Thursday, August 27, 2026

Kimberly Lynn Asked Her Nurse to Stay. Katie Schnautz Held Her Hand.

What if the biggest problem in healthcare isn't that we need more technology—but that we keep giving technology the wrong job?



“Ever-growing administrative burden that takes us away from the time with our patients…”American Medical Association

 

Kimberly Lynn went to Ascension St. Vincent in Evansville, Indiana, for what was supposed to be a routine EKG.

Then the day took a very different turn.

Her nurse, Katie Schnautz, realized something was wrong.

Lynn was frightened.

She asked Schnautz to stay.

So Schnautz held her hand.

Then Lynn's condition deteriorated and she suffered a heart attack.

More than a year later, Kimberly Lynn and Katie Schnautz reunited.

Lynn says that if Schnautz had not been there to help, she might not be alive today.

There is a lot to unpack in that tiny story.

But one detail keeps bothering me.

Kimberly Lynn did not remember the healthcare system.

She remembered Katie Schnautz.

She remembered that someone noticed.

Someone stayed.

Someone held her hand.

And that got me thinking about medical billing.

Yes.

Billing.

Because we have a strange habit in healthcare.

We call billing “back office.”

But billing touches the front desk.

The clinical workflow.

Documentation.

Coding.

Staff time.

Physician time.

Patient communication.

Cash flow.

And, eventually, the amount of attention a practice can afford to give its patients.

So perhaps the better question isn't:

“How do we make billing more efficient?”

It is:

“How much human attention are we losing because our administrative infrastructure is inefficient?”

That is a very different question.

And I think independent physicians should be asking it.


Here's my contrarian take

The healthcare industry has spent years trying to automate the work around physicians.

We should spend more time asking why so much of that work exists in the first place.

We have AI scribes.

AI coders.

AI denials.

AI prior authorization.

AI scheduling.

AI inbox assistants.

AI claim scrubbers.

AI everything.

At this rate, we may soon need AI to manage the AI.

And somewhere in the middle of all this automation, a physician is still sitting at home at 9:47 p.m. finishing administrative work.

That is not transformation.

That's just a very sophisticated version of the same headache.

The goal isn't:

More technology.

The goal is:

Less unnecessary work.


The question nobody asks about automation

Every healthcare technology company loves to say:

“Save time.”

Fine.

How much?

And then the more important question:

What happens to the time you saved?

If your billing software saves a physician 30 minutes, where did those 30 minutes go?

Another meeting?

Another inbox?

Another dashboard?

Another administrative task?

Or did the physician spend 30 more minutes actually talking to patients?

That distinction is everything.

Because time saved is not the same as time returned to care.


Kimberly Lynn gives us a better definition of ROI

We usually measure healthcare technology with:

Revenue.

Cost.

Claims.

Denials.

Throughput.

Productivity.

Utilization.

Those numbers matter.

But there is another return on investment that rarely appears on a dashboard:

Human attention.

What if we measured:

  • Minutes returned to physicians
  • Minutes returned to nurses
  • Preventable administrative tasks eliminated
  • Rework avoided
  • Patient questions resolved faster
  • After-hours work reduced
  • Staff interruptions eliminated

Suddenly, administrative efficiency becomes more than an accounting exercise.

It becomes a care-quality issue.


Because the billing department doesn't live in a basement anymore

For decades, we treated revenue cycle management like something that happens after medicine.

The patient comes in.

The doctor sees them.

Then, somewhere in the mysterious basement of healthcare, “billing” happens.

Except that's not how it works.

Billing starts much earlier.

At scheduling.

At registration.

At eligibility.

At authorization.

At documentation.

At charge capture.

At coding.

At claim creation.

The claim is simply where the consequences become visible.

By the time the claim gets denied, the original mistake may be days or weeks old.

That is why I believe:

Medical billing is often a data problem disguised as a billing problem.


The denial is not always the problem

Imagine this.

A claim gets denied.

The billing team investigates.

Someone opens the EHR.

Someone checks the payer portal.

Someone emails the physician.

The physician opens the chart.

Someone calls the payer.

Someone sends documentation.

The claim gets resubmitted.

Eventually, it gets paid.

Everyone celebrates.

But should we?

The claim got paid.

The workflow failed.

We just repaired it manually.

That is not the same thing.

A successful appeal can hide an unsuccessful system.

That may be one of the most expensive illusions in medical billing.


The better question

Instead of asking:

“How do we fix this denial?”

Ask:

“Why did the system allow this claim to reach the payer in this condition?”

That takes us upstream.

And upstream is where the real leverage lives.

If information can be validated before submission, why wait for a denial?

If eligibility can be confirmed earlier, why discover the problem after the visit?

If authorization requirements are known, why discover them after the procedure?

If documentation is missing something essential, why find out after the claim is rejected?

Fix the problem before it becomes a claim problem.

That sounds obvious.

Healthcare is surprisingly bad at doing it.


The physician burnout connection is not subtle

The AMA's latest data show that 41.9% of physicians reported at least one symptom of burnout in 2025. The organization also reports substantial variation by career stage, with burnout highest among physicians six to 10 years out of training at 48.8%.

And administrative work remains part of the story.

AMA data from 2024 found physicians reported an average 57.8-hour workweek, including 7.3 hours per week on administrative tasks. More than one in five physicians reported spending more than eight hours on the EHR outside normal work hours.

Those numbers should make every clinic owner pause.

Not because every administrative task is bad.

Some are necessary.

But because we have normalized an astonishing amount of work that physicians perform after the patient has gone home.

We call it “pajama time.”

Cute name.

Terrible operating model.


And CMS has basically put a price tag on the problem

CMS estimates that prior authorization work costs providers approximately $20–$50 per hour and consumes an average of 13 hours per week.

CMS estimates that this represents approximately 700 hours of administrative time per provider each year.

Seven hundred hours.

That is not a rounding error.

That is almost 18 forty-hour workweeks.

And the industry response has often been:

“Let's give someone another portal.”

Please.


The funniest thing about healthcare technology

Healthcare loves digital transformation.

We just don't always love removing the old process.

So we end up with:

EHR + fax.

Portal + fax.

AI + spreadsheet.

Automation + manual reconciliation.

Digital prior authorization + phone calls.

New dashboard + old workflow.

This is how healthcare gets a thousand times more digital and somehow still feels like 1998.

Digitizing a bad process does not make it a good process.

It makes it a digital bad process.


The real enemy isn't the billing professional

I want to be clear about this.

This is not an argument against medical billers.

Good billers are incredibly valuable.

They know payer rules.

They understand exceptions.

They catch errors.

They fight for revenue that practices have legitimately earned.

The problem isn't that humans are involved.

The problem is when highly skilled humans are forced to spend their day doing work that a well-designed system should have prevented.

That is waste.

And waste is expensive.


What I would automate

I would automate the predictable.

Eligibility verification.

Data validation.

Routine claim checks.

Pattern recognition.

Denial categorization.

Duplicate detection.

Exception prioritization.

Status monitoring.

Repetitive data entry.

Information routing.

The boring stuff.

Let machines be boring.

That's what they're good at.


What I would not automate blindly

Clinical judgment.

Patient conversations.

Complex exceptions.

Ethical decisions.

Ambiguous documentation.

High-stakes financial decisions.

Anything where the consequences of being wrong are significant and the reasoning cannot be meaningfully reviewed.

The future isn't:

Humans versus AI.

It is:

Humans doing human work. Machines doing machine work.

And, hopefully, fewer people doing work that nobody should be doing.


Three expert lessons healthcare leaders should pay attention to

1. AMA: Stop treating burnout as an individual resilience problem

Current AMA work continues to emphasize organizational and administrative contributors to physician burnout. The organization describes administrative burden as something that consumes time and focus, interrupts patient care, and contributes to burnout.

The lesson:

Don't give physicians a mindfulness app and a broken workflow.

Fix the workflow.

 

2. CMS: Administrative friction has a measurable economic cost

CMS's current electronic prior authorization work explicitly frames administrative burden as something that can be reduced through standardized electronic transactions. Certain CMS-regulated plans are scheduled to implement required APIs beginning January 1, 2027.

The lesson:

Administrative infrastructure is becoming a technology problem—and an interoperability problem.

 

3. AMA physician leaders: technology should create room for care

Recent AMA reporting on physician well-being highlights organizations using workflow redesign, team-based care, and technology to reduce administrative burden and cognitive load. Sutter Health, for example, has worked on reducing documentation burden so physicians can spend more time in personal interaction with patients.

The lesson:

The best technology doesn't demand attention. It gives attention back.


Here is the metric I want every clinic owner to consider

Forget one metric for a minute.

Ask:

How many minutes did we return to patient care this month?

Not:

“How many claims did we process?”

Not:

“How many AI tasks did we automate?”

Not:

“How many dashboards did we deploy?”

Ask:

How much human attention did we recover?

That's the metric that connects operations to medicine.


The Five-Minute Clinic Audit

If I were advising a physician-owned practice tomorrow, I would start here.

1. Follow one claim backward

Take a recent denial.

Don't start at the denial.

Start at the beginning.

Where was the information created?

Who entered it?

Who changed it?

Where did it move?

Where did it become incomplete?

Find the first failure.


2. Ask staff one uncomfortable question

“What do you do every week that makes absolutely no sense?”

Then listen.

Don't defend the process.

Don't explain why the payer requires it.

Just listen.

You may discover your best improvement opportunity in 10 minutes.


3. Count handoffs

Every time information moves from:

Person → person

System → system

Portal → spreadsheet

Spreadsheet → EHR

EHR → billing system

you have an opportunity for information loss.


4. Look for repeated manual corrections

If someone fixes the same type of problem every Tuesday, you don't have a “Tuesday problem.”

You have a system problem.


5. Measure physician involvement

Ask:

“Why did the physician have to touch this?”

That question is surprisingly powerful.


Three numbers I would watch

First-pass yield

How much work succeeds without human repair?

Higher is better.


Denial rate

But don't stop at the percentage.

Ask:

Why?

A denial rate without root-cause analysis is just a sad number.


Days in A/R

Money sitting in A/R is more than an accounting issue.

It affects the practice's ability to hire, invest, grow, and remain independent.


The metric I'd add

Preventable administrative hours.

How many hours are your employees spending fixing problems that could have been prevented upstream?

Now multiply that by loaded labor cost.

That is your hidden tax.

And if physicians are involved, the opportunity cost is even greater.


My favorite billing question

Here is the question I would ask every billing vendor:

“What work will disappear?”

Not:

“What features do you have?”

Not:

“Does it use AI?”

Not:

“How many integrations?”

Ask:

What work disappears?

If the answer is vague, be careful.


And one more question

Ask:

“What happens when your system is wrong?”

Every AI system is wrong sometimes.

Every rules engine encounters an exception.

Every integration breaks eventually.

A trustworthy healthcare platform needs:

Human review.

Auditability.

Clear accountability.

Appropriate security.

Escalation paths.

And transparency about uncertainty.

“AI said so” is not a governance strategy.


The legal side nobody wants to discuss

Automation does not magically transfer responsibility to software.

Practices still need to consider:

HIPAA

Business associate agreements

Data security

Access controls

Audit trails

Payer contracts

Coding rules

Documentation requirements

False Claims Act exposure

Fraud, waste, and abuse

State-specific requirements

AI governance

The exact legal requirements depend on the workflow and organization.

But the principle is universal:

If your name is on the claim, you still own the responsibility.

Software can assist.

Software cannot be your compliance officer.


The ethical question

There is also a question that doesn't fit neatly into a compliance checklist.

What are we optimizing for?

Revenue?

Speed?

Volume?

Patient access?

Clinical quality?

Trust?

If an algorithm increases collections by encouraging aggressive coding that isn't clinically supported, that's not innovation.

That's a problem.

If automation reduces staff workload but makes patients unable to understand their bills, that's not patient-centered.

If a system saves 20 minutes but creates 40 minutes of reconciliation work elsewhere, that's not efficiency.

Optimization without context is just faster movement in an unknown direction.


Myth: “Billing has nothing to do with patient care.”

Wrong.

It has indirect effects everywhere.

Administrative workload affects staff.

Staff workload affects workflow.

Workflow affects clinician time.

Clinician time affects the patient experience.

The connections aren't always visible.

They are real.

 

Myth: “The answer is more staff.”

Sometimes.

But if the workflow creates unnecessary work, adding people can simply mean paying more people to carry the same broken bucket.

Fix the bucket.

Then decide how many people you need.

 

Myth: “AI will eliminate the billing department.”

Probably not.

And that's not even the goal.

The better future is a smaller amount of repetitive work, with skilled people spending more time on exceptions, judgment, analysis, and patient-supporting operations.

 

Myth: “More automation is always better.”

Absolutely not.

Bad automation can scale mistakes.

The goal isn't maximum automation.

It's appropriate automation.


Where OnnX fits

This is the thinking behind OnnX.

I built OnnX around a simple idea:

Medical billing should be more predictable because the information entering the revenue cycle is better structured and the problems are identified earlier.

For small and medium-sized practices, that matters enormously.

You don't necessarily need another giant enterprise platform.

You need the existing pieces to work better together.

You need fewer unnecessary handoffs.

You need visibility.

You need early warnings.

You need fewer preventable errors.

And you need the billing process to stop behaving like a mystery novel where everyone discovers the ending after the claim is denied.


Why I don't think “AI-powered billing” is the best pitch

It sounds impressive.

But physicians don't wake up thinking:

“I wish my practice had more AI.”

They wake up thinking:

“Why is this claim still unpaid?”

“Why am I getting another authorization request?”

“Why am I fixing this again?”

“Why did I take work home?”

“Why does this require three systems?”

Solve those problems.

Then explain where AI helped.

Not the other way around.


The future belongs to invisible infrastructure

Think about electricity.

You don't want a sophisticated electricity dashboard.

You want the lights to turn on.

Think about plumbing.

You don't want to admire the pipes.

You want the water to work.

Healthcare technology should move in the same direction.

Invisible when it works.

Obvious when it doesn't.

That's what good infrastructure looks like.


What healthcare founders should learn from Katie Schnautz

There is an interesting lesson here for entrepreneurs.

Katie didn't create a complicated experience.

She did something simple at exactly the right moment.

She noticed.

She responded.

She stayed.

That is also what good product design should do.

Notice the problem.

Respond at the right moment.

Stay out of the user's way.

Maybe healthcare innovation doesn't always need to be more sophisticated.

Maybe it needs to be more attentive.


What physicians should demand from technology

Before buying another platform, ask five questions:

1. What problem does this actually solve?

2. What work disappears?

3. What errors does it prevent?

4. How much physician time does it return?

5. What happens when it is wrong?

If the vendor cannot answer these clearly, keep asking.


What clinic owners can do this week

You don't need a six-month transformation program.

Do this instead.

Monday

Pick one recurring billing problem.

Tuesday

Find 10 examples.

Wednesday

Identify where the problem first appeared.

Thursday

Remove one unnecessary handoff.

Friday

Measure what changed.

Then repeat.

Small improvements compound.

Especially in a small practice.


The uncomfortable truth about efficiency

Efficiency has become a dirty word in some parts of healthcare because it has sometimes been used to mean:

See more patients.

Do more with less.

Move faster.

Increase productivity.

That's not the only definition.

A better definition is:

Remove everything that prevents clinicians from doing excellent work.

That's a very different philosophy.


Kimberly Lynn's story brings us back to the point

A patient arrived expecting an EKG.

Instead, she experienced a heart attack.

She was afraid.

She asked Katie Schnautz to stay.

And Schnautz stayed.

More than a year later, the patient still remembered her.

That's the test.

Not whether the system was technologically sophisticated.

Whether, when the moment mattered, there was a human being available to respond.

Healthcare technology should help make those moments possible.

Not compete with them.


Final Thoughts: Maybe We Have Been Measuring the Wrong Thing

We measure claims.

We measure collections.

We measure productivity.

We measure utilization.

We measure clicks.

We measure denials.

We measure throughput.

But maybe we should also measure something much simpler:

How much time did we give back to people?

Because a physician with an extra 20 minutes may listen more carefully.

A nurse with an extra 15 minutes may notice something.

A staff member with an extra hour may solve a problem before it reaches a patient.

And a frightened patient may get something no algorithm can manufacture:

Someone who stays.

That is the kind of healthcare technology I want to build.

Not technology that makes humans less necessary.

Technology that makes human attention more available.


The Challenge

Physicians and clinic owners:

What is the most ridiculous administrative task you still have to do in your practice?

The one that makes you think:

“Why are we still doing this?”

Tell me in the comments.

I want to hear the real stories—not the polished vendor version.

And if this resonates with another physician or practice owner, repost this article.

Maybe the next useful healthcare innovation starts with someone finally saying:

“Why are we doing it this way?”

Then actually changing it.


Three Things to Remember

1. Fix problems upstream, not after the claim fails.

2. Measure time returned to patient care, not just tasks automated.

3. Build technology that protects human attention rather than competing for it.


About the Author

Dr. Daniel Cham is a physician, medical consultant, and healthcare entrepreneur focused on the intersection of medical technology, healthcare management, medical billing, and practice operations.

He is the founder of OnnX, an AI-powered medical billing platform focused on helping small and medium-sized medical practices reduce administrative friction and improve revenue-cycle performance.

His work focuses on a simple question:

How can technology make healthcare easier for the people actually delivering it?

Connect with Dr. Cham on LinkedIn:

Dr. Daniel Cham


Disclaimer

This article is intended for general educational and informational purposes. It does not constitute medical, legal, coding, compliance, reimbursement, or financial advice.

Healthcare regulations and payer requirements vary by jurisdiction, contract, specialty, and circumstance. Practices should consult appropriately qualified professionals for advice specific to their situation.


Continue the Conversation

The most useful healthcare conversations don't end with an article.

They continue in the clinic.

In the exam room.

At the billing desk.

In the product meeting.

And sometimes in the uncomfortable question:

“Why are we still doing this?”

I share practical perspectives on healthcare operations, medical technology, physician entrepreneurship, revenue-cycle management, and the future of medicine.

Explore more:

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If you're already on my profile, that's the easiest place to start.

Knowledge creates better questions. Better questions create better systems.


References

Kimberly Lynn and Katie Schnautz — patient/nurse reunion:
A current human-interest report from WEHT describes Kimberly Lynn's emergency after a routine EKG and her later reunion with nurse Katie Schnautz.
Read the story

CMS — electronic prior authorization:
CMS estimates prior authorization can require an average of 13 hours per week and is advancing standardized electronic workflows for certain plans beginning in 2027.
Read CMS guidance

AMA — physician burnout and administrative burden:
Current AMA data show burnout remains substantial while highlighting organizational, administrative, workflow, and EHR factors that influence physician well-being.
Explore AMA physician well-being resources


One Last Thought

The patient doesn't care how elegant your revenue cycle architecture is.

She cares whether someone is there when she is scared.

The physician doesn't need another dashboard.

The physician needs enough attention left at the end of the day to practice medicine well.

And the clinic doesn't need more technology for technology's sake.

It needs technology that quietly removes the work standing between people and care.

That is the standard we should demand.

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Kimberly Lynn Asked Her Nurse to Stay. Katie Schnautz Held Her Hand.

What if the biggest problem in healthcare isn't that we need more technology—but that we keep giving technology the wrong job? “Ever-g...