Jill May stayed with one family through cancer’s hardest moments. Her story raises an uncomfortable question: why does the rest of healthcare make continuity so difficult?

“The value is not the AI itself. It is what people and organisations become capable of doing because of it.”— Tan Kiat How, Senior Minister of State for Health, Singapore

Richard Lee Streng was dying of liver cancer.

His wife, Kay Kroeff Streng, was trying to make sense of an increasingly complicated healthcare journey.

And in the middle of it stood Jill May, B.S.N., RN, OCN, an oncology nurse navigator at Allina Health Cancer Institute in Minneapolis, Minnesota.

Nobody could promise Richard—known as Rick—that cancer would disappear.

But Jill could promise something else.

“I’m not going anywhere.”

That sentence may be one of the most powerful descriptions of good healthcare I have encountered this year.

Because Jill did something healthcare is surprisingly bad at doing.

She stayed connected to the whole story.

Not just the appointment.

Not just the diagnosis.

Not just the procedure.

Not just the chart.

The story.

Rick’s story.

Kay’s story.

Their family’s story.

And that distinction matters far beyond oncology.

It reaches into primary care.

Specialty care.

Independent practices.

Revenue cycle management.

Physician burnout.

Medical billing.

And the future of healthcare technology.

Because patients experience healthcare as one continuous journey.

Healthcare organizations often experience it as a pile of disconnected transactions.

And somewhere between those two realities, things get lost.

Sometimes it is clinical context.

Sometimes it is a phone call.

Sometimes it is an authorization.

Sometimes it is a diagnosis.

Sometimes it is a claim.

Sometimes it is $10,000.

And sometimes, unfortunately, it is the patient.

The Story That Made Me Rethink Medical Billing

Kay Kroeff Streng’s account of Jill May’s care for Rick is not a billing story.

That is exactly why I think physicians and practice owners should read it.

Rick was diagnosed with liver cancer.

The timing could hardly have been worse.

The world was entering the COVID-19 pandemic.

Healthcare was becoming more complicated by the day.

Appointments changed.

Access changed.

Communication changed.

The family had questions.

Lots of them.

Cancer has a remarkable ability to turn a normal Tuesday into a graduate course in medicine, insurance, scheduling, terminology, uncertainty, and fear.

And most patients did not enroll voluntarily.

Rick and Kay were suddenly navigating specialists, imaging, treatment decisions, procedures, transplant possibilities, setbacks, and hospitalizations.

Then there was Jill.

She became a consistent point of contact.

She knew Rick.

She knew Kay.

She knew what had happened before.

And she knew what was supposed to happen next.

That sounds simple.

It isn’t.

In modern healthcare, continuity has become almost a luxury.

The patient may see one physician.

Another specialist.

A nurse.

A scheduler.

A hospitalist.

A radiologist.

A pharmacist.

A billing representative.

A payer representative.

A different nurse.

A different specialist.

And sometimes a different version of the same story at every stop.

The patient thinks:

“These are all people taking care of me.”

The system thinks:

“These are separate encounters.”

That is the first problem.

Then There Is the Other Healthcare Journey

Here is where I make a strange leap.

Stay with me.

The clinical journey is not the only journey happening.

There is another one running alongside it.

The financial journey.

Patient registration.

Eligibility.

Authorization.

Encounter.

Documentation.

Coding.

Charge capture.

Claim submission.

Adjudication.

Payment.

Denial.

Appeal.

Reconciliation.

Patient responsibility.

Most patients never see this machinery.

Physicians often wish they never had to.

But the practice lives inside it.

And when it breaks, somebody pays.

Sometimes the payer.

Sometimes the practice.

Sometimes the patient.

And very often:

the physician’s attention.

That is the hidden currency of healthcare.

Attention.

The Healthcare System Has a Memory Problem

Here’s my contrarian view:

Healthcare does not primarily suffer from a lack-of-data problem.

We have data everywhere.

We have EHRs.

Portals.

Claims.

Clearinghouses.

Eligibility systems.

Prior-authorization platforms.

Practice-management systems.

Dashboards.

Spreadsheets.

Emails.

Text messages.

Reports.

Analytics.

And enough passwords to make a physician question every life decision that led to medical school.

We don’t have too little information.

We have too little connected context.

That’s different.

Jill May did not become invaluable because she possessed one magical piece of information.

She became invaluable because she remembered the sequence.

She knew what came before.

She knew what changed.

She knew what mattered.

She knew who needed to know.

That is continuity.

And continuity is a form of intelligence.

Now Apply That to a Medical Claim

Imagine a patient receives a procedure.

The physician documents it.

The charge is generated.

The claim goes out.

The payer denies it.

The billing team opens the denial.

Someone researches the payer policy.

Someone checks the chart.

Someone looks at the authorization.

Someone checks the coding.

Someone calls somebody.

Someone sends an appeal.

Three weeks later, the claim is paid.

Everyone celebrates.

The claim is “resolved.”

But I have a question.

Why did it happen in the first place?

That question is more important than the appeal.

Because if the same denial happens again tomorrow, nothing was actually fixed.

The practice did not solve the problem.

It merely processed the consequence of the problem.

That’s a very expensive distinction.

The Industry’s Favorite Game: Whack-a-Denial

Healthcare has become remarkably good at chasing problems after they happen.

A claim is denied.

Work it.

A payer requests documentation.

Send it.

A claim is underpaid.

Appeal it.

An authorization is missing.

Fix it.

A patient balance is wrong.

Correct it.

Another denial appears.

Repeat.

It reminds me of the arcade game where you hit one plastic mole and another immediately pops up.

Except the healthcare version has:

• payer portals,
• spreadsheets,
• passwords,
• deadlines,
• fax machines,
• appeals,
• and a physician who just wants to finish clinic.

We call this revenue-cycle management.

Sometimes it feels more like revenue-cycle whack-a-mole.

And we should stop pretending that becoming better at whacking the moles is the same thing as fixing the machine.

The Contrarian Position

Here is the position I would defend:

The best revenue cycle is not the one with the best denial department.

It is the one that creates the fewest preventable denials.

That sounds obvious.

But healthcare often rewards the people who clean up the mess rather than the people who prevent it.

We measure collections.

We measure A/R.

We measure denial rates.

We measure clean claims.

All useful.

But many of these are lagging indicators.

They tell us what already happened.

What if we focused more aggressively on leading indicators?

What if the system could tell us:

“This payer has rejected this service three times under this documentation pattern.”

“This patient’s eligibility information has changed.”

“This procedure typically requires authorization.”

“This claim contains a combination historically associated with denial.”

“This physician’s claims for this payer have an unusual rejection pattern.”

“This documentation is incomplete before submission.”

That is a different philosophy.

It is the difference between:

managing failure

and

predicting failure.

Medicine Already Understands This

Think about preventive medicine.

We don’t wait for every patient to have a heart attack before checking blood pressure.

We don’t wait for diabetes to cause complications before monitoring glucose.

We don’t wait for every cancer to become metastatic before screening when appropriate.

Medicine learned something important:

Early detection changes outcomes.

Revenue cycle management should learn the same lesson.

Why wait for the claim to fail?

Why not identify the risk earlier?

Why should the billing team be the first line of defense?

Why not move the intelligence upstream?

That is where I believe the next generation of healthcare automation will be built.

The Numbers Are Getting Harder to Ignore

The problem isn’t theoretical.

The Medical Group Management Association has described continuing pressure from prior authorization, denials, Medicare Advantage requirements, quality reporting, and other administrative requirements affecting medical practices.

And the American Academy of Family Physicians has long highlighted the magnitude of administrative burden, noting that administrative tasks can consume approximately half of a family physician’s time, alongside substantial burnout among family physicians.

The AMA also describes revenue cycle management as a process spanning registration, benefit verification, care delivery, claims submission, and reimbursement.

That definition is important.

Because it quietly destroys one of healthcare’s most persistent myths.

Billing doesn’t start when the biller opens the claim.

It starts much earlier.

Your Billing Problem May Actually Be a Registration Problem

This is one of the first things I would investigate in a struggling practice.

Where do your errors begin?

Not where are they discovered.

Where do they begin?

Those are not necessarily the same place.

A denial may be discovered in billing.

But the root cause may be:

registration.

Scheduling.

Eligibility.

Authorization.

Documentation.

Coding.

Credentialing.

Payer configuration.

Workflow design.

Or some combination.

That’s why I don’t like the phrase:

“billing error.”

It is often too narrow.

Sometimes the biller is simply the person unlucky enough to discover a problem created three departments earlier.

Blaming the biller is like blaming the smoke detector for the fire.

The alarm is not the problem.

The fire is.

Three Experts. Three Lessons.

Jill May: Continuity Is a Clinical Asset

Jill May’s story demonstrates that continuity creates trust.

Kay Kroeff Streng’s account describes Jill’s commitment to both Rick and his caregiver through an extraordinarily difficult cancer journey. Allina Health also highlighted Jill’s nomination for a CURE Extraordinary Healer Award.

The lesson is bigger than oncology.

When someone knows the history, the next decision becomes easier.

That is true clinically.

It is also true operationally.

The AMA: Revenue Cycle Is Part of Practice Infrastructure

The AMA’s practice-management resources frame revenue cycle as a process that begins well before a claim is submitted.

That matters because physician owners often inherit RCM as something they are expected to monitor but rarely understand deeply.

My advice:

Don’t become a biller.

Become financially literate about your practice.

You should know where revenue is generated.

Where it slows.

Where it leaks.

And where your system depends on human heroics.

MGMA: Administrative Burden Is Not Just an Annoyance

MGMA’s reporting has repeatedly identified regulatory and administrative requirements as significant burdens on medical groups.

That changes how we should think about physician burnout.

If your physician is spending hours dealing with administrative friction, don’t automatically prescribe resilience.

Sometimes the better prescription is:

fix the workflow.

The Physician Owner’s Uncomfortable Question

Here’s a question I wish more physician owners asked:

“How much revenue are we losing because our practice does not know what it does not know?”

Not how much did we collect.

Not how many claims were submitted.

Not how many denials were worked.

How much did we never know was at risk?

That is a much harder question.

And potentially a much more valuable one.

Five Things I Would Audit Tomorrow

1. Your Top Five Denial Reasons

Not the entire denial report.

Just the top five.

Then ask:

What percentage could have been prevented?

2. Your A/R Aging

Look beyond the total.

Where is the money?

0–30 days?

31–60?

61–90?

Over 90?

Then ask why.

3. Payer Behavior

Do not treat all payers as identical.

Which payer creates the most:

delays?

denials?

underpayments?

authorization friction?

Patterns matter.

4. Physician Touches

Count how many times a physician has to intervene in the financial workflow.

That number may surprise you.

And every unnecessary physician touch should make you uncomfortable.

5. Rework

This may be the most revealing metric.

How much work is being done twice?

A claim corrected.

A form re-entered.

A document resent.

An authorization repeated.

A patient called again.

A denial appealed again.

Rework is invisible labor.

And invisible labor is still expensive.

The Biggest RCM Mistake?

Hiring another person.

I know.

That sounds ridiculous coming from someone who believes people matter.

People absolutely matter.

But if your process creates the same error 500 times, hiring another person to correct it 500 times is not transformation.

It is scaling the workaround.

Fix the workflow first.

Then staff it appropriately.

The Second Biggest RCM Mistake?

Outsourcing accountability.

Outsourcing billing can be smart.

Outsourcing expertise can be smart.

Outsourcing repetitive work can be smart.

But saying:

“Our billing company handles that.”

is not a strategy.

It’s an abdication.

Your billing partner should be able to answer:

What are our top denial causes?

Where is revenue being delayed?

What is our payer-specific performance?

What is preventable?

What is getting paid late?

What is being underpaid?

What requires physician intervention?

If nobody can answer those questions, you don’t have visibility.

You have a vendor.

There is a difference.

The AI Trap

Now let’s talk about AI.

Healthcare is currently fascinated with AI.

And honestly, I understand why.

AI can do impressive things.

But I think we’re asking the wrong question.

Everyone asks:

“What can AI automate?”

I think the better question is:

“What should humans never have had to do manually in the first place?”

That question changes everything.

If a staff member spends 30 minutes searching three payer portals to determine whether authorization was required, that’s not necessarily valuable human judgment.

If someone spends 20 minutes locating information that already exists in another system, that’s not clinical expertise.

If someone manually checks thousands of claims for a predictable pattern, perhaps the machine should help.

The objective isn’t:

AI everywhere.

The objective is:

human attention where it matters.

What OnnX Is Built Around

This is the thinking behind OnnX.

I don’t believe the future of medical billing is simply a faster version of today’s billing process.

I believe it should become more predictive, connected, and proactive.

Instead of waiting for the denial:

identify the risk.

Instead of discovering the underpayment months later:

surface the anomaly.

Instead of asking staff to remember every payer rule:

make the relevant information visible at the point of action.

Instead of forcing physicians to become billing specialists:

give them meaningful exceptions instead of administrative noise.

That’s the opportunity.

Not replacing humans.

Protecting human attention.

Here’s Where I Am Going to Challenge the AI Industry

If your AI requires physicians to learn another complicated dashboard, I have a question.

Who is actually being automated?

If your “automation” generates another inbox, another alert, another login, and another workflow, you haven’t reduced burden.

You’ve relocated it.

Healthcare does not need more digital junk.

It needs less friction.

The best technology should feel almost boring.

It should quietly say:

“I caught this before it became a problem.”

Then get out of the way.

The Jill May Test

Here is a test I would use for healthcare technology.

Ask:

Does this technology help preserve context?

Does it know what happened before?

Does it recognize what changed?

Does it connect the relevant people?

Does it reduce unnecessary handoffs?

Does it help someone act earlier?

Does it protect the human relationship?

If not, perhaps we’re just digitizing fragmentation.

And healthcare does not need a prettier version of fragmentation.

The Most Dangerous Phrase in Healthcare

“That’s just how the system works.”

I hate that sentence.

Because it usually means someone has become accustomed to an inefficient process.

Patients hear it.

Physicians hear it.

Nurses hear it.

Billers hear it.

Practice managers hear it.

Eventually everyone stops questioning it.

That’s how bad workflows become institutional tradition.

Faxing something three times?

That’s how the system works.

Calling the payer repeatedly?

That’s how the system works.

Waiting weeks for authorization?

That’s how the system works.

Fixing the same denial every month?

That’s how the system works.

No.

That’s how the current system works.

Those are not the same thing.

Myth Buster

Myth: “Billing happens after care.”

Reality: Financial consequences begin long before claim submission.

Myth: “A clean claim means we’re healthy.”

Reality: A claim can be clean and still be underpaid, delayed, or later recouped.

Myth: “Denial management equals revenue-cycle optimization.”

Reality: Denial management treats failure. Prevention addresses the cause.

Myth: “AI means fewer people.”

Reality: The better goal is fewer unnecessary tasks.

Myth: “Outsourcing means I don’t need to understand RCM.”

Reality: You don’t need to run the billing department. You do need to understand the financial health of your practice.

Myth: “Administrative work is just part of being a physician.”

Reality: Some administrative work is necessary. Some is simply inherited dysfunction.

A Seven-Step Revenue-Cycle Reset

Step 1: Measure

Pull your last 90 days.

Don’t guess.

Step 2: Categorize

Group denials and delays by root cause.

Step 3: Prioritize

Find the three problems causing the greatest financial or operational damage.

Step 4: Trace Upstream

Find where each problem began.

Not where it was discovered.

Step 5: Prevent

Change the workflow before the claim reaches the payer.

Step 6: Automate

Only after the workflow makes sense.

Do not automate chaos.

You’ll just get faster chaos.

Step 7: Re-measure

Did the problem actually decline?

If not, go back.

That’s process improvement.

Metrics Worth Watching

Physician owners don’t need 47 KPIs.

You need a handful that tell you what is happening.

Track:

Days in A/R

Denial rate

Clean-claim rate

Net collection rate

First-pass resolution

Payment velocity

Underpayment rate

Appeal overturn rate

Top denial categories

Preventable denial percentage

And one more:

Physician administrative touches.

Because a practice can technically improve its revenue while making its physicians miserable.

That’s not optimization.

That’s moving the pain around.

The Legal and Ethical Line

There is an important distinction between revenue optimization and revenue manipulation.

The objective should never be to manufacture reimbursement.

Never invent documentation.

Never upcode without support.

Never manipulate diagnoses.

Never create medical necessity that isn’t there.

Never allow an algorithm to become an excuse for poor clinical judgment.

The goal is much simpler:

Capture accurately what was legitimately delivered.

That’s it.

The financial system should reflect the clinical reality.

Not distort it.

Privacy Matters Too

Any technology touching patient information must be designed around appropriate privacy and security controls.

That means considering:

HIPAA

access controls

auditability

data minimization

vendor agreements

security monitoring

human oversight

appropriate AI governance

The fact that a machine can access information does not mean it should.

And the fact that automation is possible does not mean automation is appropriate.

What I Would Do If I Owned a Five-Physician Practice

I would not start by buying another giant platform.

I would start with a notebook.

Yes.

A notebook.

I’d write down:

Where did we lose money last month?

Then:

Why?

Then:

Could we have prevented it?

Then:

Who owns the fix?

Then:

How will we know if it worked?

Do that consistently and you will learn more about your practice than another thousand-page software brochure.

Technology comes after understanding.

The Future Isn’t Fully Automated Healthcare

I don’t think the future is a healthcare system where machines do everything.

That would be a terrible future.

I think the better future is one where machines handle more of the repetitive infrastructure so humans can spend more time on the things machines struggle to replace:

judgment

empathy

context

communication

relationships

trust

That is what Jill May provided.

She didn’t automate care.

She made care more connected.

That’s different.

And That Brings Me Back to Rick

Richard Lee Streng ultimately died.

Jill May could not change that.

No technology could.

No revenue-cycle platform could.

No AI model could.

That is precisely why his story matters.

Because healthcare is not successful only when the patient survives.

Sometimes success means helping someone live through something frightening with dignity.

Sometimes it means helping a spouse understand what is happening.

Sometimes it means recognizing a problem.

Sometimes it means making one phone call.

Sometimes it means holding someone’s hand.

Sometimes it means saying:

“I’m not going anywhere.”

Those are not things we should automate away.

They are things we should build better systems around.

The Real Opportunity in Healthcare Technology

The opportunity is not to replace the human being.

It is to remove everything that unnecessarily gets in the human being’s way.

That applies to clinical care.

It applies to nursing.

It applies to patient navigation.

And yes.

It applies to medical billing.

If a physician spends less time chasing a denial, there is more time for a patient.

If a nurse spends less time fighting an administrative system, there is more time for a family.

If a practice collects accurately and predictably, it can invest in people.

If staff spend less time on repetitive rework, they can spend more time solving meaningful problems.

That is what I think healthcare automation should mean.

Not fewer humans.

More human healthcare.

Final Thoughts

The most interesting lesson from Jill May and Richard Lee Streng isn’t about cancer.

It is about continuity.

Rick’s illness was complicated.

The healthcare system around him was complicated.

But Jill became a constant.

She knew the story.

She understood the context.

She helped connect the pieces.

And when the medical objective changed, she stayed.

That is what healthcare technology should aspire to do.

Not make the system more complicated.

Not give physicians another dashboard.

Not generate another alert.

Not create another login.

Connect the dots.

And when we talk about revenue cycle management, we should remember the same principle.

A claim isn’t just a claim.

Behind it is a patient encounter.

Behind that encounter is a physician.

Behind the physician is a practice.

Behind the practice are employees, families, and patients who depend on that practice remaining financially healthy.

So perhaps the real question isn’t:

“How do we collect more money?”

Maybe it is:

“How do we build a healthcare system where legitimate care is accurately recognized, paid for, and sustained—with as little unnecessary human friction as possible?”

That’s a much bigger question.

And I think it is worth asking.

Get Involved

If your practice lost 20% of its collectible revenue tomorrow, would you know exactly where the problem started—or would you simply discover it after the money was already gone?

I’d genuinely like to hear from physicians and clinic owners:

What is the one administrative or billing problem you have stopped questioning because you’ve been told, “That’s just how healthcare works”?

Share it in the comments.

And if this perspective made you think differently about the relationship between patient care, physician attention, and revenue cycle management, share or repost it so another physician-owner can join the conversation.

The future of healthcare will not be built by accepting broken workflows as inevitable.

It will be built by physicians and healthcare leaders willing to question them.

Start with one problem. Find the root cause. Fix what you can. Then keep going.

About the Author

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

He is the founder of OnnX, an AI-powered medical billing SaaS platform focused on helping small and medium-sized medical practices improve revenue-cycle visibility, identify preventable problems, reduce administrative friction, and spend less time managing fragmented billing workflows.

Dr. Cham writes about the practical intersection of medicine, technology, entrepreneurship, healthcare economics, and physician leadership.

Connect with Dr. Cham on LinkedIn for ongoing perspectives on medical billing, healthcare AI, practice operations, and the future of independent medicine.

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References

1. CURE — “The Impact of the Oncology Nurse Navigator on the Lives of Patient and Caregiver.”
Kay Kroeff Streng’s first-person account describes Jill May’s extraordinary continuity and support during Richard Streng’s cancer journey.

2. Allina Health — “Nurse Nominated for CURE Extraordinary Healer Award.”
Allina Health confirms Jill May’s role as an oncology nurse navigator and highlights Kay Kroeff Streng’s nomination recognizing her care.

3. Richard “Rick” Streng Obituary.
Richard Streng’s obituary confirms his identity, age, death on May 1, 2023, and three-year battle with liver cancer.

Disclaimer

This article is intended for general educational and informational purposes only. It does not constitute medical, legal, coding, compliance, financial, reimbursement, or professional advice. Healthcare organizations and professionals should obtain appropriate guidance for their individual circumstances, particularly when making decisions involving billing, coding, payer contracts, privacy, cybersecurity, artificial intelligence, or regulatory compliance.

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