Beyond the Code:
Building Trust in High-Risk Health AI
Health AI Governance Advisory is an independent educational and advisory initiative focused on Sociotechnical Governance of AI in Healthcare. By combining evidence-informed insights from health informatics, implementation science, and AI governance, it supports more responsible, practical, and sustainable approaches to AI use in healthcare.
The Pain Points I Help You Navigate
Building professional confidence through rigorous sociotechnical auditing.
Fairness evaluations to prevent patient harm and reputational damage.
Ensuring systems meet evolving global regulatory standards and documentation.
Assessing the real-world operational impact of AI on clinical staff.
Identifying failure models and human-AI interaction risks to ensure safety.
Advisory Areas
Technical Readiness Review
Clinical Workflow Integration Review
Human-AI Interaction and Usability Review
Fairness and Bias Review
Workshops and Masterclasses
For Healthcare Providers
Clinician-oriented education focused on human–AI interaction, workflow integration, cognitive burden, trust, usability, oversight responsibilities, and the practical realities of using AI safely and effectively in contemporary clinical practice.
For Health Leaders
Executive-focused sessions examining organisational readiness, governance maturity, accountability structures, implementation strategy, generative AI adoption, and the sociotechnical challenges associated with operationalising AI in healthcare environments.
For Researchers
Evidence-informed workshops and masterclasses exploring implementation readiness, translational barriers, and the operational realities that influence whether healthcare AI can succeed beyond pilot and research settings.
About
Dr Robab Abdolkhani
I provide specialist expertise in Health AI governance, helping healthcare organisations safely integrate AI into clinical operations. Drawing on a PhD in Health Informatics and extensive research and industry experience in sociotechnical health AI systems, I bring a rigorous, evidence-based approach to assessing risk and operational readiness. Through governance framework design, data pipeline assurance, and comprehensive sociotechnical evaluation, I deliver practical oversight structures that ensure regulatory alignment, data integrity, and safe, transparent deployment. My advisory supports healthcare organisations to adopt AI confidently, responsibly, and at scale.
- Associate Degree — Medical Record Administration
- BSc — Health Information Management
- MSc — Health IT
- PhD — Health Informatics & Information Systems
- The Global Agency for Responsible AI in Health
- International Open Digital Health Organization
- Australasian Institute of Digital Health
- ISO/IEC 42001 AI management systems
- AI governance & responsible AI training
- AI auditing & assurance training
- Cloud computing & applied AI pathways
Why Work With Me
I understand healthcare systems, not just algorithms
I evaluate real-world use, not just model accuracy
I align with global AI regulations
I write professional-level reports for executives, regulators, and academic environments
I understand the cultural, organisational, and human impacts of technology in healthcare
I simplify complex AI issues for non-technical healthcare executives
I bring a lens of equity and patient safety, not just fairness metrics
Projects
A sociotechnical framework for data quality management in AI-enabled health wearables
Internationally validated via expert consensus.
Blog
Trust, but verify: health AI governance
How to verify third-party AI models and protect patient data in clinical settings.
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Rethinking the loop in health AI systems
Why collaborative AI-in-the-loop design matters more than automation alone.
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Beyond accuracy: model selection in health AI
A sociotechnical lens for choosing safer, more practical health AI models.
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Let's build responsible Health AI together.
Whether you are evaluating an AI solution, designing governance, or preparing your organisation for safe AI adoption — I can help.
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