For healthcare and enterprise leaders
AI recommendations that put patients first
Evidence-based guidance on AI adoption in healthcare. From clinical workflows to administrative efficiency.
What we cover
- Clinical AI applications and use cases
- Healthcare data governance and privacy
- AI ethics in medical decision-making
- Implementation roadmaps and change management
Who it's for
- Healthcare executives and board members
- CIOs and technology leaders
- Clinical informaticists and digital health teams
- Health tech vendors and consultants
Latest posts
View all-
Telehealth and AI: Integration Lessons From Two Years of Australian Experience
What we've learned about integrating AI with telehealth since the pandemic-driven expansion, with practical guidance for Australian healthcare providers.
-
AI for Informed Consent: Applications Across Clinical Specialties
How AI is being applied to support informed consent processes across different clinical specialties in Australian healthcare.
-
AI in Clinical Coding: Revenue Integrity Applications in Australian Hospitals
Examining how AI is being applied to clinical coding and revenue integrity in Australian hospitals, with practical implementation guidance.
-
Paediatric AI: Special Considerations for Children's Healthcare
Examining the unique challenges and requirements for implementing AI in paediatric healthcare settings in Australia.
-
AI Strategy for Private Hospitals: Different Context, Different Approach
How private hospital AI strategy differs from public healthcare, with practical guidance for Australian private hospital leaders.
-
AI and Nursing Documentation: Reducing Burden Without Compromising Care
Examining how AI can reduce nursing documentation burden in Australian hospitals while maintaining quality and safety.
-
Building a Clinical Informatics Career in the AI Era
Career guidance for health professionals interested in clinical informatics, with specific advice for developing AI-relevant skills in Australian healthcare.
-
AI in Clinical Trial Recruitment: Improving Access to Research for Australian Patients
How AI is being used to improve clinical trial recruitment and matching in Australian healthcare settings.
-
My Health Record and AI: Current State and Future Possibilities
Examining how My Health Record data could support AI applications and what needs to change to make this feasible in Australian healthcare.
-
AI in Hospital Pharmacy: Medication Safety Applications That Actually Work
Examining practical AI applications in hospital pharmacy settings, focusing on medication safety, workflow efficiency, and clinical decision support.
-
Radiology AI Beyond Detection: Quantification, Workflow, and the Next Wave
Looking beyond lesion detection at emerging radiology AI applications in Australian practice, including quantification, workflow optimization, and reporting.
-
Patient Deterioration Prediction: Where AI Is Actually Making a Difference
Examining AI systems for predicting patient deterioration in Australian hospitals, with evidence on what works and implementation lessons.
-
Partnering with Universities on Clinical AI: A Practical Guide for Health Services
How Australian health services can effectively partner with university research teams on clinical AI development and validation.
-
When Clinical AI Performance Degrades: Detection, Causes, and Response
Understanding how clinical AI systems can deteriorate over time and what Australian healthcare organisations should do about it.
-
Hospital AI Implementation Timelines: Why Everything Takes Longer Than You Expect
Realistic timeframes for clinical AI implementation in Australian hospitals, with guidance on what causes delays and how to plan accurately.