Clinical AI Governance Framework
I use a six-pillar Clinical AI Governance Framework to evaluate AI adoption in healthcare systems.
Core Pillars
- Clinical Value — Does the AI improve patient care or clinical decision-making?
- Workflow & Adoption — Does it integrate into clinical practice without increasing burden?
- Ethics & Equity — Does it ensure fairness, transparency, and responsible use?
- Safety & Risk — Does it protect patients and support safe decision-making?
- Privacy & Compliance — Does it meet regulatory and data protection standards?
- Performance & Outcomes — Is success measurable and continuously monitored?
This framework reflects my developing approach to evaluating healthcare technology through both clinical and systems-thinking perspectives.
AI Ethics in Healthcare
- Clinicians verify AI-generated content before it enters the medical record.
- AI supports efficiency, but clinicians remain accountable for accuracy and interpretation.
- Patient narratives must be preserved to maintain clinical context and quality of care.
These principles guide my perspective on responsible AI use in healthcare environments.
How I Built This Work
I used ChatGPT (OpenAI) to help structure and refine initial ideas for healthcare AI governance frameworks. I then iteratively revised the outputs to align with clinical workflows, healthcare system realities, and concepts I am exploring through my DNP program and nursing practice.
Additional Projects (In Progress)
- Healthcare workflow mapping in behavioral health settings
- AI evaluation framework for clinical decision support tools
- Healthcare systems thinking models for digital transformation
Faith in AI Health 