Objective:

To explore how decision intelligence can enhance glaucoma management through improved data integration and personalized care.

Key Findings:

• Glaucoma often progresses asymptomatically, leading to late detection and treatment.
• Current care practices are fragmented, making it difficult to synthesize information for timely decisions.
• Decision intelligence can enhance diagnostic accuracy and personalize treatment by integrating diverse data sources.

Interpretation:

Integrating decision intelligence into glaucoma care can bridge the gap between abundant data and effective clinical decisions, ultimately improving patient outcomes.

Limitations:

• Implementation of decision intelligence requires significant changes in clinical workflows.
• Data fragmentation across platforms may still pose challenges even with advanced analytics.

Conclusion:

Adopting decision intelligence in glaucoma care can lead to more proactive, personalized management, reducing preventable vision loss.