Oracle’s “AI-Native” EHR: Why This Isn’t the Revolution Healthcare Needs
Let’s Declare Our Independence—from the EHRs That Broke American Medicine
For over a decade, electronic health record companies have promised to modernize care. What they delivered instead was bureaucracy, burnout, and a system optimized for billing, not healing. In chasing data compliance over clinical clarity, these platforms stripped the soul from the exam room and burdened clinicians with endless clicks and checkboxes.
EHRs didn’t just digitize medicine—they dehumanized it.
But hope is not lost. Independence is possible.
Today, we stand at the edge of a true paradigm shift. One where AI is not just an assistant layered on broken systems—but the core logic that redefines how care is delivered. Where we stop asking how to document faster and start asking if we even need to. Where technology finally serves medicine, not the other way around.
The revolution won’t come from retrofits or rebuilds. It will come from rethinking everything.
Let’s begin.
Read: Oracle Rebuilds Its EHR Infrastructure to Support AI-Native Workflows
First announced in October 2024, Oracle recently launched a rebuilt, browser-native, AI-enhanced EHR architecture. Headlines describe it as a “clean-sheet design,” with new capabilities like ambient documentation, automated workflows, and embedded AI agents. It’s Oracle’s most significant health-care product update since acquiring the medical records giant Cerner for $28 billion in 2022.
On paper, this may appear like a much needed major departure from legacy systems like Epic or Allscripts. Unfortunately, while the headlines focus on the how, I believe the real question we should be asking is why.
And that’s where this rebuild—though impressive—is still stuck in the past.
The Fallacy of a Faster Horse
When Henry Ford said, “If I had asked people what they wanted, they would have said faster horses,” he was describing a failure of imagination. That’s where Oracle’s “rebuild” lands today.
Yes, Cerner’s legacy systems needed an overhaul. Yes, moving to the cloud is long overdue. But if your infrastructure is still organized around the same assumptions that created provider burnout, skyrocketing admin costs, and workflow inefficiencies—then you haven’t rebuilt anything. You’ve just scaled a crippled paradigm that does not work.
This is not a rebuild. It’s a re-skin.
AI-Assist Is Not the Same as AI-Core
Most EHRs chasing AI are chasing what I call AI-Assist: smarter templates, ambient scribes, predictive orders, auto-generated ICD-10 suggestions.
These are valuable—but they’re patchwork. They don’t question the premise.
They still assume that we must document everything in real-time. That care must happen after dozens of clicks. That patients all want to talk on the phone. That workflows must be chained to administrative logic.
In contrast, what we at Nemedic are building is an AI-Core—a foundational shift where AI isn’t grafted on top of legacy workflows but is instead the engine that defines what workflows should even exist in the first place.
First Principles Thinking: The Only Way Out
In surgery and in systems design, first principles thinking demands we break down problems into their fundamental components and rebuild from there. For example:
- Instead of asking, “How can AI help document faster?”
- We ask, “Why do we need documentation in this step at all?”
From that lens, we design systems where:
- Documentation becomes post hoc and event-driven.
- Intake and triage are asynchronous, autonomous, and adaptive.
- AI alerts providers of care gaps before new patients arrive or schedule.
- Perioperative pathways are orchestrated without manual dashboards.
This is not automation for efficiency’s sake. It’s deconstruction for reinvention.
What This Unlocks for Healthcare
When AI becomes native—not assistive—everything changes:
- Getting Back To Care: We eliminate the cognitive tax of clicking, documenting, and double-checking to restore the agency that doctors have lost in the modern era of EHRs.
- Cost Reduction: By removing redundant layers of clerical processes, we reduce administrative overhead and reallocate resources where they matter—on care.
- Access & Accuracy: When AI can manage longitudinal data and automate follow-up, triage, and risk flagging, providers can serve more patients more effectively.
Scalable Excellence: Clinical judgment is amplified, not replaced—empowering the top doctors to deliver innovative care to the population at scale.
What Oracle’s Rebuild Gets Right—and Still Misses
Oracle is right about one thing: a clean break is needed. Epic, Cerner, and other legacy systems have built EHRs for reimbursement, not outcomes. Retrofitting them for AI is a losing battle.
But even Oracle’s new platform still aims to optimize old tasks—document faster, code better, bill cleaner.
The real win isn’t efficiency. It’s obsolescence.
Don’t just do it faster. Ask if it needs doing at all.
Final Thought: Let’s Rebuild Medicine, Not the Software That Broke It
AI is not a layer.
It’s a lens that forces us to rethink what it means to deliver care—from the first intake ping to post-op recovery. If we allow legacy logic to dictate AI’s role, we’ll miss the revolution entirely.
When would now be a good time to realize we don’t need AI to polish the EHR? Instead, we need AI to replace the logic that made it necessary in the first place.
Fire up! Let freedom ring!