About
Intelligent Mind Institute®
A structured, credentialled pathway for health professionals to build practical AI capability — designed for the clinical environment, delivered under Intelligent Mind® Pty Ltd.
What you leave with
Designed around outcomes, not exposure
Every session has a deliverable. By the end of the series, participants have a body of evidence — built from their own practice — that is ready for CPD portfolio submission or college audit.
A named framework you can teach as well as use.
The Diagnostic Prompt is the anchor method of this series — a structured approach that has participants let AI interrogate their thinking before asking it to act. Grounded in Socratic coaching methodology and the clinical parallel of structured history-taking. By the end of Week 1, participants have applied it to a genuine clinical problem from their own practice and recorded what it changed.
Working AI workflows — built, tested, and demonstrated.
Every self-directed session has participants build and test something in their own clinical environment. By the capstone, they have at least one no-code workflow automation running with real data — demonstrated live to peers, measured for impact, and documented as part of their CPD evidence package. Not a workshop handout. An actual output.
A specific, practical map of the Australian clinical AI environment.
Which tools work on locked-down hospital computers. Which require a personal device. What the Australian Privacy Principles and My Health Record obligations require. How to operate within — and advocate for — local AI governance frameworks. Participants leave with a clear, actionable picture of what they can actually deploy from the week they finish.
Programme Director
Dr Rajan Kailainathan
MBBS (Hons), FACEM, FRCEM, AFRACMA
I'm an emergency physician. I still work clinical shifts, and for a long time I was drowning in the same documentation and administrative burden that most of my colleagues are carrying right now.
I started using AI tools to solve real problems in my own practice — not out of curiosity, but out of necessity. What I found was that most clinicians who tried the same thing hit the same wall: the tools are capable, but nobody had shown them how to use them well for clinical work.
That's why I built this programme.
But documentation was just the start. I also use AI to audit clinical data at a scale that simply wasn't possible before. Health services accumulate years of information — patient presentations, outcomes, process variations, quality signals that never got followed up — and most of it has never been properly interrogated. Not because it wasn't valuable, but because the volume made it impractical. AI changes the economics of that analysis. Patterns that would have taken months of manual review now surface in hours. Findings that were invisible because the dataset was too large to read are suddenly tractable. That capability — using AI to ask real questions of your own clinical data — is a core part of what I teach.
I use AI for deep research — synthesising literature across dozens of sources in the time it used to take to read one paper properly. In a field that moves as fast as health AI, that matters. I can actually stay current. And I use it to create teaching content: structuring a session, building case scenarios, stress-testing an explanation against a sceptical audience before I stand in front of one. AI has made me a more effective educator — not by writing my slides for me, but by compressing the thinking time between an idea and a well-constructed lesson.
Outside clinical practice, I build health AI products. Intelligent Roster automates workforce scheduling for health services. Intelligent Helix is an institutional knowledge assistant that answers operational and policy questions drawing only from a health organisation's own approved documents, with citations provided for every response. These aren't side projects. They're how I stay close to what actually works in health system environments, and they directly shape how I teach.
I hold fellowship of the Australasian College for Emergency Medicine and the Royal College of Emergency Medicine UK, and am an Associate Fellow of the Royal Australasian College of Medical Administrators. I completed the MIT xPRO Certificate in Artificial Intelligence in Healthcare in 2025.
Intelligent Mind® Pty Ltd · ABN 91 691 526 351 · [email protected]
Safe clinical use
Compliance is curriculum, not a disclaimer
Safe and compliant use of AI isn't covered in a slide at the end. It is the operating framework every practical exercise is built around — from the first session to the capstone reflection.
Patient data stays de-identified — in every exercise.
All tasks in this series use anonymised scenarios or participant-supplied de-identified cases. Participants learn why this is non-negotiable, not just that it is.
Participants practise verifying AI output — not accepting it.
Every documentation and content task includes a structured review step. The series teaches a three-step verification protocol so participants leave with a repeatable method, not just an instruction to "check the output".
Accountability is addressed directly.
The documentation session covers exactly what it means to sign a note that AI helped draft. The capstone reflection asks participants to articulate their professional accountability in their own words — on the record, as part of the CPD evidence package.
Hospital IT restrictions are a teaching point, not a footnote.
Participants leave knowing which tools are available on locked-down hospital systems, which require a personal device, and how to work within local AI governance frameworks — including how to advocate for appropriate access.
Australian Privacy Principles, My Health Record obligations, and data residency considerations are covered explicitly in IMI-01 Hour 3.
CPD Structure
CPD Accreditation PendingEach course is structured across three recognised CPD categories. Hours are self-claimable for most clinical college CPD frameworks. ACEM formal accreditation is currently pending.
| Course | EA hrs | RP hrs | MO hrs | Total |
|---|---|---|---|---|
Foundations AI-Augmented Practice | 4 | 2 | 2 | 8 |
Practitioner Applied AI Fluency | 5 | 2 | 1 | 8 |
Architect AI Architecture for Health | 5 | 1 | 2 | 8 |
| Series total | 14 | 5 | 5 | 24 |
EA = Educational Activities · RP = Reviewing Performance · MO = Measuring Outcomes. CPD categories are self-claimable under most Australasian clinical college frameworks.
Tools Covered Across the Series
All tools taught using a task-first framework.
Claude (Anthropic)
Reasoning, writing, The Diagnostic Prompt, long documents
ChatGPT / GPT-4o
Broad clinical tasks, comparison baseline
Gemini Deep Research
Multi-source literature synthesis with citations
NotebookLM (Google)
Personal clinical knowledge base, guideline querying
Perplexity AI
Real-time cited answers to on-shift clinical questions
Microsoft Copilot
Excel audit analysis, PowerPoint — hospital IT-approved
AI Ambient Scribing
Clinical documentation, consultation capture
Make.com
No-code workflow automation, agentic workflows
Questions before enrolling?
Reach out directly or view the programme that interests you most.