The problem isn't always a lack of care. Sometimes it's what happens between the people who provide it.
“Redesigning workflows attacks the source of distress
instead of giving people skills to cope with it.” — Dr.
Liz Harry, Chief Well-Being Officer, Michigan Medicine, quoted by the
American Medical Association
Mark Andrew Collins was 26 years old when he finally
asked for help.
That sentence should bother every person who works in
healthcare.
Not because asking for help guarantees recovery.
It doesn't.
Not because every emergency department can solve addiction
in one visit.
It can't.
And not because Mark's story, by itself, proves that a
particular clinician or hospital caused his death.
It doesn't.
But because Mark did something healthcare constantly
tells patients to do.
He raised his hand.
He said, in effect:
I need help.
And then the system had to decide what happened next.
That is where this story becomes much bigger than addiction.
It becomes a story about handoffs.
And healthcare has a handoff problem.
Nine Days
Diane Santos had only nine days between learning
about her son's opioid addiction and finding him dead.
Nine days.
There were tears.
Confessions.
Phone calls.
And, importantly, hope.
Mark wanted treatment.
According to his mother, he wanted to stop using drugs. He
wanted to understand why he was using them. He had researched treatment and was
looking forward to getting help, including therapy.
He was not simply refusing care.
He was looking for it.
He had even secured an appointment for early January.
The problem was that January was still weeks away.
Then withdrawal became severe.
Diane asked whether he wanted to go to the emergency
department.
Eventually, he said yes.
They went to Backus Hospital in Norwich, Connecticut.
According to Santos' account, Mark told hospital staff that
he had used fentanyl that morning.
He was evaluated.
He was not admitted.
A recovery coach spoke with him and provided a number to
call the next day for treatment access.
Mark went home.
The next day, he called.
There was no immediate treatment available.
The plan was to keep trying.
The following morning, Diane went to wake her son.
His bedroom door was locked.
There was no answer.
She opened it.
Mark was on the floor.
He was cold.
He was gone.
He died on December 30, 2023, at age 26. His obituary
identifies him as Mark Andrew Collins and says he had asked for help overcoming
addiction.
The recent Connecticut reporting says his death occurred
roughly 36 hours after his emergency-department visit.
That timeline is devastating.
But there is something else about the story that deserves
attention.
The Most Dangerous Word in Healthcare
It may not be “denied.”
It may not be “delayed.”
It may not even be “error.”
It may be:
“Next.”
The patient goes to the next person.
The referral goes to the next department.
The authorization goes to the next queue.
The claim goes to the next system.
The denial goes to the next worklist.
The phone call goes to the next representative.
The patient waits.
The physician assumes someone else is handling it.
The staff member assumes the physician handled it.
The payer assumes the documentation was sufficient.
The practice assumes the payer received everything.
Everybody is busy.
Everybody is doing something.
And somehow, nobody owns the outcome.
That is the paradox of modern healthcare.
We have more specialists, more software, more portals, more
protocols, more dashboards, more data and more artificial intelligence than
ever.
Yet we can still lose a human being between two perfectly
documented steps.
A Referral Is Not Treatment
This is where Mark's story becomes uncomfortable.
A healthcare organization can truthfully say:
“We connected the patient with a recovery resource.”
That sounds like action.
But did the patient actually receive treatment?
Those are not the same thing.
A phone number is not treatment.
A referral is not treatment.
An appointment request is not treatment.
A portal message is not treatment.
A discharge instruction is not treatment.
A task placed into someone's queue is not treatment.
The outcome is what matters.
And this distinction is not unique to addiction.
Consider a patient with a suspicious imaging result.
The scan is completed.
The radiologist reports an abnormality.
The report enters the EHR.
The ordering physician is notified.
A message is generated.
The patient is told to follow up.
Everyone can point to a completed action.
But six months later, nobody can answer a simple question:
Did the patient actually receive the follow-up care?
That is a handoff failure.
Or consider a prior authorization.
The physician orders a medically necessary procedure.
The staff submits the authorization.
The payer requests additional documentation.
Someone assumes someone else responded.
The authorization expires.
The procedure is delayed.
Technically, the prior authorization workflow existed.
Operationally, it failed.
Healthcare loves confusing activity with completion.
We count tasks.
We should count outcomes.
And Then There Is Medical Billing
This is where the conversation becomes particularly
interesting for physicians.
Because the exact same structural problem exists in revenue
cycle management.
A patient receives care.
But the money doesn't automatically follow the care.
Why?
Because healthcare revenue is also a chain of handoffs.
Patient → registration → eligibility → encounter →
documentation → coding → claim → payer → adjudication → payment → posting →
reconciliation.
One broken connection can contaminate everything downstream.
And here is the uncomfortable part:
Most healthcare technology is designed to optimize
individual steps.
Better scheduling.
Better documentation.
Better coding.
Better clearinghouses.
Better denial management.
Better dashboards.
Better AI.
Better analytics.
Better portals.
But we keep asking:
“How do we make this step faster?”
The more important question is:
“Why did this information have to travel through six
disconnected steps in the first place?”
That's a different question.
And it leads to a different kind of healthcare technology.
Healthcare Has a Favorite Illusion
It is called workflow.
Healthcare organizations love workflows.
There is a workflow for registration.
A workflow for referrals.
A workflow for prior authorization.
A workflow for documentation.
A workflow for coding.
A workflow for claims.
A workflow for denials.
A workflow for appeals.
Soon we will probably have a workflow for managing the
workflows.
At some point, someone will build an AI agent to remind
another AI agent to check whether the first AI agent completed its task.
We will call it innovation.
And someone will put it on a conference stage.
The problem isn't that workflows are bad.
The problem is that we often automate fragmentation
instead of eliminating it.
Automation can make a broken process faster.
It can also make a broken process fail at scale.
The Contrarian View: AI Is Not the Solution to Bad Data
This is where the current AI conversation gets backward.
Healthcare is rushing to put AI everywhere.
AI coding.
AI clinical documentation.
AI prior authorization.
AI denial prediction.
AI scheduling.
AI patient messaging.
AI revenue-cycle management.
And yes, these tools can be useful.
But there is a fundamental problem.
AI cannot manufacture trustworthy context from missing
information.
If the underlying data is incomplete, ambiguous,
inconsistent or disconnected, the AI may simply produce a faster interpretation
of bad inputs.
Garbage in, garbage out is old.
The modern version is:
Garbage in, beautifully summarized.
That's progress of a sort.
But it isn't transformation.
The Real Problem Is Upstream
Suppose a physician documents:
“Patient presents with worsening symptoms. Continue
management.”
That sentence may be clinically understandable to the
physician.
But downstream, it may be remarkably unhelpful.
The coder needs specificity.
The billing system needs specificity.
The payer may need specificity.
The quality system may need specificity.
The next clinician may need specificity.
The patient may need specificity.
The problem didn't begin with the coder.
It began when the information was captured.
This is why I believe healthcare billing is fundamentally a data-quality
problem before it is a tooling problem.
The claim is simply the final expression of everything that
happened upstream.
If the information is incomplete at the point of capture,
somebody downstream will eventually pay for it.
Sometimes the cost is a denial.
Sometimes it is staff time.
Sometimes it is a delayed payment.
Sometimes it is an appeal.
Sometimes it is a frustrated patient.
And in clinical care, the consequences can be much more
serious.
The Five Handoffs Every Practice Should Audit
Forget the software demo for a moment.
Walk through the patient journey.
1. Patient → Front Desk
Did the practice capture the information correctly?
Or did someone type something quickly because the waiting
room was full?
Measure: registration accuracy.
2. Front Desk → Clinical Team
Did the clinical team receive the information that actually
matters?
Or did important context disappear between intake and the
exam room?
Measure: missing or corrected intake data.
3. Clinical Encounter → Documentation
Did the medical record accurately capture the service
delivered?
Not merely enough to close the note.
Enough to support the clinical, operational and financial
consequences of the encounter.
Measure: documentation completeness and charge lag.
4. Documentation → Claim
Did the structured information actually support the claim?
Or is the billing team reconstructing the encounter after
the fact?
Measure: first-pass yield, edits and preventable
denials.
5. Claim → Payment
Did the claim become money?
Or did it become another work queue?
Measure: clean-claim rate, denial rate, days in A/R
and avoidable rework.
The Billing Department Is Often Being Asked to Solve a
Problem It Didn't Create
This may be the most underappreciated issue in medical
billing.
A claim gets denied.
So what happens?
Someone blames billing.
The biller opens the chart.
Reads the note.
Looks for missing information.
Sends a message.
Waits.
Contacts the physician.
The physician modifies or clarifies documentation.
The claim gets corrected.
Then everyone celebrates.
The claim was fixed.
But was the system fixed?
No.
The system simply learned how to repair the damage.
That is reactive healthcare.
And reactive healthcare is expensive.
The Cheapest Denial Is the One That Never Exists
This sounds obvious.
It isn't how most organizations operate.
Many revenue-cycle teams are optimized around working
denials.
How many were received?
How quickly were they touched?
How many were appealed?
How many dollars were recovered?
Those are useful metrics.
But they measure the cost of failure.
A more interesting question is:
Why did the denial happen in the first place?
Was the patient's insurance information wrong?
Was eligibility checked too late?
Was the authorization missing?
Was the diagnosis insufficiently supported?
Was the procedure documentation incomplete?
Was the payer rule misunderstood?
Was the wrong payer pathway used?
Was information available in one system but invisible to
another?
The denial is the symptom.
The upstream data failure is the disease.
This Is Where Healthcare Gets Weird
Imagine an airline.
A passenger buys a ticket.
The airline checks the passenger.
The passenger boards.
The aircraft departs.
Then, after landing, someone discovers that the airline
never actually recorded where the passenger was supposed to go.
Nobody would say:
“Don't worry. We have a really sophisticated airport team
that specializes in finding passengers after they land.”
Yet healthcare routinely operates this way.
We build enormous departments to repair problems that should
have been prevented earlier.
Then we congratulate ourselves for recovering 80% of the
lost revenue.
That is not efficiency.
That's organized recovery from preventable confusion.
Mark's Story Forces a Bigger Question
Diane Santos has spent the years since her son's death
advocating for better treatment and sharing his story.
The recent reporting says she later returned to Backus
Hospital, where she found an emergency-department protocol for initiating
buprenorphine that she believed could have helped Mark. She brought the issue
to administrators and says changes were subsequently made.
That part of the story matters enormously.
Because it introduces a concept healthcare often struggles
with:
The protocol existed.
The question was whether the system reliably translated the
protocol into action.
That is a very different problem from not having a protocol.
And it is a problem that exists everywhere.
You can have:
- a
policy nobody follows,
- a
dashboard nobody checks,
- an
alert everyone ignores,
- a
referral nobody closes,
- a
claim nobody reconciles,
- a
denial nobody learns from,
- and an
AI tool nobody actually integrates into the workflow.
Healthcare doesn't merely need knowledge.
It needs execution.
Dr. Gail D'Onofrio's Point Is Bigger Than Addiction
Emergency physician and addiction-medicine expert Dr.
Gail D'Onofrio has argued for a more routine approach to initiating
treatment for opioid use disorder in emergency departments.
In the recent reporting, she described the need for a
standardized process involving medication, harm reduction and continued
treatment. She also acknowledged the complexity of emergency-department
operations and the reluctance to legislate clinical medicine.
That tension is important.
Because healthcare has two competing instincts.
Standardize everything.
And:
Don't turn medicine into a checklist.
Both instincts are reasonable.
The answer isn't to replace physicians with protocols.
The answer is to make the right clinical action easier to
execute reliably while preserving clinical judgment.
That distinction matters.
A protocol should support judgment.
It shouldn't replace it.
The Same Principle Applies to Billing
Imagine a physician sees a patient.
The practice already knows:
- who
the patient is,
- what
insurance they have,
- what
appointment they booked,
- why
they came,
- what
services are scheduled,
- what
authorizations are required,
- what
documentation is necessary,
- what
financial responsibility is expected.
Yet these facts often live in different systems.
So humans become the integration layer.
That's the hidden infrastructure of American healthcare.
People copying information from one box into another box.
And then we wonder why administrative costs are so high.
The Human API
Here is my favorite description of modern healthcare
administration:
The human API.
When two software systems don't communicate, a person does.
When the EHR doesn't talk to the billing system, someone
exports data.
When the payer portal doesn't integrate with the practice
workflow, someone logs in.
When documentation doesn't support coding, someone sends a
message.
When the claim is rejected, someone investigates.
When the referral isn't completed, someone calls.
When the patient doesn't understand the instructions,
someone explains them.
Humans are constantly acting as APIs between disconnected
systems.
And humans are expensive APIs.
More importantly:
Humans get tired.
Burnout Isn't Always a Physician Problem
We often talk about physician burnout as though the primary
cause is seeing too many patients.
Sometimes it is.
But there is another form of burnout that receives less
attention:
workflow absurdity.
The physician enters information.
The nurse re-enters information.
The front desk re-enters information.
The biller interprets information.
The payer requests the same information again.
The patient receives another form.
Then everyone asks why clinicians are exhausted.
Maybe the problem isn't that healthcare workers don't know
how to work hard.
Maybe they are working hard on things that should not
require human effort in the first place.
The Measurement Trap
Healthcare loves measuring productivity.
Patients per hour.
Claims per day.
Denials worked.
Calls answered.
Prior authorizations completed.
Notes closed.
Revenue collected.
But productivity can become dangerous when the measurement
ignores the system.
A billing employee can process 100 claims.
Wonderful.
But what if 30 of them require rework?
A staff member can complete 50 prior authorizations.
Wonderful.
But what if the process requires information that should
have been captured automatically?
A physician can close every note before leaving.
Wonderful.
But what if the documentation still fails downstream
requirements?
Speed without quality is just faster rework.
And rework is one of healthcare's least celebrated
industries.
What Should Physicians Measure Instead?
Start with five questions.
1. Where does information get re-entered?
Every manual re-entry is a potential failure point.
2. Where does responsibility become ambiguous?
If two people think the other person owns the task, nobody
owns the task.
3. Where does work leave the system?
Every external portal, fax, spreadsheet or phone call
deserves scrutiny.
4. Where are errors discovered?
The later the error appears, the more expensive it usually
becomes.
5. What percentage of work is preventive versus
corrective?
This may be the most revealing metric of all.
A mature organization doesn't simply become better at fixing
mistakes.
It becomes better at preventing the mistakes from being
created.
Three Myths Worth Killing
Myth #1: “We need more staff.”
Sometimes you do.
But adding people to a broken workflow can simply create a
larger broken workflow.
Before hiring, ask:
What work are we hiring humans to compensate for?
Myth #2: “We need better AI.”
Maybe.
But first ask:
Is the underlying information structured well enough for
AI to help?
If not, you may simply automate uncertainty.
Myth #3: “Our denial team is excellent.”
That's great.
But here's the contrarian question:
Why are you measuring how good your organization is at
cleaning up preventable mistakes instead of measuring how few mistakes it
creates?
The best denial is not the one recovered.
It's the one that never happened.
What a Better Practice Looks Like
A better practice does not necessarily have more software.
It has fewer gaps between systems.
The goal is simple:
Capture better information earlier.
Connect it.
Validate it.
Use it.
And prevent the same information from being repeatedly
recreated by different people.
For a physician practice, that means building a chain of
continuity:
Patient information → clinical context → documentation →
coding → claim → payer response → payment.
Each stage should inherit trustworthy information from the
stage before it.
Not a photocopy.
Not a reinterpretation.
Not a manual reconstruction.
Continuity.
The OnnX Thesis
This is the thinking behind what I'm building with OnnX.
I don't believe the future of medical billing is simply:
“Put AI on top of billing.”
That's too shallow.
The bigger opportunity is to move upstream.
Instead of waiting for the claim to fail, identify the
missing information before the claim exists.
Instead of asking a biller to interpret a fragmented chart,
structure the information closer to the point where it is created.
Instead of making humans the permanent bridge between
disconnected systems, make the systems communicate.
Instead of treating billing as a separate department, treat
it as the financial expression of the clinical and operational data generated
throughout the practice.
That changes the question.
From:
“How do we work more denials?”
to:
“Why did we create the denial?”
From:
“How do we automate billing?”
to:
“How do we make the revenue cycle more deterministic?”
From:
“How can AI replace administrative work?”
to:
“How can better data eliminate unnecessary administrative
work?”
That's a much more ambitious goal.
And, in my opinion, a much more useful one.
The Future Isn't More Automation
This may be the most contrarian prediction in this article.
The future of healthcare may not be about more automation.
It may be about less work.
Those are not the same thing.
Automation asks:
Can we make this task happen automatically?
Better system design asks:
Why does this task exist?
That distinction could save healthcare billions.
If a task is unnecessary, automating it is still waste.
If a handoff is unnecessary, automating the handoff is still
waste.
If a form exists only because two systems cannot
communicate, building an AI that fills out the form is still a workaround.
The ultimate automation is deleting the work.
And That Brings Us Back to Mark
Mark Andrew Collins is not a billing story.
He is not a technology case study.
He should not be reduced to a metaphor for software.
He was a 26-year-old man who wanted help.
His mother, Diane Santos, lost her son and then chose to
turn grief into advocacy.
That deserves to remain the center of the story.
But his story also forces healthcare leaders to ask a
difficult question:
What happens between “the patient needs help” and “the
patient actually receives help”?
Because that space between those two sentences is where
handoffs live.
And handoffs are where systems reveal themselves.
Dr. D'Onofrio's argument for making appropriate treatment
more routine in emergency care points toward the same principle: don't rely
entirely on heroic individuals to make a fragmented system work. Build
processes that reliably connect patients to the care they need.
The lesson extends far beyond addiction.
It applies to referrals.
Prior authorizations.
Test results.
Medication reconciliation.
Discharge planning.
Documentation.
Claims.
Payments.
And everything in between.
Healthcare's Most Expensive Employee May Be the Person
Who Keeps Fixing the Same Problem
Think about the person in your practice who everyone
considers indispensable.
They know which payer portal to use.
They know which physician forgets to document something.
They know which claims are likely to deny.
They know which fax number works.
They know which insurance representative actually answers
the phone.
They know the workaround.
They know the workaround for the workaround.
They are brilliant.
They are also a warning sign.
Because when one employee becomes the only person who knows
how to make the system work, the organization hasn't created resilience.
It has created institutional dependency.
The goal should not be to eliminate that person's value.
It should be to capture their knowledge and build it into
the system.
Otherwise, one vacation can become an operational event.
One resignation can become a crisis.
One missed handoff can become a patient-safety problem.
One bad data field can become a denial avalanche.
The Question Every Physician Should Ask
Not:
“Do we have enough staff?”
Not:
“Do we have an AI tool?”
Not:
“How many claims did we collect?”
Ask this instead:
“Where does responsibility disappear in our practice?”
Then follow the patient.
Follow the information.
Follow the money.
You may discover that the problem isn't one bad employee.
It isn't one bad payer.
It isn't one bad software platform.
It isn't even one bad process.
It is the space between processes.
That is where healthcare loses time.
That is where healthcare loses money.
And sometimes, as Mark Andrew Collins' story painfully
reminds us, that is where healthcare can lose something much more important.
A Final Provocation
We often say healthcare needs more compassion.
I agree.
But compassion without execution can become another form of
bureaucracy.
The system can care deeply.
The clinicians can care deeply.
The staff can care deeply.
The family can care deeply.
And the patient can still fall through the gap.
Good intentions don't close handoffs. Systems do.
That is why the future of healthcare shouldn't simply be
about adding intelligence.
It should be about creating continuity.
Continuity of information.
Continuity of responsibility.
Continuity of care.
Continuity of revenue.
And ultimately:
continuity between what healthcare promises and what
healthcare actually delivers.
Diane Santos has said that she continues to tell Mark's
story because she wants his life and death to make a difference.
That is perhaps the most important lesson of all.
A tragedy should not become content.
It should become accountability, learning and change.
Mark asked for help.
His story should make us ask whether our systems are
designed merely to respond to requests—
or actually to close the loop.
Because in healthcare, the difference between those two
things can be enormous.
And sometimes, it can be everything.
What This Means for Your Practice Monday Morning
Don't start with another software purchase.
Start with a whiteboard.
Write:
Patient → Front Desk → Clinical → Documentation → Coding
→ Claim → Payer → Payment
Then ask your team:
Where does information get lost?
Where does somebody re-enter it?
Where does someone wait for someone else?
Where do we discover errors too late?
Where are we paying people to repair problems that better
system design could prevent?
Then pick one handoff.
Fix it.
Measure the result.
Repeat.
That's how you move from reactive healthcare to
deterministic healthcare.
Not by buying another dashboard.
By removing another failure point.
FAQ
Is Mark Andrew Collins' story evidence that the hospital
caused his death?
No. Public reporting describes Santos' account of what
happened and the timeline surrounding Mark's death. That information alone does
not establish legal or medical causation. Any such conclusion would require
review of the complete clinical record and other evidence.
Why use an addiction story to discuss medical billing?
Because the underlying lesson is not addiction-specific.
It is about handoffs, continuity, ownership and
information integrity.
Those same structural problems appear in clinical care,
prior authorization, documentation, coding, claims and payment.
Is AI the answer?
AI can help, but only when the underlying workflow and data
are reliable.
The goal should not be to automate every broken task.
It should be to eliminate unnecessary work and make the
remaining work more reliable.
What should practices measure?
Start with:
- First-pass
yield
- Preventable
denial rate
- Charge
lag
- Days
in A/R
- Documentation
corrections
- Authorization
turnaround
- Manual
re-entry
- Rework
volume
- Exception
volume
- Percentage
of problems discovered upstream versus downstream
The most valuable metric may be:
How much work did we prevent from happening?
The Bigger Lesson
Healthcare doesn't have a shortage of intelligence.
It has a shortage of continuity.
We have brilliant physicians.
Dedicated nurses.
Exceptional billers.
Talented administrators.
Sophisticated software.
Powerful AI.
And enormous amounts of data.
Yet we still create systems where each component can work
perfectly while the overall patient journey fails.
That's the paradox.
Local optimization can create global dysfunction.
The front desk can be efficient.
The physician can be efficient.
The coder can be efficient.
The billing team can be efficient.
The payer can be efficient.
And the entire system can still be terrible.
Why?
Because healthcare isn't a collection of departments.
It's a chain.
And a chain doesn't become stronger because one link gets
smarter.
It becomes stronger when the links actually connect.
About the Author
Dr. Daniel Cham is a physician and medical consultant
with experience across medical technology, healthcare management and medical
billing. His work focuses on practical solutions to the operational problems
that sit at the intersection of clinical care, technology and healthcare
economics.
Through OnnX, he is exploring a different approach to
medical billing: improving the quality and continuity of information upstream
so that revenue-cycle problems can be prevented rather than endlessly repaired
downstream.
Connect with Dr. Cham on LinkedIn and follow his work across
healthcare technology, medical practice and operational strategy.
Continue the Conversation
Healthcare is changing quickly.
The people who understand the systems behind the change will
be better positioned to shape what comes next.
Knowledge drives progress. Start your journey here.
Explore more insights, conversations and healthcare
perspectives:
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Your Turn
Here's the question I want to leave you with:
Where does responsibility disappear inside your
healthcare organization?
Is it between the physician and the coder?
The patient and the referral?
The practice and the payer?
The clinical note and the claim?
Or somewhere nobody has thought to look yet?
Tell me in the comments.
If this perspective challenges how you think about
healthcare operations, share or repost this article and start the
conversation with another physician, practice owner or healthcare leader.
Because maybe the biggest healthcare problem isn't that we
don't have enough technology.
Maybe we've simply become very good at automating the
gaps between things that should have been connected in the first place.
Mark Andrew Collins asked for help.
His story reminds us that healthcare's job isn't finished
when we hand someone a phone number, close a task, submit a claim or move
something to the next queue.
The job is finished when the loop is closed.
References
- Cris
Villalonga-Vivoni, Connecticut Insider / CT Post — September 3, 2026
“CT man sought help for opioid addiction. His mom found him dead 36 hours later: ‘Now I’m his voice’”
This is the primary human-interest story behind the article. It documents Mark Andrew Collins’ attempt to seek treatment, his mother Diane Santos’ advocacy, and the broader questions surrounding emergency-department access to opioid-use-disorder treatment.
Read the Connecticut Insider story - American
Medical Association STEPS Forward — September 1, 2026
“Small Workflow Changes Can Make a Big Impact”
The AMA's current workflow-improvement discussion is highly relevant to the article's central argument: healthcare organizations can address friction by redesigning workflows rather than simply asking clinicians and staff to absorb more administrative burden.
Read the AMA STEPS Forward article - Medical
Group Management Association (MGMA) — September 2, 2026
“Fewer than 1 in 10 practices see faster prior auth turnarounds in 2026”
MGMA reports that 44% of medical-group leaders said prior-authorization turnaround was slower in 2026, while only 7% said it was faster. It also highlights the hidden work surrounding authorizations—status checks, documentation, peer-to-peer reviews, denials, appeals and multiple payer portals.
Read the MGMA report
#Healthcare #HealthcareLeadership #HealthcareInnovation
#PhysicianLeadership #HealthcareOperations #MedicalBilling
#RevenueCycleManagement #HealthcareTechnology #HealthTech #PatientSafety
#OpioidUseDisorder #AddictionMedicine #WorkflowDesign #HealthcareAI
#ClinicalOperations #PhysicianBurnout #MedicalPractice
#HealthcareTransformation #HealthEquity #OnnX
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