville, Kentucky.
She had spent years caring for women during some of the most
vulnerable moments of their lives.
She knew the terminology.
She knew the procedures.
She knew the warning signs.
She knew what clinicians were looking for.
She knew what questions patients were likely to ask.
She knew what could go wrong.
And then she became pregnant with her second child.
Suddenly, Kourtney Martin was not standing beside the bed.
She was in it.
Her colleague and friend, Kimberly S. Barnes, APRN, CNM,
was there to help guide her.
So was a labor-and-delivery nurse named Devin, who
was training to become a midwife.
Before Martin's induction, Devin decorated her room with
streamers and the baby's name.
Later, when Martin became nervous during her epidural, Devin
held her.
Think about that for a second.
No algorithm did it.
No dashboard did it.
No chatbot did it.
No billion-dollar healthcare platform did it.
A person held another person's hand.
And Martin remembered.
She later described how reassuring it was to have familiar
people around her who she trusted to care for and protect her and her baby.
She also said that experiencing pregnancy, delivery and
postpartum care from the patient's side made her more empathetic.
That is a beautiful story about childbirth.
But I think it is also a story about healthcare's biggest
problem.
And it has surprisingly little to do with childbirth.
It has to do with attention.
Who gets it?
Who loses it?
Who protects it?
And who gets buried under everything else?
Because there is another person in healthcare who knows
exactly what it feels like to be pulled away from the thing that matters most.
The physician.
What if the problem isn't physician burnout?
Before you disagree with me, hear me out.
We have spent years talking about physician burnout.
We have conferences about it.
Surveys about it.
Wellness programs about it.
Resilience workshops.
Mindfulness sessions.
Leadership initiatives.
Employee assistance programs.
Sometimes we even give doctors pizza.
Nothing against pizza.
But perhaps we have been asking the wrong question.
Maybe the question isn't:
“Why can't physicians handle the pressure?”
Maybe it is:
“Why have we designed so much work that physicians
shouldn't have to do in the first place?”
That is a very different question.
And it changes the solution.
The American Medical Association reports that physician
burnout has improved, with 41.9% of physicians reporting at least one
symptom of burnout in 2025, down from 43.2% in 2024 and 48.2% in 2023.
That is genuinely good news.
But improvement does not mean the problem has disappeared.
Administrative work, EHR inefficiencies and staffing
challenges remain important sources of physician stress.
So perhaps we should stop treating burnout as an individual
defect.
Maybe some of it is simply workflow debt.
Healthcare has accumulated years of inefficient processes.
Physicians are paying the interest.
The physician's second job
Nobody really tells you about this part of becoming a
physician.
You go to medical school.
You learn anatomy.
You learn physiology.
You learn pharmacology.
You learn diagnosis.
You learn procedures.
You learn how to manage uncertainty.
You learn how to sit with someone who has just received
devastating news.
Then you discover another career waiting for you.
Claims analyst.
Coder.
Payer negotiator.
Prior-authorization specialist.
Documentation auditor.
Portal operator.
A/R investigator.
Sometimes amateur IT technician.
Occasionally unpaid collections manager.
It is quite the residency curriculum.
And somehow, "medical billing" wasn't on the MCAT.
Yet physicians can end up spending substantial time dealing
with it.
That should bother us.
Not because billing is unimportant.
It is extremely important.
A medical practice cannot survive if it does not get paid.
But the physician is not necessarily the right person to
perform every step required to get the practice paid.
That distinction matters.
The hidden cost of a denied claim
Let's say a claim gets denied.
On paper, it is a financial event.
$287 denied.
$1,400 denied.
$7,800 denied.
The revenue-cycle department sees a dollar amount.
But the real cost may be much larger.
Someone has to open the denial.
Someone has to understand why it happened.
Someone has to find the documentation.
Someone has to check the payer's rules.
Someone has to determine whether the claim needs correction
or appeal.
Someone has to prepare the response.
Someone has to submit it.
Someone has to track it.
Someone has to follow up.
And sometimes the physician gets pulled into the middle.
Now that $287 denial is no longer $287.
It is:
$287 + staff time + physician time + rework + cognitive
interruption + delay + frustration.
The spreadsheet sees revenue.
The human sees another interruption.
That is the hidden economy of administrative healthcare.
We measure dollars. We rarely measure attention.
This is one of the biggest blind spots in healthcare
operations.
We measure:
Revenue.
A/R.
Denial rates.
Collection rates.
Visits.
Productivity.
Length of stay.
Readmissions.
But how often do we measure:
How many times did we interrupt the physician today?
How much time did the practice spend looking for information
that already existed somewhere?
How many times did staff enter the same information into
different systems?
How many tasks were created because another task was done
incorrectly?
How many hours were spent fixing problems that should never
have occurred?
And perhaps the most important question:
How much human attention did the workflow consume?
Attention is a healthcare resource.
We just don't put it on the balance sheet.
Kourtney Martin understood something about healthcare
that dashboards cannot capture
When Martin became the patient, she already knew what was
happening clinically.
But clinical knowledge didn't eliminate vulnerability.
She still needed reassurance.
She still needed communication.
She still needed trust.
She still needed someone she knew.
That tells us something important.
Healthcare is not merely an information-delivery system.
It is a relationship.
The patient is not a case.
The physician is not a productivity unit.
The nurse is not a staffing ratio.
The biller is not a labor expense.
These are human beings operating inside a complicated
system.
And systems can either protect human attention or consume
it.
Here is my contrarian take
I think healthcare has a technology problem.
But it is not the technology problem most people talk about.
We do not necessarily need more technology.
We need better choreography between people, technology
and workflow.
Healthcare has accumulated tools like a person who keeps
downloading productivity apps but never cleans the kitchen.
We have:
An EHR.
A clearinghouse.
A billing platform.
A payer portal.
A scheduling system.
A fax machine that somehow survived the digital revolution.
A spreadsheet.
Email.
Text messages.
Phone calls.
Passwords.
More passwords.
And another password to reset the password.
Then we put AI on top.
And call it innovation.
Sometimes it is.
Sometimes it is just digital clutter with a language
model attached.
The real innovation is not adding another tool.
It is removing unnecessary steps.
Start with the work, not the AI
This is the part I wish more healthcare technology companies
talked about.
Don't start with:
“Where can we use AI?”
Start with:
“Where are humans doing repetitive cognitive work that
does not require human judgment?”
That question is much more useful.
For example:
A claim is rejected.
Does a human really need to manually determine the basic
rejection category every time?
A payer sends a repetitive message.
Does someone need to read it from scratch?
A work queue contains hundreds of claims.
Does a manager need to manually determine which ones deserve
attention first?
A denial follows a familiar pattern.
Does someone need to rediscover the same solution every
week?
Maybe.
Maybe not.
But these are questions worth asking.
AI's best job may be boring
There is a lot of excitement about AI diagnosing rare
diseases.
AI discovering drugs.
AI transforming medicine.
AI replacing entire departments.
Those stories get clicks.
But the most valuable AI in a medical practice may do
something incredibly boring.
It might say:
“This claim looks like the last 37 claims that were
denied for the same reason.”
That doesn't sound revolutionary.
Good.
Maybe healthcare needs fewer revolutionary demos and more
boring things that actually work.
An AI system that quietly identifies a pattern before a
human spends 20 minutes investigating it can create real value.
An AI system that prepares a denial for review can create
real value.
An AI system that prioritizes A/R work can create real
value.
An AI system that identifies missing information before
submission can create real value.
The future may be less glamorous than the keynote speeches
suggest.
And that's okay.
The real opportunity: cognitive offloading
We talk about outsourcing labor.
But AI's more interesting opportunity in healthcare may be cognitive
offloading.
Not:
“Let the machine replace the person.”
But:
“Let the machine carry some of the mental load.”
That is different.
A physician should not have to remember every payer rule.
A biller should not have to manually rediscover every denial
pattern.
A clinic manager should not have to monitor every workflow
manually.
A nurse should not have to become an insurance detective.
The human still makes the important decision.
The system helps prepare the ground.
That is where I see responsible AI becoming genuinely
useful.
The revenue cycle is a workflow, not a collection of
departments
Here is the model I use:
Patient
↓
Documentation
↓
Coding
↓
Claim
↓
Payer
↓
Denial
↓
Appeal
↓
Payment
↓
A/R
Most organizations manage these as separate functions.
Patients don't experience them separately.
Neither does the money.
Neither does the physician.
A documentation problem can become a coding problem.
A coding problem can become a denial.
A denial becomes A/R.
A/R becomes staff work.
Staff work becomes operational cost.
And eventually someone asks:
“Why are our physicians spending so much time on
administration?”
Because the workflow is connected.
We just happen to manage it in pieces.
The three questions I would ask every clinic owner
If I walked into a small medical practice tomorrow, I would
not ask:
“What AI platform are you using?”
I'd ask:
1. Where are you losing money?
Not theoretically.
Show me the actual data.
2. Where are your people wasting time?
Not where they say they are busy.
Where are they repeatedly doing work that could be
eliminated, simplified or automated?
3. Where does the physician get pulled into the workflow?
This one matters.
Every time a physician has to intervene in an administrative
process, ask:
Why?
Sometimes the answer will be legitimate.
Sometimes it will be embarrassing.
Three experts. Three uncomfortable lessons.
Christine Sinsky, MD: Fix the system
Christine Sinsky, MD, has spent years studying physician
work and burnout.
One of the most important ideas in this conversation is that
burnout is not simply an individual resilience problem.
It is deeply influenced by the environment in which
physicians work.
That should change how leaders respond.
If the workflow is broken, telling physicians to become more
resilient is like telling someone to exercise harder because the office chair
is broken.
It misses the point.
Fix the chair.
Then talk about exercise.
Kimberly S. Barnes, APRN, CNM: Trust matters
Barnes matters to this story because Martin chose her.
That choice says something.
When the caregiver becomes the patient, clinical competence
is not the only thing that matters.
Trust matters.
Familiarity matters.
Knowing that someone has your back matters.
Healthcare organizations sometimes try to manufacture
patient experience with surveys and scripts.
But trust is not manufactured by a script.
It is earned through relationships.
The lesson from Devin: Small acts are not small
Devin's role in Martin's story is easy to overlook.
A nurse decorated the room.
A nurse stayed close.
A nurse held her during a frightening moment.
None of this would make a hospital technology conference
keynote.
But the patient remembered it.
That should make us uncomfortable.
Because healthcare sometimes measures what is easy to count
and ignores what is easy to feel.
A human hand cannot be easily entered into a dashboard.
But a patient knows when it is there.
The statistics tell one story. Kourtney tells another.
The statistics tell us physician burnout is improving.
That's good.
The statistics also tell us administrative burden remains a
significant issue.
That's important.
The story of Kourtney Martin tells us something the numbers
cannot:
When you are vulnerable, the experience of care is
personal.
Put those together and we get a different definition of
healthcare innovation.
Not:
More technology.
Not:
More automation.
Not:
More data.
Instead:
Less unnecessary work between the human beings who need
each other.
That is a much harder problem.
It is also a much more interesting one.
A practical framework: Eliminate before you automate
Here is the framework I would recommend:
1. Eliminate
Ask:
Does this task need to exist?
If the answer is no, stop doing it.
Congratulations.
You just built your first automation.
Without buying anything.
2. Simplify
If the task must exist, make it easier.
Remove unnecessary steps.
Reduce handoffs.
Standardize information.
3. Standardize
Create a predictable process.
AI works better when workflows are understandable.
Humans do too.
4. Automate
Only now should you ask what software can do.
5. Measure
Did it actually improve the workflow?
If not, change it.
Or kill it.
That last part is important.
Healthcare needs more permission to kill bad workflows.
Don't automate chaos
This may be the most important warning in this article.
AI can make a bad process faster.
It cannot automatically make the process good.
If your workflow requires six unnecessary steps, adding AI
to step four does not solve the other five.
You have simply created a faster inefficient workflow.
That is why the sequence matters:
Eliminate → Simplify → Standardize → Automate → Measure.
Not:
Buy AI → announce AI → hope for ROI.
A 30-day experiment for your practice
You do not need a three-year transformation project.
Start with 30 days.
Days 1–7: Watch
Have staff document administrative interruptions.
Every time someone has to:
- re-enter
data
- search
for information
- call a
payer
- check
a portal
- correct
a claim
- chase
documentation
- explain
a denial
- escalate
something to the physician
Record it.
No judgment.
Just observe.
Days 8–14: Rank
Score each task on:
Frequency
Time
Frustration
Financial impact
The worst combination is high frequency + high time + high
frustration.
Start there.
Days 15–21: Redesign
Ask:
Can we eliminate it?
Can we simplify it?
Can someone else do it?
Can we standardize it?
Can software handle part of it?
Days 22–30: Test
Automate one small part.
Keep a human review step.
Measure the outcome.
Then decide.
That is innovation without the theater.
What should you measure?
Forget vanity metrics.
Measure:
Denial rate
Clean claim rate
Days in A/R
First-pass resolution
Appeal success
Rework
Staff hours
Physician administrative hours
Time to resolution
Revenue recovered
And one metric I wish more healthcare companies used:
Human hours returned.
If your system saves 500 hours, where did those hours go?
Did physicians spend them with patients?
Did staff handle more meaningful work?
Did someone stop taking work home?
Did your practice increase capacity?
Did patients get faster answers?
If the answer is yes, now we're talking.
The AI safety question nobody should skip
Before automating a workflow, ask:
What happens when the system is wrong?
That question is more important than:
“How accurate is the AI?”
Why?
Because accuracy without context is meaningless.
A 99% accurate system can still cause serious problems if
the 1% occurs in the wrong place.
So build:
Human review.
Escalation rules.
Audit trails.
Confidence thresholds.
Exception handling.
Monitoring.
Clear accountability.
AI should not become the new mysterious employee nobody
knows how to supervise.
Legal and compliance considerations
Medical billing is not a playground for improvisation.
AI systems handling healthcare information need appropriate
privacy and security safeguards.
Practices should consider:
HIPAA and protected health information
Business associate requirements where applicable
Data retention
Access controls
Auditability
Coding and billing compliance
Documentation requirements
Payer contracts and rules
Human accountability
Vendor agreements
Most importantly, never confuse:
“The AI suggested it”
with
“The practice is not responsible.”
Technology does not magically transfer accountability.
Healthcare organizations should obtain appropriate legal,
compliance and security advice for their specific use case.
Ethical considerations
There is another question beyond compliance.
Should we automate this?
That is an ethical question.
Suppose automation saves the practice money.
Great.
But does it make the patient's experience worse?
Does it create barriers?
Does it unfairly reject claims?
Does it hide errors?
Does it make it harder for staff to challenge an incorrect
recommendation?
Does it shift work onto patients?
Does it create a system that nobody can explain?
Efficiency is not automatically ethical.
A healthcare system can be extremely efficient at doing the
wrong thing.
The goal is responsible efficiency.
What I think healthcare gets wrong about AI
We keep asking AI to do increasingly complicated things.
Maybe we should first ask it to do simpler things extremely
well.
Find.
Classify.
Summarize.
Prioritize.
Recommend.
Prepare.
Route.
Monitor.
Then let a human decide.
That may sound less exciting.
But it is much closer to how trustworthy healthcare systems
should evolve.
What OnnX is trying to build
This is the problem that led me to build OnnX.
I am not interested in putting an AI chatbot on top of an
already complicated billing workflow and calling it transformation.
I am interested in something much more practical.
Can AI remove repetitive cognitive work from medical
billing while keeping humans in control?
Consider a denied claim.
Instead of:
Denial → human searches → human interprets → human hunts
for documentation → human decides → human prepares response
Imagine:
Denial → AI analyzes → AI identifies likely cause → AI
retrieves relevant information → AI recommends action → human approves →
workflow proceeds
That is the difference between an AI feature and an AI
workflow.
One answers questions.
The other helps move work forward.
Why small and midsize practices matter
Large health systems can throw people at administrative
problems.
Small practices cannot.
A five-physician practice cannot necessarily hire another
department every time a payer creates another administrative requirement.
The physician becomes the safety net.
The office manager becomes the safety net.
The biller becomes the safety net.
Eventually, everyone becomes the safety net.
That is not a scalable operating model.
For smaller practices, workflow automation is not
necessarily about replacing people.
It can be about making a small team capable of operating
like a much larger one.
That is where AI could become economically meaningful.
But here is the uncomfortable part
Sometimes the answer is not AI.
I want to say that clearly as someone building an AI
company.
If a process can be fixed with a policy change, fix the
policy.
If delegation solves it, delegate it.
If training solves it, train people.
If the task should not exist, eliminate it.
If a simple rule handles it, use the rule.
Only use AI when AI actually adds value.
Healthcare does not need another company telling it that
every problem requires artificial intelligence.
Sometimes the smartest algorithm is:
Stop doing that.
The future of healthcare AI may be surprisingly boring
I think the best healthcare AI may eventually become almost
invisible.
It won't announce itself.
It won't necessarily have a flashy interface.
It will quietly notice:
“This looks familiar.”
“This information is missing.”
“This claim resembles previous denials.”
“This account needs attention.”
“This task can wait.”
“This one cannot.”
“This requires a human.”
And then it will get out of the way.
That is important.
Because the ultimate goal of healthcare technology should
not be to make technology more visible.
It should make care more visible.
The patient should never have to know how complicated the
back office is
This is one of my favorite tests.
Imagine a patient sitting in an exam room.
They should not have to care about:
The clearinghouse.
The payer portal.
The denial queue.
The coding edit.
The A/R aging report.
The workflow exception.
The billing system.
They just want to know:
What is wrong with me?
What do we do next?
Will I be okay?
That's it.
And physicians should have more time to answer those
questions.
What if AI's greatest healthcare contribution is time?
We usually describe AI using capability.
What can it generate?
What can it predict?
What can it summarize?
What can it automate?
But maybe the most important metric is simpler:
What can it give back?
Five minutes.
Twenty minutes.
An hour.
An evening.
A weekend.
A little less cognitive noise.
A little more attention.
A little more patience.
A little more time to explain.
A little more time to listen.
A little more time to hold someone's hand.
That is not a small outcome.
That is healthcare.
The Kourtney Martin test
Here is the test I would use for any healthcare technology:
If Kourtney Martin were sitting in the exam room, would
this technology make her experience better?
Not theoretically.
Actually.
Would the physician have more time?
Would the nurse have more attention?
Would the patient receive clearer communication?
Would unnecessary administrative work disappear?
Would the system make someone feel less alone?
If yes, keep exploring it.
If not, perhaps we are solving the wrong problem.
Three myths worth killing
Myth #1: More technology means better healthcare.
No.
Better workflow means better healthcare.
Technology is one possible ingredient.
Not the recipe.
Myth #2: AI's goal should be replacing humans.
No.
The better goal is replacing unnecessary human work.
Those are very different things.
Myth #3: Billing is separate from patient care.
Absolutely not.
Billing affects staffing.
Staffing affects capacity.
Capacity affects access.
Administrative burden affects physicians.
Physician time affects patient care.
Everything connects.
The biggest opportunity may be hiding in plain sight
Healthcare has spent enormous amounts of energy trying to
improve the clinical encounter.
But what surrounds the clinical encounter?
A mountain of administrative work.
Before the patient enters:
Scheduling.
Eligibility.
Authorization.
Documentation.
After the patient leaves:
Coding.
Claims.
Denials.
Appeals.
A/R.
Follow-up.
The clinical encounter is only one part of the journey.
If we want truly human-centered healthcare, we have to
redesign the entire journey.
That includes the back office.
Especially the back office.
A physician entrepreneur's confession
I will admit something.
When I first started thinking about healthcare AI, it was
tempting to focus on the technology.
That's what entrepreneurs do.
We see a capability and immediately ask:
“What can we build?”
But healthcare forces you to ask a harder question:
“What should we build?”
And then an even harder one:
“Will anyone actually use it?”
That changed how I think about OnnX.
The goal is not to build something impressive.
The goal is to solve something painful.
There is a difference.
The best product may be the one nobody talks about
Imagine a clinic owner telling a friend:
“We bought this incredible AI platform.”
That's nice.
Now imagine saying:
“We don't spend three hours every Friday fixing the same
billing problems anymore.”
That is better.
The second statement is not sexy.
It is useful.
And usefulness compounds.
What I would tell every physician starting a practice
Do not wait until your practice is overwhelmed to map your
workflows.
Do it early.
Document who does what.
Measure where claims fail.
Track A/R.
Understand payer patterns.
Separate clinical judgment from administrative work.
Build escalation rules.
Standardize repetitive tasks.
And when technology can safely remove work, use it.
But keep asking:
Does this make the practice more human?
If the answer is no, rethink it.
What I would tell every clinic owner
Your billing workflow is not merely a finance function.
It is an operating system.
It affects:
Cash flow.
Staff workload.
Physician time.
Patient access.
Practice growth.
Retention.
Stress.
Treat it accordingly.
Do not wait for your A/R to become a crisis.
Do not wait for physicians to become exhausted.
Do not wait until your best employee quits because they
spend every Friday afternoon fixing the same problem.
Measure the workflow now.
What I would tell healthcare innovators
Stop selling AI.
Start selling outcomes.
Don't tell a physician:
“Our model has impressive reasoning capabilities.”
Tell them:
“We reduced denial-review time by 40%.”
Don't say:
“We have an intelligent agent.”
Say:
“Your staff no longer has to manually review these 300
routine cases.”
Don't say:
“We use generative AI.”
Say:
“Your physician spends less time on administrative work.”
The technology is interesting.
The outcome is the product.
Final Thoughts: Give the caregiver back
Kourtney B. Martin knew how healthcare worked.
Then she became the patient.
And when she needed reassurance, what mattered was not
another layer of technology.
It was another human being.
Kimberly S. Barnes was there.
Devin was there.
They gave Martin something healthcare cannot manufacture at
scale:
presence.
That story should make every healthcare leader pause.
Because we are building increasingly intelligent systems
while simultaneously asking whether physicians have enough time to be present
with patients.
That is backwards.
The question isn't whether AI can make healthcare more
technologically sophisticated.
It can.
The question is whether we will use it wisely.
Will we use AI to add another layer of complexity?
Or will we use it to remove complexity?
Will we automate people?
Or will we automate the work that prevents people from doing
what only people can do?
Will we chase productivity?
Or will we protect attention?
I know which future I want to build.
Less clicking.
Less chasing.
Less rework.
Less administrative noise.
And more time for the work that brought most of us into
healthcare in the first place.
Caring for people.
Get Involved
So here is my challenge to 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 politically correct answer.
Give me the task that makes you mutter something under your
breath when nobody is listening.
Tell me in the comments.
I want to know where the real friction is.
And if this perspective resonates with you, repost this
article and send it to another physician, practice leader or healthcare
innovator.
Maybe someone in your network is fighting the exact same
workflow you are.
Maybe they have already solved it.
Either way, the conversation is worth having.
Question the workflow.
Protect human attention.
Use AI where it actually helps.
The future of healthcare does not need to be less human.
It needs to be less unnecessarily difficult for humans.
About the Author
Dr. Daniel Cham is a physician, medical consultant
and healthcare entrepreneur whose work sits at the intersection of medical
technology, healthcare management, medical billing and AI-powered 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 work and improve revenue-cycle workflows.
His perspective is simple:
Technology should make healthcare easier to practice, not
harder.
Connect with Dr. Cham on LinkedIn to follow his work on
healthcare operations, AI, medical billing and practical innovation.
LinkedIn: linkedin.com/in/daniel-cham-md-669036285
Disclaimer
This article is intended for general educational and
informational purposes. It does not constitute medical, legal, regulatory,
compliance, financial or professional advice. Specific healthcare, billing,
technology and compliance decisions should be evaluated with appropriately
qualified professionals.
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References
Norton
Healthcare — “From caregiver to patient: A nurse midwife’s own birth story.”
The August 21, 2026 story about Kourtney B. Martin provides
the human-interest foundation for this article and describes her experience
moving from caregiver to patient.
American
Medical Association — Physician burnout data.
The AMA's 2026 reporting shows physician burnout declining
to 41.9%, while significant system and administrative challenges remain.
American
Medical Association — Prior authorization burden.
AMA survey findings illustrate the continuing administrative
burden associated with payer requirements and physicians' skepticism that
recent insurer reforms will meaningfully reduce the problem.
One Last Question
Maybe we have been measuring healthcare incorrectly.
We measure what gets billed.
What gets collected.
What gets documented.
What gets coded.
What gets denied.
What gets paid.
But perhaps we should also measure:
How much time did we give back?
How many minutes did a physician spend with a patient
instead of a payer portal?
How many hours did a nurse spend caring instead of chasing
paperwork?
How many evenings did a clinic owner get back?
How many interruptions disappeared?
How many moments of human connection became possible?
Those numbers may never fit neatly into a revenue-cycle
dashboard.
But patients notice them.
Physicians notice them.
Families notice them.
And perhaps that is the point.
The best healthcare technology may not be the technology
patients notice.
It may be the technology that quietly gives their
caregivers enough time to notice them.
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#PhysicianBurnout #AdministrativeBurden #RevenueCycleManagement
#MedicalPracticeManagement #HealthcareInnovation #HealthTech #AIinHealthcare
#PhysicianLeadership #ClinicOwners #HealthcareOperations #DigitalHealth
#PatientExperience #HumanCenteredHealthcare #MedicalTechnology
#PhysicianEntrepreneur #HealthcareLeadership #OnnX
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