“Every system is perfectly designed to get the results it
gets.” — W. Edwards Deming (quality and systems thinking
pioneer)
Healthcare doesn’t fail because people stop caring. It
fails because systems assume caring is enough.
The IVF embryo mix-up made global headlines for one reason:
It feels unthinkable.
A couple gives birth to a child they believed was theirs.
Genetic testing reveals otherwise.
Another family realizes their embryo was implanted
elsewhere.
A custody agreement follows.
Lives permanently altered.
And the public reaction is always the same:
“How could this happen in modern medicine?”
But that question assumes something important:
That healthcare is supposed to be safe because it is
advanced.
That assumption is wrong.
The uncomfortable truth nobody wants to say
Healthcare is not a reliability-optimized industry.
It is a heroism-dependent industry.
It survives on three beliefs:
- Highly
trained people prevent catastrophic failure
- Attention
and vigilance are sufficient safeguards
- “Best
practice” reduces risk to near zero
None of these are structurally true.
They are cultural comfort stories.
And the IVF incident didn’t expose a rare failure.
It exposed a universal design flaw in healthcare systems.
Here’s the contrarian take
This is not an IVF problem.
This is not a fertility clinic problem.
This is a healthcare operating model problem.
Because the same structural weakness exists in:
- Revenue
cycle management
- Medical
billing workflows
- Prior
authorization pipelines
- Lab
specimen tracking
- Radiology
reporting loops
- EHR
documentation systems
- Referral
handoffs
Most physician practices don’t have fewer risks than IVF
clinics.
They just have less visible failures… for now.
The pattern nobody tracks: process debt
Healthcare talks constantly about clinical quality.
But almost never about process debt.
Process debt is what happens when:
- Workarounds
become standard practice
- Humans
become error correction layers
- Systems
depend on memory instead of structure
- “We’ve
always done it this way” replaces design
It accumulates silently.
Until it doesn’t.
Then it becomes:
- A
lawsuit
- A
denied claim spiral
- A
compliance audit failure
- A
patient safety event
- A
revenue collapse no one saw coming
The IVF case is simply process debt at maximum visibility.
Most clinics are operating with the same debt.
Just smaller consequences.
The billing system is not safe either (this is the
uncomfortable parallel)
If you are a physician-owner, consider this:
Your revenue cycle likely depends on:
- Manual
coding interpretation
- Staff
memory of payer rules
- Faxed
or fragmented documentation
- Delayed
eligibility verification
- External
clearinghouse logic you don’t control
- Human
follow-up on denial queues
Now ask a harder question:
If one person leaves tomorrow, what breaks?
If the answer is “a lot,” then you don’t have a billing
system.
You have a people-dependent financial assembly line.
That works… until it doesn’t.
Just like IVF labs assumed their chain-of-custody was “good
enough.”
The myth healthcare still believes
Myth: Safety comes from expertise.
Reality: Safety comes from design.
Expertise catches errors.
Design prevents them from happening.
And here is the uncomfortable gap:
Healthcare invests heavily in expertise.
It underinvests in error-proof systems.
What AI is getting wrong in healthcare right now
Everyone is racing toward AI:
- AI
scribes
- AI
coding
- AI
billing optimization
- AI
prior auth automation
But most of the conversation is shallow.
It focuses on:
- Efficiency
- Speed
- Cost
reduction
Not reliability.
Not system failure modes.
Not structural risk elimination.
So the real question is not:
“Can AI make healthcare faster?”
It is:
“Can AI make healthcare less dependent on fragile human
chains?”
Because speed without reliability is just accelerated
failure.
Expert insight #1 — James Reason (systems safety theory)
Most catastrophic errors occur when multiple small failures
align.
Healthcare tends to fix the last visible error.
High-reliability systems fix the structure that allowed it.
Expert insight #2 — Atul Gawande
Checklists don’t reduce intelligence.
They reduce reliance on memory under pressure.
That is the real point.
Expert insight #3 — Peter Pronovost
Safety improvements don’t come from more effort.
They come from better defaults.
Defaults beat vigilance.
Every time.
Statistics physicians should not ignore
- Medical
error remains a leading contributor to preventable harm globally
- Administrative
burden consumes a significant portion of physician time
- Revenue
cycle inefficiencies cost practices billions annually
- Denials
and documentation gaps remain a major financial leakage point in
outpatient medicine
But the most important statistic is not measured:
How many failures are quietly absorbed before they become
visible?
That number is always larger than reported harm.
Pitfalls in modern physician-owned practices
Most clinics fail in predictable ways:
- Over-reliance
on single staff members
- No
structured audit loops
- Reactive
denial management instead of prevention
- Lack
of real-time revenue visibility
- Fragmented
communication between clinical and billing systems
- No
system-level accountability for “silent errors”
These are not staffing problems.
They are architecture problems.
Insights most physicians underestimate
- Small
errors are not small
They are signals of structural weakness - Revenue
leakage is often invisible before it is significant
It accumulates like clinical risk - Most
“billing problems” are actually workflow design problems
- The
biggest threat to practice stability is not competition
It is internal fragility
Recent news lens (why this matters now)
The IVF incident is part of a broader shift:
Healthcare systems are under increasing scrutiny for:
- Chain-of-custody
failures
- Documentation
traceability gaps
- Liability
exposure from operational breakdowns
- Data
integrity across clinical workflows
At the same time, clinics are rapidly adopting AI tools
without redesigning underlying processes.
That combination is dangerous:
New tools on old systems do not reduce risk. They amplify
it.
Legal implications
When systems fail:
- Liability
often follows documentation gaps
- “Human
error” is not a legal shield
- Lack
of audit trails increases exposure
- Inadequate
workflow controls can be interpreted as negligence
In court, the question is rarely:
“What happened?”
It is:
“Was this preventable?”
Ethical considerations
Healthcare ethics increasingly extends beyond bedside care:
- Transparency
of systems
- Responsibility
for operational design
- Disclosure
of preventable failures
- Equity
in administrative burden
Ethical healthcare is not only about outcomes.
It is about how predictable failure is managed before
harm occurs.
Step-by-step: how physician clinics reduce structural
risk
- Map
every revenue and clinical workflow
- Identify
single points of failure
- Replace
memory-based steps with system triggers
- Build
audit trails for critical events
- Introduce
denial prevention, not just denial management
- Standardize
documentation inputs upstream
- Measure
near-misses, not just losses
Tools, metrics, and operational signals
Track:
- Denial
rate by category
- Time-to-resolution
for claims
- Missing
documentation frequency
- Rework
percentage in billing cycles
- Referral
leakage rate
- Staff
dependency concentration (who knows what)
If you cannot measure fragility, you cannot improve it.
Future outlook
Healthcare will split into two categories:
- Organizations
that digitized chaos
- Organizations
that redesigned it
AI will not fix the gap.
It will expose it.
The winners will not be the most automated clinics.
They will be the most operationally disciplined systems
with the least hidden dependency on human heroics.
Final Thoughts
The IVF embryo mix-up is not a story about fertility
medicine.
It is a story about healthcare’s structural blind spot:
We assume highly trained people can compensate for poorly
designed systems forever.
They cannot.
At some point, the system fails in a way that cannot be
quietly absorbed.
The question for physician-owners is not whether your clinic
is safe today.
It is:
Where are you currently relying on perfection without
realizing it?
That is where the real risk lives.
About the Author
Dr. Daniel Cham is a physician and medical consultant
specializing in healthcare technology, clinical operations, and medical billing
systems. He focuses on helping physician-owned practices improve financial and
operational performance through practical, systems-based thinking at the
intersection of medicine and technology.
Connect with Dr. Cham on LinkedIn to
learn more.
Disclaimer
This article is intended for informational and educational
purposes only and does not constitute medical, financial, or legal advice.
Readers should consult qualified professionals for guidance specific to their
clinical, operational, or legal circumstances.
Continue the Conversation
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Not when they accept defaults.
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Call to Action
What part of your practice depends on memory instead of
systems?
Drop a comment with one workflow you suspect is more fragile
than it should be.
Share this if you think healthcare needs fewer heroes and
more reliable systems.
♻️ Repost if this perspective
resonates and could help another physician rethink their practice operations.
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References
1. Patient Safety and
System Failure (Core Framework)
Reason, J. (2000). “Human error: models and management.”
BMJ
This foundational paper explains how errors in healthcare
are rarely caused by individuals alone, but by latent system failures
aligning across workflows (Swiss Cheese Model). It is widely used in
patient safety science and directly supports the idea that healthcare failures
are systemic, not personal.
2. Surgical Safety and
Checklist-Based Reliability
Gawande, A. et al. (2009). “A Surgical Safety Checklist
to Reduce Morbidity and Mortality in a Global Population.” New England Journal
of Medicine
This landmark WHO-supported study demonstrated that
structured system interventions (checklists, verification steps) significantly
reduce complications and deaths across global hospitals, reinforcing that design
beats memory and vigilance.
3. Healthcare
Quality and System Design Philosophy
Berwick, D. M. (1991–present body of work, Institute for
Healthcare Improvement)
Don Berwick’s work on healthcare quality emphasizes that most medical harm is not due to bad actors but poorly designed systems, and that improvement requires redesign of processes rather than blame-based approaches.
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