Explainable multimodal AI and neuro-symbolic clinical decision support system for chronic eye disease management: a digital health implementation study.

The system achieved 98.3% accuracy in clinical entity extraction and 96.7% accuracy in administrative information extraction.

Automated rule validation achieved 100% reimbursement compliance with no denied insurance claims.

This resulted in an estimated labor cost saving of approximately 52 CNY (≈7 USD) per visit and projected annual savings of 42-56 USD per AMD patient under standard treatment schedules.

The proposed system improves documentation efficiency, coding accuracy, and auditability while reducing hidden administrative costs.