Healthcare AI Deployment Readiness Checklist

InsytAI · Singapore · For healthcare, research, and enterprise teams planning clinical AI deployment. This checklist does not constitute medical advice.

1. Data readiness

• Data sources identified and documented (EMR, imaging, labs, notes)
• Data quality assessed (completeness, consistency, timeliness)
• Access governance and consent pathways defined
• De-identification / pseudonymisation approach documented
• Train/validation/test split strategy defined on institutional data

2. Clinical workflow fit

• Target workflow mapped with frontline users
• Human-in-the-loop touchpoints defined
• Override and escalation paths documented
• Integration points with existing systems identified
• Success metrics agreed with clinical stakeholders

3. Model evaluation

• Evaluation metrics defined (clinical + operational)
• Benchmark datasets vs real-world institutional data addressed
• Bias and subgroup performance assessed
• Failure modes and edge cases documented
• Independent validation plan in place

4. Privacy & security

• PDPA / local privacy requirements mapped
• Data residency and cross-border transfer assessed
• Encryption at rest and in transit verified
• Role-based access control implemented
• Security review completed before production

5. AI governance

• Model risk classification documented
• Ethics / IRB pathway identified where required
• ISO 42001 alignment gap assessment completed
• Model card / documentation prepared
• Change management and approval workflow defined

6. Monitoring & drift

• Production monitoring metrics defined
• Data drift and model drift detection planned
• Incident response and rollback procedures documented
• Audit logging for every inference enabled
• Periodic re-validation schedule set

7. Implementation risk

• Technical dependencies and blockers identified
• Deployment environment chosen (cloud / on-prem / hybrid)
• Rollback and fallback strategy defined
• Training and adoption plan for end users
• Leadership-ready summary prepared for sign-off

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