Mickey and Declan Merrill’s rare-disease journey exposes a hard truth about progress: better technology matters, but timing, access, and the systems surrounding care matter, too.
“The status quo is immoral. It’s unacceptable.” — Dr.
Robert Wachter, professor and chair of medicine at UCSF, speaking about
the need to improve healthcare in an October 7, 2026, interview with the
Institute for Healthcare Improvement.
A family’s experience with Sanfilippo syndrome offers a
deeply human starting point for a provocative question facing modern
healthcare: Are we solving problems at their source, or becoming more efficient
at managing their consequences?
The family that makes us rethink progress
Molly Merrill and Don Merrill are raising three children:
Mickey, Declan, and Maya.
Their family has experienced something healthcare leaders
often discuss in abstract terms: the difference that timing can make.
Their daughter, Mickey Merrill, was diagnosed with
Sanfilippo syndrome at age three. The rare genetic disease progressively
damages the brain and body. As it advanced, Mickey lost abilities, including
speech and hearing, and her family faced increasingly demanding care needs.
Years later, their son, Declan Merrill, was diagnosed
early enough to receive experimental gene therapy as an infant.
Five years later, Declan attends kindergarten and
communicates through speech and sign language. His progress offers hope,
although he is not cured and the long-term effects of treatment remain
uncertain.
Their daughter, Maya Merrill, does not have the
condition.
For Molly and Don, Declan’s progress is a reason to
celebrate. But it cannot erase what Mickey has experienced or the fact that she
was not eligible for the same treatment.
Imagine living with two realities at once: watching one
child gain opportunities that were unavailable to another child in the same
family.
This is not a simple story about a medical miracle. It is a
story about progress, uncertainty, access, and the limits of what medicine can
currently offer.
The family has continued advocating for research and raising
awareness through the Save Mickey Association.
Their experience deserves attention on its own terms. A rare
genetic disease is not a billing problem, and a treatment eligibility decision
is not equivalent to an avoidable administrative error.
Yet their story raises a broader question for healthcare
leaders:
What if our next major improvement comes not from
managing more problems, but from eliminating the ones we can prevent?
That question matters to physicians, clinic owners, and
healthcare innovators.
Because while medicine cannot yet solve every disease,
medical practices still spend enormous amounts of time correcting incomplete
information, chasing claims, resolving avoidable errors, and navigating
fragmented administrative processes.
We cannot eliminate every obstacle. But we should stop
treating every obstacle as inevitable.
Healthcare's favorite productivity trick: Doing
unnecessary work faster
Healthcare has a complicated relationship with efficiency.
We celebrate faster documentation, faster claims processing,
faster authorization workflows, and faster administrative communication.
Speed is useful. Nobody wants to wait unnecessarily for an
authorization or a payment.
But speed alone is a poor definition of progress.
If a practice submits an incomplete claim in 30 seconds
instead of two minutes, it has become faster at creating a problem.
The problem now has a better turnaround time.
If a billing team processes denials more efficiently, that
can improve collections. But if many denials originate from preventable
information gaps, we should also ask why those gaps continue to exist.
If a physician finishes documentation faster at night, the
physician may be more productive. But perhaps the better question is why the
physician needs to spend the evening doing it at all.
There is a difference between automating work and
eliminating unnecessary work.
Automation improves how a task is performed. Process
improvement asks whether the task should be necessary in the first place.
Both matter. Confusing them can be expensive.
For a small physician-owned clinic, every hour spent on
administrative rework competes with something else: patient communication,
staff development, financial planning, or simply ending the workday at a
reasonable hour.
Small practices do not have endless departments waiting to
absorb problems. The same employee may handle scheduling, eligibility checks,
claim follow-up, and patient questions.
One missing detail can become a group project.
And sometimes the group project ends with the physician
being asked to provide the same information for the third time.
We should not automatically blame the people doing the work.
Sometimes payer requirements create legitimate complexity. Sometimes the
clinical record needs clarification. Sometimes an error is unavoidable.
But when the same problem repeatedly travels through the
same workflow, the process deserves scrutiny.
The best operational question is not always, “How can we
do this faster?” Sometimes it is, “Why are we doing this again?”
The hidden connection: Timing, information, and access
Mickey and Declan’s experiences differed in important ways
because the disease was identified at different times and the treatment had
eligibility limitations.
Early identification created an opportunity for Declan. It
did not erase Mickey’s needs or guarantee a cure.
This is not a story about one child deserving care more than
another. Both children deserve care.
It is a reminder that information is most valuable when
it arrives in time to influence a decision.
That principle has practical implications for clinic
operations.
An eligibility issue identified before an appointment may be
easier to address than one discovered after services are delivered.
An authorization requirement identified early may give a
practice more time to resolve questions before a planned service.
A missing documentation element detected before claim
submission may prevent an avoidable correction cycle.
These administrative examples are not equivalent to early
diagnosis of a progressive genetic disease. Their consequences differ
enormously.
The shared lesson is that late discovery can reduce the
options available to act.
For independent practices, better information at the right
moment can improve predictability, reduce rework, and help staff focus on
unresolved cases that genuinely require attention.
The objective is not perfect information in every
circumstance. Clinical care is complex, and some facts become available only
later.
The objective is to reduce preventable information gaps and
manage unavoidable exceptions more intelligently.
The numbers behind the administrative burden
The administrative challenge is measurable.
The American Medical Association's 2025 Prior Authorization
Physician Survey, reported in May 2026, found that:
- 95%
of surveyed physicians said prior authorization delays access to
necessary care.
- 92%
said prior authorization negatively affects clinical outcomes.
- 94%
said prior authorization contributes to physician burnout.
- Physicians
and their staff spend an average of 13 hours per week on prior
authorization.
- 79%
said patients sometimes abandon treatment because of authorization
challenges.
- 26%
reported that prior authorization had contributed to a serious adverse
event.
These are physician-reported survey findings. They are not
proof that every authorization delay causes harm, and they do not measure every
aspect of medical billing.
But they make one thing difficult to ignore: administrative
work can consume substantial time and may have consequences beyond the billing
department.
For independent clinics, the appropriate response is to
separate three categories:
External requirements: Rules and decisions imposed by
payers or regulators that the practice may not be able to change unilaterally.
Internal process failures: Duplicate entry, unclear
ownership, inconsistent checks, and avoidable handoff problems.
Information failures: Missing, inaccurate, or
inconsistent data that prevent the next step from being completed correctly.
The categories overlap, but distinguishing them matters. A
clinic cannot solve every external constraint, yet it can still improve the
parts of its process within its control.
Source: American
Medical Association — Prior Authorization Physician Survey
Three expert perspectives worth considering
1. Dr. Ricki Carroll: Recognize problems early
Dr. Ricki Carroll, a complex-care and palliative-care
pediatrician at Nemours Children's Hospital, discussed the Merrill family's
experience in the original reporting.
Rare diseases can involve complicated diagnostic journeys,
difficult treatment decisions, and considerable uncertainty. Early recognition
may create opportunities for intervention, although it cannot guarantee a
particular outcome.
For clinic operations, the practical lesson is to identify
recurring errors before they travel through the entire revenue cycle.
Do not wait for a denial to ask whether the required
information could have been captured or checked earlier.
Practical advice: Choose one recurring problem and
identify the earliest point at which the practice can reliably detect it.
2. Dr. Bobby Mukkamala: Promises need proof
Dr. Bobby Mukkamala, president of the American Medical
Association, has drawn attention to physician concerns about prior
authorization and the need for meaningful reform.
The AMA's 2026 reporting found that only one in three
surveyed physicians believed the latest insurer pledge would make a
meaningful difference.
This raises a question that applies to healthcare technology
as well as payer reform: How will we know whether the change actually worked?
A vendor may promise fewer denials. A practice may introduce
a checklist. A payer may announce a streamlined process.
None of those actions proves that the burden has decreased.
Practical advice: Establish a baseline before
changing a workflow. Then measure whether error rates, rework, turnaround time,
or patient-facing delays improve.
3. Dr. Atul Gawande: Make reliable action easier
Surgeon and writer Dr. Atul Gawande has explored how
checklists and structured processes can help professionals manage complexity
and reduce avoidable failures.
The underlying lesson is that expertise alone does not
guarantee consistency.
A practice may employ excellent clinicians and experienced
billing professionals while still relying on memory, informal handoffs, and
undocumented exceptions.
The answer is not to create a checklist for every imaginable
situation. It is to make important steps clear, consistent, and proportionate
to the risk.
Practical advice: Standardize recurring tasks where
doing so improves reliability, while preserving human judgment for cases that
require it.
These perspectives point toward a shared objective: identify
problems early, measure whether interventions work, and design processes that
make reliable action easier.
They are not endorsements of OnnX or any specific billing
product.
OnnX's working thesis: Billing starts before billing
At OnnX, our working thesis is that healthcare billing is
partly a data-quality problem, not just a tooling problem.
Billing platforms, clearinghouses, and revenue-cycle teams
play important roles. They help practices submit claims, track payments, manage
denials, and navigate complex requirements.
But downstream systems depend on information created
upstream.
Consider a common example.
A patient receives care. The encounter is documented. Staff
prepare the claim. A required detail is missing or inconsistent. The claim is
rejected or denied. Someone investigates, contacts another staff member,
corrects the information, resubmits the claim, and checks again.
A downstream tool may make that correction faster. That can
be valuable.
But the more fundamental question is whether the required
information could have been captured accurately at the beginning.
This is where workflow design and technology should work
together.
A useful system should help people identify what is missing,
understand what happens next, and avoid unnecessary duplication.
It should not force clinicians to become billing specialists
or require staff to reconstruct an encounter from disconnected records.
Garbage in, beautifully summarized, is still garbage.
AI can organize information, summarize correspondence,
classify errors, and support routine workflows. But when source information is
inaccurate or incomplete, the output may also be inaccurate or incomplete.
In his October 7, 2026, interview with the Institute for
Healthcare Improvement, UCSF physician and researcher Dr. Robert Wachter warned
that AI's benefits depend on how these tools work in practice. He also
highlighted the risks of misinformation, bias, privacy failures, and
overreliance on automated outputs.
His point is particularly relevant to administrative
automation: deploying a tool is not the same as redesigning a workflow.
The real question is not whether AI can perform a task.
It is whether the tool helps prevent errors, reduces net
workload, and improves the final outcome.
Read: Dr.
Robert Wachter's interview with IHI
Seven practical steps to reduce unnecessary billing work
Step 1: Find your most expensive recurring problem
Review recent claim rejections, denials, corrections,
authorization delays, and unresolved accounts.
Group cases by cause rather than treating every case as
unique.
Look for problems that occur frequently, consume substantial
time, or create meaningful financial or patient-facing consequences.
Deliverable: A prioritized list of recurring failure
points.
Step 2: Find where the problem begins
Trace each problem backward.
Was information missing during registration? Was eligibility
checked? Was the documentation complete? Was authorization required? Did a
handoff fail? Was a payer requirement misunderstood?
The first visible error is not necessarily the original
cause.
Deliverable: A description of the likely root cause,
supported by case review.
Step 3: Define what must be known before proceeding
For each workflow, identify the information required at each
stage.
Assign responsibility for collecting, checking, and
escalating missing information.
Avoid introducing unnecessary checks that slow down the
process without reducing risk.
Deliverable: A practical workflow with clear
ownership and escalation criteria.
Step 4: Fix the process before automating it
Simplify the workflow where appropriate. Remove redundant
steps. Clarify responsibilities. Document legitimate exceptions.
Then assess whether automation can improve the process.
Automating a poorly designed workflow can make the same
mistake faster and more consistently.
Deliverable: A defined process ready for a controlled
pilot.
Step 5: Test one change at a time
Choose a limited intervention, such as a pre-submission
validation step or a clearer authorization queue.
Train staff, explain the intended outcome, and collect
feedback from the people doing the work.
Deliverable: A pilot with a baseline, an accountable
owner, and measurable success criteria.
Step 6: Measure the net effect
Track error rates, rework time, claim outcomes, and staff
workload.
Check whether the intervention eliminates work or merely
moves it elsewhere.
A faster front-end process that creates more back-end
corrections is not necessarily an improvement.
Deliverable: Evidence showing whether the change
improved the overall process.
Step 7: Keep what works
If the pilot succeeds, document the new process and monitor
its performance.
If it fails, investigate why. The problem may have been
incorrectly defined, the intervention may not address the cause, or the
workflow may have introduced a new bottleneck.
Do not defend a failed process simply because the practice
has already invested time or money in it.
Deliverable: A documented improvement plan based on
observed results.
The metrics that matter more than a busy dashboard
A dashboard can make a practice look busy. A good
measurement system helps determine whether it is getting better.
Consider tracking:
- First-pass
acceptance rate: How often are claims accepted without correction at
the initial submission stage?
- Denial
rate: What proportion of claims are denied, and for what reasons?
- Rework
hours: How much staff time is spent correcting avoidable errors and
locating missing information?
- Days
in accounts receivable: How long does it take to collect outstanding
balances?
- Authorization
turnaround time: How long does the process take, and where do delays
occur?
- Clean-claim
rate: How consistently are claims submitted with the required
information and without known correctable errors?
- Patient-facing
delays: How often do administrative issues contribute to rescheduling
or additional patient communication?
- Staff
experience: Are employees spending less time on repetitive
corrections, or has the new system created more monitoring work?
Define each metric consistently. Interpret it alongside
payer mix, service complexity, claim age, and compliance requirements.
No single number tells the entire story.
The goal is to measure meaningful improvement, not to
create an impressive dashboard.
Myth busters: Five assumptions healthcare should
challenge
Myth 1: More automation always means less work
Not necessarily. Automation may reduce repetitive tasks but
introduce exception handling, monitoring, and correction work.
Measure the net effect.
Myth 2: A submitted claim is a completed claim
Submission is one step in a longer process. Acceptance,
adjudication, payment, and reconciliation may still be outstanding.
Track the outcome, not just the action.
Myth 3: Billing problems belong entirely to the billing
department
Billing depends on information and decisions made across
scheduling, eligibility verification, clinical documentation, coding,
authorization, and payment processing.
Problems that cross departments require coordinated
solutions.
Myth 4: More software will fix poor data quality
Software can validate and organize information, but it
cannot reliably reconstruct every missing fact or replace professional
judgment.
Improve the information entering the process as well as the
tools handling it.
Myth 5: Efficiency is separate from patient care
Some administrative requirements are necessary. Others can
create avoidable delays and consume time that could otherwise support patients.
The goal is not to remove every administrative step. It is
to understand which steps protect quality and which create unnecessary
friction.
Recent news: What this week's healthcare stories reveal
Two recent reports offer useful perspectives on healthcare
innovation.
First, Spotlight Delaware published Julia Merola's
October 9, 2026, report on the Merrill family's experience with Sanfilippo
syndrome. Declan received experimental gene therapy as an infant after early
identification of the disease, while Mickey was not eligible for the same
treatment.
The story illustrates the possibilities and limitations of
medical progress. It also reminds us that innovation does not remove the need
for ongoing care, family support, or further research.
Read: Spotlight
Delaware — “All of the joy and grief”
Second, on October 7, 2026, the Institute for Healthcare
Improvement published an interview with Dr. Robert Wachter about AI in
healthcare. Wachter discussed administrative opportunities as well as risks
involving misinformation, bias, privacy, and overreliance on AI.
Read: IHI
— Dr. Robert Wachter on AI in healthcare
These stories concern different problems, but both challenge
simplistic definitions of progress.
A new treatment can offer hope without helping every
patient. A new technology can improve a workflow without eliminating every
failure.
The right response is neither cynicism nor uncritical
celebration. It is to ask who benefits, what remains unresolved, and how the
next improvement can be measured.
Legal, ethical, and practical considerations
Efficiency cannot come at the expense of accuracy, privacy,
or accountability.
Medical practices should assess their obligations involving
HIPAA, protected health information, business associate agreements where
applicable, access controls, audit logs, data retention, and vendor security
practices.
Claims must accurately reflect the services provided and the
supporting documentation. Automation should not invent clinical facts,
encourage unsupported coding, or replace appropriate professional judgment.
Payer requirements differ by plan, service, and
jurisdiction. Practices should maintain current procedures for eligibility,
authorization, claim corrections, appeals, and timely filing.
Before implementing a tool, evaluate its integration
requirements, total cost, staff training needs, limitations, and exit
arrangements. Understand who remains accountable when the vendor's system makes
an error or becomes unavailable.
Ethically, leaders should ask whether a change improves
access, distributes administrative burden fairly, preserves patient dignity,
and makes responsibilities clearer.
Patients should not have to navigate disconnected
departments indefinitely to understand what happened to an authorization or
claim.
Efficiency is valuable only when it supports reliable,
responsible care.
Tools and resources for independent practices
Improvement does not require a large technology budget.
Existing practice-management systems and clearinghouse
reports may already provide useful information about claim status, rejections,
and payments.
A spreadsheet can help categorize recurring problems,
provided patient information is handled securely and the tool is approved for
its intended use.
A simple workflow map can reveal duplicate steps and unclear
responsibilities. Standard operating procedures can make recurring work more
consistent.
Payer portals and official guidance can help staff verify
requirements. Qualified billing and compliance professionals can assist with
complicated cases.
AI-enabled tools may support classification, summarization,
work-queue prioritization, and identification of missing information. Their
value depends on data quality, integration, accuracy, and appropriate
oversight.
Before adopting a tool, ask five questions:
- What
problem does it solve?
- How
will we measure success?
- What
errors or risks could it introduce?
- Who is
accountable when it gets something wrong?
- What
happens if we decide to stop using it?
A tool should earn its place in the workflow through
demonstrated value, not simply an impressive feature list.
Future outlook: From managing problems to preventing them
Healthcare administration will not disappear. Clinical
complexity, payer requirements, documentation standards, and compliance
obligations will remain.
But the way practices manage these responsibilities can
improve.
Better information capture may help identify missing details
earlier. Targeted automation may help classify routine errors and prioritize
work. Improved integration may reduce duplicate entry and make it easier to
understand the status of an encounter.
These possibilities come with challenges. Systems need
appropriate validation, security, governance, and human oversight. Integration
can be expensive. Automation may fail when circumstances differ from the cases
it was designed to handle.
The most promising future is not one in which technology
replaces every person involved in healthcare administration.
It is one in which technology helps people spend less time
correcting avoidable mistakes and more time handling the situations that
genuinely require their judgment.
For independent practices, the opportunity is to make
operations more predictable without creating another layer of complexity.
That is the kind of progress worth measuring.
FAQs
What is the main lesson from Mickey and Declan Merrill's
story?
Their experience shows how timing, access, and medical
uncertainty can shape a family's experience. Declan's treatment offers hope,
but it does not erase Mickey's needs or guarantee a cure.
How does this story relate to medical billing?
The story is not about billing, and the two experiences
should not be equated. It provides a starting point for considering how timely
information and access affect outcomes. In practice operations, earlier
identification of missing information can help prevent avoidable rework.
What is upstream data quality in medical billing?
It refers to the accuracy and completeness of information
captured before downstream billing tasks begin. Better information at the
source can reduce some preventable errors, although it cannot eliminate every
denial or payer requirement.
Should independent clinics automate their billing
workflows?
They should evaluate automation when it addresses a clearly
defined problem. Establish a baseline, assess risks, involve staff, test the
tool, and measure whether it improves outcomes without creating additional
work.
Which metrics should a clinic monitor first?
Start with a specific problem. Depending on the practice,
useful measures may include first-pass acceptance, denial rate by cause, rework
hours, days in accounts receivable, and authorization turnaround time.
Can AI eliminate medical billing errors?
No tool can guarantee that all errors will disappear. AI may
help identify missing information, classify common problems, and organize
follow-up, but it can also make mistakes. Human oversight and accurate source
data remain important.
How can a small clinic begin improving its revenue cycle?
Choose one recurring problem, review recent cases, identify
the likely cause, test a targeted change, and measure the result. Avoid
changing several processes simultaneously before understanding what works.
Final thoughts: Stop celebrating busywork
Molly and Don Merrill's experience with Mickey and Declan
reminds us that medical progress can create hope while leaving painful
limitations unresolved.
Their story deserves attention on its own terms. It is about
a family navigating a rare disease, the promise of early treatment, and the
uncertainty that remains when medicine cannot offer every answer.
It should not be reduced to a business metaphor.
But it can remind us why timing, information, and access
matter in healthcare.
For physicians and clinic owners, the challenge is to apply
that thinking to the administrative systems within our reach.
Find the recurring failure. Understand where it begins. Test
a practical improvement. Measure the result. Keep the patient and the people
doing the work in view.
Three actions to take today:
First: Identify one administrative problem your
practice repeatedly fixes.
Second: Ask where it begins, rather than focusing
only on where it becomes visible.
Third: Test one change and measure whether it reduces
rework without compromising accuracy or care.
At OnnX, we are exploring how better data and more
thoughtful workflows can help small and medium-sized physician-owned practices
reduce unnecessary billing friction.
The question is bigger than any one product:
Are we making healthcare more efficient, or are we simply
getting better at managing inefficiency?
Continue the conversation
What is one recurring administrative task in your practice
that should be eliminated rather than automated?
Share your experience in the comments. Your insight may help
another physician or clinic owner identify a problem they have come to accept
as normal.
If this perspective resonates, consider reposting the
article to help more healthcare professionals rethink how billing and
operational design affect the practice of medicine.
Join the conversation. Challenge unnecessary complexity.
Help shape a healthcare system that gives people more time for what matters.
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References and further reading
1. A family's experience with a rare, progressive
disease. Julia Merola's October 9, 2026, report documents the Merrill
family's experience, including early treatment for Declan and the challenges
Mickey continues to face.
Read
the Spotlight Delaware report
2. Physician-reported prior authorization burden. The
American Medical Association summarizes survey findings on administrative
workload, patient access, and physician concerns about prior authorization
reform.
3. Expert perspective on AI and healthcare improvement.
Dr. Robert Wachter discusses administrative opportunities, risks, and the
importance of real-world implementation in this October 7, 2026, interview.
Read
the Institute for Healthcare Improvement interview
About the author
Dr. Daniel Cham is a physician and medical consultant
focused on healthcare technology, practice management, and medical billing.
Through his work on OnnX, an AI-powered medical billing SaaS for small and
medium-sized physician-owned clinics, he explores practical ways to reduce
administrative friction and improve the reliability of healthcare operations.
His work focuses on the intersection of clinical realities,
better data, responsible technology, and more effective practice management.
Connect on LinkedIn: Dr. Daniel Cham, MD
Disclaimer
This article is intended for general educational and
informational purposes. It does not constitute medical, legal, coding,
compliance, or reimbursement advice. Requirements vary by payer, jurisdiction,
and practice setting. Consult appropriately qualified professionals for
guidance specific to your circumstances.
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