Heidi vs Lyrebird vs ChatGPT for Clinical Notes: An Australian Clinician's 2026 Comparison
A practical comparison of the three AI tools Australian clinicians are actually using — what each one is, where each one fits, and how AHPRA AI guidelines plus the Australian Privacy Principles change the picture.
Quick answer
Heidi vs Lyrebird:both are healthcare-purpose-built AI scribes with Australian data residency, and either is a defensible choice for AHPRA-registered clinicians. Heidi has the larger market position (Heidi's founders claim roughly half of Australian GPs as users) and broader workflow support across allied health. Lyrebird is leaner, focused on fast transcription, and well-suited to smaller practices.
ChatGPT for clinical notes is a different category — it is a general-purpose LLM, not a clinical scribe. It does not meet AHPRA AI guidelines or the Australian Privacy Principles for patient health information by default, and using it without explicit patient consent and significant workflow redesign is a Privacy Act risk.
The rest of this article walks through what each tool actually does, where they sit against AHPRA and NDIS scrutiny, and how to pick the right one for your scope of practice.
What is Heidi Health?
Heidi Health is an Australian-founded ambient AI medical scribe. It listens to the consultation in real time (with patient consent), generates structured clinical notes in the format the clinician wants, and integrates with the major Australian practice-management systems. Heidi's founders publicly state that the platform is used by approximately half of Australian general practitioners, and it has expanded across allied health, including physiotherapy, osteopathy, psychology and speech pathology.
What makes Heidi a healthcare-purpose-built tool (rather than a general LLM with a wrapper) is the combination of:
- Australian data residency. Patient audio and transcripts are processed on infrastructure that satisfies Australian Privacy Principles around offshore disclosure.
- Specialty-tuned templates. The note structure follows actual AU clinical conventions (SOAP, problem-orientated, NDIS-aligned, mental health care plans, etc.), not generic prose.
- Consent and audit trail features built into the workflow — important for AHPRA scrutiny and any future Medicare or NDIS audit.
What is Lyrebird Health?
Lyrebird Health is the other Australian-built AI scribe most commonly compared with Heidi. It is also an ambient transcription tool that records the consultation, produces structured notes, and stores data on Australian infrastructure. Lyrebird is smaller than Heidi by market position but well-regarded in solo and small-group practices.
Practitioners typically choose Lyrebird when they value:
- A leaner, faster workflow with fewer template-customisation knobs to learn.
- Lower price point for solo practitioners and small clinics.
- Direct transcript-to-notes output without the larger workflow surface area Heidi offers.
Both Heidi and Lyrebird sit in what we call Tier A in the course framework — healthcare-purpose-built tools with AU data residency, clinical templates, and consent/audit features baked in. Either is defensible against AHPRA AI guidelines.
Can I use ChatGPT for clinical notes?
The short answer: not without significant workflow redesign, explicit patient consent, and a real understanding of where the data goes.
Consumer ChatGPT (the free or Plus version most clinicians know) sends inputs to OpenAI's servers in the United States. Pasting any patient health information into that interface is an offshore disclosure of personal information under Australian Privacy Principle 8 — which is permitted only with the patient's explicit informed consent, or under a narrow set of exceptions that rarely apply in routine clinical work.
Beyond Privacy Act exposure, ChatGPT is a general-purpose LLM. It was not designed for clinical documentation, and several real-world failure modes follow:
- Template drift and recycled phrasing — outputs read as templated, which the NDIA has flagged in recent fraud-and-assurance work as a red flag for AI-generated NDIS reports.
- No consent or audit trail — you cannot demonstrate to an AHPRA investigator how the note was generated.
- No specialty templates — the output requires manual cleanup against clinical conventions every time, which often defeats the time-saving rationale.
ChatGPT (and Claude, and Gemini) can be used safely as a general-purpose tool for clinical writing — translation, patient information sheets, exercise programs — when the inputs are stripped of personal information. That is not the same as using it as a clinical scribe.
Side-by-side comparison
| Feature | Heidi | Lyrebird | ChatGPT (consumer) |
|---|---|---|---|
| Built for clinical use | Yes | Yes | No |
| AU data residency | Yes | Yes | No (US) |
| Privacy Act fit (default) | Compliant | Compliant | Requires explicit consent |
| Ambient transcription | Yes | Yes | No |
| Specialty templates (AU) | Extensive | Moderate | None (DIY) |
| Practice software integrations | Broad | Focused | None |
| Audit trail / consent log | Built-in | Built-in | None |
| Suitable for NDIS allied health reports | Yes (with workflow) | Yes (with workflow) | High audit risk |
| Tier (course framework) | A | A | C |
AHPRA AI guidelines and the Australian Privacy Principles
AHPRA has published guidance on meeting your professional obligations when using AI in healthcare, and the TGA has issued specific guidance on digital scribes. Indemnity insurers (Avant, MIPS, Guild, MIGA) have published their own checklists. The common themes:
- Patient consent is mandatory. Verbal consent at the start of the consult, documented in the notes. Heidi and Lyrebird build this into the workflow; with ChatGPT you have to build it yourself.
- The clinician remains responsible for the final note. AI-assisted does not mean AI-authored. You read, edit, and sign.
- Data location matters. Offshore processing of patient information is a notifiable disclosure under APP 8 without explicit consent.
- The note must reflect the clinical encounter. Templated AI output that recycles phrases across patients is a documentation-integrity problem and a flag for NDIS or Medicare audit.
Choosing a Tier A tool (Heidi or Lyrebird) handles items 1, 3, and 4 by design. You still own item 2 — reading and signing the note — no AI changes that.
Which one should you pick?
A practical decision tree:
- Solo practice or 2–3 clinician clinic, simpler workflow: Lyrebird is often a better fit.
- Larger practice, broad specialty mix, integration with existing practice-management software: Heidi's wider surface area pays off.
- NDIS-heavy allied health practice: Either Tier A tool works, but the audit-risk angle makes a structured workflow with audit logging essential. Either tool meets this; ChatGPT does not.
- Considering ChatGPT or Claude as your scribe: don't. Use them for non-PHI clinical writing tasks (patient info sheets, exercise programs in plain language) where you can strip identifiers, and use a Tier A tool for actual note-taking.
Want the full framework?
This article covers the headlines. Our short course AI in Clinical Practice walks through the AHPRA AI guidelines, Australian Privacy Principles, NDIS audit-safe documentation workflows, and the full Tier A/B/C framework with worked examples for physiotherapy, osteopathy, GP and naturopathy. 3 CPD hours, fully online, certificate on completion. Launching 17 June 2026.