AI Scribes & Medical Records

In my previous posts on AI in healthcare, I focused on two recurring themes:

➡️ how people increasingly use LLM as a “replacement” for doctors, psychotherapists, or psychologists, and

➡️ why a large portion of health-related data sits outside HIPAA, creating a fragmented and often misleading privacy/security reality.

This time, the topic is closely related, but even more operational: AI scribes and medical documentation.

After reading “Medical records and AI scribes: Risk considerations” (Rachel V. R.), it’s clear that AI scribes can deliver real value (time savings, reduced clinician documentation burden), but they also raise governance questions that go far beyond “documentation quality.” They immediately trigger discussions about HIPAA scope, privacy by design, AI governance, and cybersecurity controls.

Link

Photo: Freepik

Unlike classic dictation tools, AI scribes may capture and transform sensitive clinical narratives into structured medical notes. That means they touch:

➡️ PHI,

➡️ special category data,

➡️ and the most sensitive part of the patient relationship.

This is exactly where my “HIPAA vs. beyond HIPAA” point becomes crucial again:

If the scribe is used by a covered entity and the vendor operates as a business associate with a proper BAA, the data can be inside the HIPAA ecosystem.

But if the tool is implemented through consumer-style AI services, unclear subcontracting chains, or “HIPAA-ready” marketing without true HIPAA governance, the reality can drift into a weaker protection model, even while the data looks like PHI.

What the article highlights

Integrity and accountability

The article points to expectations around accurate and complete medical records, proper authentication, and protection of integrity and security.

For AI scribes, this forces practical questions:

➡️ Who is the author? Who approves? How do we ensure traceability? How do we prevent silent edits?

Transparency

Beyond general consent requirements, AI scribes raise “next level” transparency issues:

➡️ Is the patient informed that AI is used? Is audio recorded? Where does it go? For how long? Who can access it?

Hallucinations

The article explicitly flags hallucinations and the potential for adverse outcomes and even billing risk.

Compliance

This is the part that aligns strongly with my earlier posts: in healthcare AI projects, the real risk is not only “legal.” It’s the combination of:

➡️ privacy compliance,

➡️ cybersecurity controls,

➡️ vendor chain governance,

➡️ operational monitoring.

If you want AI scribes, treat them as a regulated, high-impact system.

Author: Sebastian Burgemejster