The paper elaborates on deploying Swarm-Structured Multi-Agent Systems (MAS) in conjunction with LLMs to aid the medical necessity justification process in healthcare settings. By systematically segmenting complex tasks into simpler subtasks, each handled by a specialized AI agent, this hybrid approach not only enhances accuracy but also boosts explainability in medical reviews. The novel architecture leverages prompt-based strategies with LLMs, providing an analytical backbone that significantly raises the veracity of medical justifications.

Highlights:

• Medical Necessity Justification: Uses AI to verify the medical necessity of treatments.
• Swarm-Structured Multi-Agent Systems: Employs multiple AI agents for segmented task handling.
• Integration with LLMs: Enhances the power and flexibility of MAS through seamless integration with LLMs.

Potential Impact:

• Increased Accuracy and Trust: Aims for higher precision and reliability in medical decisions.
• Enhanced Explainability: Offers clearer explanations for automated decisions, fostering greater trust among practitioners and patients.
• Optimized Medical Reviews: Streamlines the process, reducing time and resource consumption.