What one Oakland patient’s long road to recovery reveals about the hidden connection between patient care, administrative friction, and the future of medical billing.
“The needs of the patient come first.” — Donald M.
Berwick, MD, MPP, is a physician and healthcare-quality expert, co-founder
of the Institute for Healthcare Improvement and former CMS administrator. His
work centers on patient safety, healthcare quality, and patient-centered care.
What if we have been thinking about medical billing
completely backwards?
On August 6, 2026, Kiara’ Darvonne Bowling was
walking a dog in Oakland.
She was 31.
She was finishing her J.D. at California State University
East Bay. She had recently returned from a summer program at Yale. She had also
recently been selected as Miss California Regency International 2026.
She was building a future.
Then a car struck her.
In seconds, the future she had been working toward became
uncertain.
Bowling suffered a brain bleed and multiple facial
fractures and was taken to Highland Hospital. Her family says she faces
multiple surgeries, extensive rehabilitation, transportation to appointments,
and potentially a lifelong recovery. (People)
There is a detail in this story that I cannot stop thinking
about.
The story does not end with the ambulance.
It does not end with surgery.
It does not end when the bleeding is controlled.
It does not even end when the patient leaves the hospital.
The real story begins afterward.
Physical therapy.
Specialists.
Follow-up care.
Prescriptions.
Transportation.
Insurance.
Authorizations.
Claims.
Bills.
Appeals.
Family members taking time away from work.
A patient trying to understand what happens next.
That is the part of healthcare we often hide behind the word
administrative.
And I think that word has become a problem.
Because some of the things we call administrative are
actually part of the patient's healthcare journey.
Here is my contrarian take
Medical billing is not merely a finance function.
It is a patient-continuity function.
That statement may make some healthcare executives
uncomfortable.
Good.
It should.
Because we have spent decades separating the clinical side
of medicine from the business side of medicine.
Clinical people care for patients.
Administrative people handle the paperwork.
Finance collects the money.
IT manages the systems.
Compliance watches the rules.
The payer processes the claim.
Everyone has a box.
But the patient has only one story.
And when those boxes do not communicate, the patient
experiences the consequences.
The patient sees a story. We see transactions.
This is one of the biggest problems in modern healthcare.
A physician sees a patient.
The EHR records an encounter.
A coder assigns codes.
A claim is created.
A clearinghouse transmits it.
A payer adjudicates it.
A remittance arrives.
An employee posts the payment.
A denial enters a work queue.
A bill goes to the patient.
The system calls this a successful transaction.
The patient experiences something very different.
“I was injured.”
“I needed care.”
“I am trying to recover.”
“Why is my treatment delayed?”
“Why did I receive this bill?”
“Why does my doctor say one thing and my insurance
company say another?”
“What happens next?”
That last question may be the most important one.
What if the biggest healthcare technology opportunity
isn't another clinical tool?
Healthcare innovation loves the visible problem.
Cancer.
Imaging.
Surgery.
Diagnostics.
Drug discovery.
Remote monitoring.
AI scribes.
Clinical decision support.
All important.
But there is another enormous layer underneath healthcare:
the administrative infrastructure that determines whether
the clinical work gets translated into sustainable care.
This layer is not glamorous.
It doesn't make headlines.
Nobody posts a dramatic product launch about correcting an
eligibility error.
But multiply one small error by 10,000 encounters.
Now you have a business problem.
Multiply it across thousands of practices.
Now you have a healthcare problem.
The uncomfortable question for physicians
Here is the question I would ask every physician-owner:
If your practice could not collect what it earned for 90
days, how long could you continue caring for patients?
Thirty days?
Sixty?
Ninety?
Longer?
The answer tells you something about your practice.
A medical practice is not financially healthy simply because
the physicians are busy.
It is not healthy because the waiting room is full.
It is not healthy because collections increased this month.
It is healthy when clinical work reliably becomes
sustainable operating cash.
That is not greed.
That is infrastructure.
A clinic that cannot pay its nurses cannot provide nursing
care.
A clinic that cannot retain staff cannot maintain
continuity.
A clinic that cannot invest in equipment eventually
compromises capacity.
A clinic drowning in administrative work has less attention
available for patients.
So let's stop pretending that financial operations are
somehow outside healthcare.
They are part of the machinery that keeps healthcare
available.
The story behind the claim
Think about a patient who needs months of rehabilitation.
The patient's clinical journey might look like this:
Emergency care.
Specialist evaluation.
Imaging.
Surgery.
Follow-up.
Physical therapy.
Primary care.
Medication management.
Rehabilitation.
Then another specialist.
Then another appointment.
The administrative journey is just as complicated.
Eligibility.
Authorization.
Claim submission.
Claim status.
Payment.
Denial.
Appeal.
Secondary insurance.
Patient responsibility.
It is one patient.
But the system may treat the journey as dozens of unrelated
transactions.
That is the disconnect.
Healthcare is longitudinal.
Billing systems are often transactional.
The opportunity is to connect them.
Recent News: Kiara’ Darvonne Bowling's story makes the
invisible visible
Bowling's story has received attention because the
circumstances were extraordinary and because the injuries were severe.
But the deeper reason it matters to healthcare professionals
is more ordinary.
Her recovery requires more than emergency medicine.
It requires a network.
It requires time.
It requires rehabilitation.
It requires transportation.
It requires financial resources.
It requires family support.
And it requires coordination.
Her family's fundraising effort specifically identifies
ongoing medical care, transportation, physical therapy, and possible future
surgeries among the needs associated with her recovery. (People)
That is the real patient journey.
And it raises a question:
Why does our healthcare infrastructure remain so good at
documenting encounters and so bad at preserving the entire story?
The first myth: “Billing is not patient care.”
I disagree.
Not because billing is clinical medicine.
It isn't.
But because the administrative system affects access,
continuity, staffing, and financial stability.
Imagine a prior authorization delays treatment.
Is that “just administration”?
Imagine an incorrect eligibility record forces a patient to
postpone an appointment.
Is that “just administration”?
Imagine a denial requires repeated calls and the treatment
is delayed.
Is that “just administration”?
Imagine a physician leaves independent practice because
administrative work has become economically unsustainable.
Is that “just administration”?
The label matters because labels influence priorities.
If we call something administrative, we may decide it can
wait.
Sometimes it cannot.
The second myth: “A clean claim means we are doing well.”
No.
A clean claim is a useful metric.
It is not a complete diagnosis of your revenue cycle.
A practice can have a strong clean-claim rate and still
suffer from:
Slow payment.
Underpayments.
Aging A/R.
Poor denial recovery.
Unworked claims.
Silent write-offs.
Secondary claims that are never filed.
Payer-specific friction.
High staff workload.
The question is not simply:
“Did the claim go out clean?”
The bigger question is:
“How reliably did clinical work become cash?”
The third myth: “We need more billing staff.”
Sometimes you do.
But first ask why.
If employees are repeatedly correcting the same problem,
adding more employees may simply increase the cost of inefficiency.
Suppose a practice repeatedly submits claims with an
eligibility problem.
One employee fixes it.
Another reviews it.
A biller resubmits it.
Someone checks the status.
Another person posts the eventual payment.
Five touches.
One preventable problem.
The industry calls this productivity.
I call it expensive repetition.
The better question is:
Why did the error reach the claim in the first place?
The fourth myth: “AI will solve RCM.”
No.
AI will solve some RCM problems.
It may also create new ones.
AI can identify patterns.
It can flag risk.
It can prioritize work.
It can automate repetitive tasks.
It can recognize anomalies.
It can help predict which claims deserve attention.
But AI cannot rescue bad processes simply because the
software is intelligent.
Bad data + sophisticated AI = sophisticated bad data.
That is why I believe the real opportunity is upstream.
My thesis: billing is a data-quality problem
This is the idea behind much of my work with OnnX.
Billing is often a data-quality problem before it becomes
a billing problem.
Think about the sequence.
The patient provides information.
The front desk enters it.
The clinician documents care.
The practice captures diagnoses and services.
The system creates the claim.
The claim is transmitted.
The payer evaluates it.
By the time the denial appears, the original mistake may be
several steps upstream.
Yet the practice often attacks the denial at the end.
That is expensive.
The closer you move prevention to the source, the cheaper
the correction usually becomes.
Prevent upstream.
Monitor continuously.
Escalate intelligently.
Recover selectively.
That is a better RCM philosophy.
The statistic physicians should pay attention to
The American Medical Association's 2025 physician survey
found that 95% of physicians said prior authorization delays access to
necessary care.
92% said prior authorization negatively affects
clinical outcomes.
79% reported that patients abandon treatment because
of authorization challenges.
And 26% said prior authorization had contributed to a
serious adverse event, including hospitalization, permanent impairment, or
death. (AMA)
Physicians and their staff reported spending an average of 13
hours each week dealing with prior authorization.
That is not a small administrative annoyance.
That is a workforce.
Another number worth knowing
The 2025 CAQH Index estimated that healthcare avoided
approximately $258 billion in administrative costs through electronic
transactions and improved data exchange.
But the same analysis identified another $21 billion in
potential savings from further automation of manual and partially manual
administrative transactions. (CAQH/GlobeNewswire)
That is the paradox.
Healthcare has automated enormous amounts.
And there is still enormous friction left.
So the question isn't:
“Does automation work?”
It clearly does.
The question is:
“Where should we automate next?”
Three expert perspectives
Don Berwick: the system exists for the patient
Berwick's work on healthcare quality repeatedly returns to a
simple principle:
Patients are not components of the system. The system
exists for them.
That sounds obvious.
But operational design often tells a different story.
When a staff member spends an hour correcting a preventable
billing error, who benefits?
When a physician spends an evening dealing with an insurance
issue, who benefits?
When a patient waits weeks because administrative work
failed, who benefits?
The patient should be the test.
Atul Gawande: technical success isn't the whole outcome
Gawande's writing frequently examines the gap between
medical capability and what people actually experience.
A technically successful procedure is not necessarily a
successful healthcare journey.
The patient still has to live afterward.
That is why continuity matters.
The procedure is an event.
Recovery is a process.
Healthcare systems are designed heavily around events.
Patients live through processes.
Danielle Ofri: don't automate away the human being
Ofri has written extensively about listening and the gap
between what patients say and what doctors hear.
That matters in the age of AI.
We should automate administrative friction.
We should not automate empathy.
We should not automate judgment where judgment is required.
We should not replace human conversation simply because a
machine can generate text.
Automate the repetitive. Protect the relational.
That should be one of the foundational principles of
healthcare AI.
The five-stage revenue cycle physicians should understand
Forget the complicated terminology for a moment.
Think about RCM as five stages.
1. Capture
Did we capture the right information?
2. Validate
Can we identify the problem before submission?
3. Submit
Did the claim leave correctly and on time?
4. Monitor
Do we know what happened afterward?
5. Recover
If something went wrong, are we acting intelligently?
Most traditional RCM systems become very active in stage
five.
I would rather spend more energy in stages one and two.
Because:
Recovery is expensive.
Prevention is cheaper.
The 30-day physician-owner challenge
You do not need a million-dollar consulting engagement to
start.
Try this.
Days 1–7: Find the leaks
Pull 90 days of data.
Look at:
Denial reasons.
A/R aging.
Payment delays.
Underpayments.
Write-offs.
Top payers.
High-value unpaid claims.
Don't fix anything yet.
Find the pattern.
Days 8–14: Rank the problems
Choose your top three.
Not ten.
Three.
Ask:
Which problem costs the most?
Which occurs most often?
Which is easiest to prevent?
Where do those three overlap?
That intersection is where you start.
Days 15–21: Remove human touches
For each recurring problem, ask:
Can eligibility be checked automatically?
Can the system flag missing information?
Can payer rules be applied before submission?
Can the claim be prioritized automatically?
Can payment variance be detected?
Can aging claims be escalated?
Can staff review exceptions instead of everything?
That is where technology should earn its place.
Days 22–30: Measure
Compare your baseline.
Did:
Denials fall?
A/R improve?
Payment time decrease?
Staff touches decrease?
Underpayments get recovered?
Cash improve?
If you cannot answer those questions, the project isn't
finished.
The seven metrics I would watch
Forget the dashboard with 47 boxes.
Start with seven.
1. Days in A/R
2. 90+ day A/R
3. Preventable denial rate
4. Net collection rate
5. Average time to payment
6. Underpayment variance
7. Human touches per claim
That last one deserves special attention.
Because it measures friction.
And friction is expensive.
The metric most dashboards miss
Human touches per claim.
Imagine two practices.
Practice A gets a claim paid after one automated
transaction.
Practice B gets the same claim paid after:
A phone call.
A correction.
A resubmission.
A status check.
A second follow-up.
A payment posting correction.
Both practices collected the money.
But they did not operate the same way.
One has a scalable system.
The other has a labor-intensive system.
Revenue alone will not show you the difference.
Touch count will.
Underpayments: the quiet leak
Everyone talks about denials.
Underpayments can be quieter.
A claim is paid.
The staff member posts it.
Everyone moves on.
But was the payment correct?
If expected reimbursement was $1,000 and the payer paid
$850, the claim technically got paid.
But $150 remains unexplained.
Multiply that across thousands of claims.
Now you have a revenue opportunity.
That is why payment integrity should sit beside
denial management.
The problem with “industry best practices”
Here's another contrarian point.
There is no universal best practice.
There are better practices for specific environments.
A dermatology practice is not a cardiology practice.
A solo physician is not a 300-provider group.
A Medicare-heavy practice is not the same as a commercially
insured practice.
A rural clinic is not the same as an urban specialty group.
So don't ask:
“What is the best RCM workflow?”
Ask:
“What workflow produces the best outcome for our
patients, our staff, our specialty, and our payer mix?”
Benchmarking is useful.
Copying is not.
What physicians should stop accepting
Stop accepting:
“That's just how insurance works.”
Stop accepting:
“Our billing company handles everything.”
Stop accepting:
“Our clean-claim rate is good.”
Stop accepting:
“We need more staff.”
Stop accepting:
“The payer denied it.”
Stop accepting:
“That's too small to worry about.”
Every one of those statements may be true.
But none of them explains the root cause.
The better question is always:
Why?
What physicians should start asking
Why did this claim fail?
Where did the error begin?
Could we have predicted it?
Could we have prevented it?
How many staff touches did it require?
How much did it cost to recover?
What happens if we multiply this by 10,000 claims?
Those questions change the conversation.
Legal implications: automation does not remove
responsibility
AI and automation make RCM more powerful.
They also create governance obligations.
Practices need to consider:
HIPAA.
Data security.
Business associate agreements.
Coding compliance.
Documentation integrity.
Medical necessity.
Payer contracts.
Overpayments.
False Claims Act exposure.
Improper billing.
Timely filing.
Credentialing.
Patient financial communications.
The principle is simple:
The software can automate the workflow. It cannot
automate accountability.
If an automated system makes a mistake, the practice still
needs to understand:
What happened.
Why it happened.
What data was used.
What action was taken.
Who reviewed it.
How the problem was corrected.
Ethical considerations
There is a line between optimizing revenue and optimizing
care.
It matters.
A system designed to improve reimbursement should never
become a system that encourages inappropriate clinical decisions.
The physician's clinical judgment must remain independent.
The goal should be:
Accurate care.
Accurate documentation.
Accurate coding.
Accurate reimbursement.
Not:
“Find every possible way to increase the bill.”
That distinction is foundational.
Another ethical question: where do the savings go?
Suppose automation saves a practice $150,000.
What happens next?
Do you reduce staff?
Increase physician capacity?
Improve benefits?
Expand patient access?
Invest in cybersecurity?
Lower patient costs?
Fund better clinical equipment?
There isn't one correct answer.
But there should be a conversation.
Efficiency should create capacity, not simply demand more
productivity from exhausted people.
Why I built OnnX
This is where my work as a physician and entrepreneur
intersects.
I did not build OnnX because I believe physicians need
another billing dashboard.
They don't.
They need fewer administrative headaches.
They need visibility.
They need earlier warnings.
They need cleaner workflows.
They need to know where revenue is at risk.
And they need technology that works with their practice
instead of creating another layer of work.
The philosophy behind OnnX is straightforward:
Identify the problem early.
Automate what is predictable.
Surface what requires attention.
Keep humans in the loop where judgment matters.
Give the practice control of its own revenue-cycle
intelligence.
That last point matters.
The physician should not have to ask a vendor:
“What is happening with my claims?”
The system should tell the practice.
Why eliminating middlemen is not really about eliminating
people
I use the phrase “eliminate middlemen” carefully.
Not every third-party billing company is bad.
Many are excellent.
The problem is opacity.
If the practice cannot see what is happening, cannot
understand why claims are failing, cannot measure performance, and cannot
easily access its operational data, it becomes dependent.
The goal should be operational independence.
That means the practice understands:
What happened.
Why.
What is at risk.
What needs attention.
What was recovered.
What remains unresolved.
Technology should make the practice more informed.
Not more dependent.
The future: predictive RCM
Traditional billing asks:
What went wrong?
The next generation should ask:
What is likely to go wrong?
Imagine knowing before submission that a claim has a high
probability of rejection.
Imagine knowing which payer behavior is changing.
Imagine identifying a documentation gap before it becomes a
denial.
Imagine detecting an unusual reimbursement pattern before
hundreds of claims are affected.
Imagine knowing which 20 claims deserve human attention this
morning.
That is where predictive RCM becomes interesting.
Not because prediction is perfect.
Because attention is limited.
But AI should know when it doesn't know
This is critical.
A good system should not pretend certainty.
A claim with high confidence can be automated.
A complex claim should be escalated.
A high-dollar claim may require human review.
An ambiguous case may need clinical context.
The architecture should be:
AI detects.
AI prioritizes.
AI explains.
Human decides when judgment matters.
That is safer.
And it is more useful.
The hidden lesson in Kiara’ Darvonne Bowling's story
Her story is not an RCM case study.
It should never be presented that way.
She is a person experiencing something painful and
profoundly uncertain.
But her story reminds us of something important.
A medical event is rarely a single event.
It is a chain.
And the chain continues long after the emergency room.
For Bowling, the next chapters involve recovery.
For other patients, it may be cancer treatment.
A transplant.
A chronic illness.
A new diagnosis.
A disability.
A rehabilitation program.
End-of-life care.
Whatever the condition, patients do not experience the
system one department at a time.
They experience it as life.
That is the standard healthcare technology should eventually
meet.
The biggest opportunity in healthcare may be invisible
We have become fascinated with what AI can generate.
Maybe the better question is:
What unnecessary work can AI make disappear?
A summary is useful.
A prediction is useful.
A generated note may be useful.
But if a physician still spends hours dealing with
preventable administrative problems, something is missing.
The greatest healthcare technology may be the technology
nobody notices.
The claim that never becomes a denial.
The authorization that never becomes a delay.
The payment discrepancy that gets caught automatically.
The aging account that gets addressed before it becomes a
crisis.
The staff member who goes home on time.
The physician who doesn't open the billing portal at 9:30
p.m.
Those are outcomes worth measuring.
A new definition of patient-centered care
Maybe patient-centered care should include more than the
exam room.
Maybe it should include:
The waiting room.
The referral.
The authorization.
The claim.
The bill.
The follow-up.
The recovery.
The transition home.
The patient doesn't care which department owns the problem.
They just want it solved.
That is the ultimate test.
FAQ
Is RCM really part of patient care?
Not clinically, but operationally it affects access,
continuity, staffing, and practice sustainability.
Should every practice adopt AI?
No.
Start with the problem.
Then determine whether automation is appropriate.
Is outsourcing RCM a mistake?
No.
It can be effective.
But maintain visibility, data ownership, performance
measurement, and accountability.
What should I measure first?
Start with A/R days, aging, preventable denials, payment
velocity, and human touches.
Is a 95% clean-claim rate good?
It may be.
But it tells only part of the story.
Look at what happens after submission.
Should every denial be appealed?
No.
Prioritize based on probability of recovery, dollar value,
effort, payer behavior, and filing limits.
Can AI replace billers?
The better question is which billing tasks should no longer
require manual work.
Human judgment remains important for exceptions and complex
cases.
What is the biggest RCM mistake?
Waiting until the denial.
The better strategy is identifying the problem before
submission.
How do I know whether an RCM technology investment
worked?
Establish a baseline.
Then measure changes in denials, A/R, payment speed,
staff touches, underpayments, and cash.
Myth Buster
Myth: Billing is finance's problem.
Reality: RCM crosses clinical documentation,
front-office operations, coding, billing, payer relations, technology, and
finance.
Myth: More billers fix bad RCM.
Reality: More people can increase capacity, but they
cannot automatically fix bad workflow.
Myth: AI eliminates the need for human oversight.
Reality: AI should reduce repetitive work while
escalating uncertainty.
Myth: Clean claims equal healthy cash flow.
Reality: Payment velocity, aging, underpayments, and
recoverability matter too.
Myth: Every denial is the payer's fault.
Reality: Many problems begin upstream.
Myth: Small-dollar discrepancies do not matter.
Reality: Small losses multiplied across thousands of
encounters can become substantial.
Tools, metrics, and resources
A practical RCM technology stack should include capabilities
for:
Eligibility verification
Authorization tracking
Claim validation
Claim-status monitoring
Denial analytics
Payment reconciliation
Underpayment detection
A/R aging
Payer performance
Workflow automation
Exception management
The tool is secondary.
The metric is primary.
If you cannot identify the metric you want to improve, you
probably are not ready to buy the tool.
Three resources worth reading
American Medical Association — Prior Authorization Survey
The AMA's latest physician survey provides current evidence on authorization
burden, delays, treatment abandonment, administrative workload, and patient
consequences.
Read
the AMA findings
2025 CAQH Index
The CAQH Index examines administrative transactions, automation,
interoperability, and remaining opportunities for efficiency.
Read
the CAQH Index findings
DataSpring Administrative Transaction Framework
DataSpring provides information about administrative healthcare transactions
including eligibility, authorization, claims, payment, and remittance
processes.
Explore
the framework
Three things I would do tomorrow morning
First: Pull your 90-day A/R and denial data.
Second: Identify the three largest preventable
sources of friction.
Third: Ask your team one question:
“Why are humans still doing this manually?”
That question may uncover more value than another software
demonstration.
Future Outlook
The next phase of medical billing will not be about creating
more sophisticated ways to chase money after something goes wrong.
It will be about preventing the problem.
The evolution looks something like this:
Reactive RCM
What went wrong?
↓
Automated RCM
Can software do the work?
↓
Predictive RCM
What is likely to go wrong?
↓
Preventive RCM
How do we stop the problem before it happens?
That is where healthcare should be heading.
And eventually, the best RCM system may become almost
invisible.
The physician documents.
The patient receives care.
The system validates.
The claim moves.
Exceptions surface.
Humans intervene where needed.
The payment arrives.
No drama.
No heroic billing recovery.
No midnight spreadsheet.
Just a healthcare system quietly working the way it should.
Final Thoughts: We are solving the wrong problem
downstream
Kiara’ Darvonne Bowling's story began with a terrible
moment.
But her story is not only about what happened on that
Oakland street.
It is about everything that comes afterward.
That is true for millions of patients.
And it is true for medical practices.
We cannot control every event that changes a patient's life.
But we can control how much friction we create after that
event.
We can build better workflows.
We can capture better information.
We can identify problems earlier.
We can automate repetitive work.
We can protect human judgment.
We can make practices financially stronger.
And we can remember why all of this matters.
There is a human being behind every claim.
There is a clinician behind every clinical decision.
And there is a practice behind every promise to keep
caring for patients tomorrow.
The goal of healthcare technology should not be to make
medicine more automated.
The goal should be to make medicine more human by
removing the work that never needed a human in the first place.
Get Involved — Start the Conversation
Here is the question I want to leave with physicians and
clinic owners:
What is one administrative task your practice still
performs manually that you believe should have disappeared years ago?
Tell me in the comments.
What is the biggest source of RCM friction in your
practice?
If you have solved it, share what worked.
If you have not solved it, share the problem.
Someone else may have already found an answer.
And if this article made you rethink the relationship
between patient care, administrative work, and revenue cycle management,
please repost it so more physicians and clinic owners can join the
conversation.
Raise your hand. Start the conversation.
Share what you are learning.
Help build a healthcare system where better operations
give clinicians more room to care.
Continue the Conversation
The healthcare conversation should not stop with the latest
headline.
I share practical perspectives on healthcare operations,
medical technology, medical billing, physician entrepreneurship, and innovation.
For deeper insights, practical strategies, and
behind-the-scenes perspectives on how healthcare is changing, continue the
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Free Resource
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About the Author
Dr. Daniel Cham is a physician, healthcare management
consultant, and entrepreneur focused on the intersection of medical
technology, healthcare operations, and medical billing.
As founder of OnnX, he focuses on practical
technology solutions designed to help small and medium-sized medical practices
reduce administrative friction, improve revenue-cycle visibility, identify
preventable problems, and spend less time navigating unnecessary billing complexity.
His perspective comes from working across clinical medicine,
healthcare operations, entrepreneurship, and medical technology.
His goal is straightforward:
Take complicated healthcare problems and turn them into
practical ideas physicians can actually use.
Connect with Dr. Cham on LinkedIn to
learn more.
Disclaimer
This article is intended for general educational and
informational purposes only. It should not be interpreted as medical,
legal, regulatory, coding, billing, compliance, financial, or other
professional advice.
Healthcare laws, payer policies, contractual
requirements, and individual practice circumstances vary. Readers should
consult appropriately qualified professionals for guidance concerning their
specific circumstances.
Information concerning Kiara’ Darvonne Bowling's accident
and recovery is based on publicly available reporting and may change as
additional information becomes available.
#Healthcare #HealthcareLeadership #PhysicianLeadership
#MedicalPractice #MedicalBilling #RevenueCycleManagement #RCM
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