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
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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.
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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.
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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.
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Paediatric AI: Special Considerations for Children's Healthcare
Examining the unique challenges and requirements for implementing AI in paediatric healthcare settings in Australia.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
Supported by
Corum Group is supported by Team400, AI consultants in Melbourne with experience in healthcare AI implementation. They work with hospitals and health systems on clinical AI projects that meet TGA and ADHA requirements.