MediAgents

Inspiration

Healthcare systems today are highly fragmented, with patient data scattered across multiple platforms and departments. This lack of interoperability often leads to delayed diagnoses, inefficient workflows, and increased burden on healthcare professionals.

We were inspired to solve this by leveraging AI agents that can collaborate and communicate seamlessly using standardized healthcare protocols like FHIR. Our goal was to create a system where multiple intelligent agents work together to improve decision-making and patient outcomes in real time.

What it does

Our project is an interoperable multi-agent healthcare system where specialized AI agents handle different tasks such as patient triage, diagnosis assistance, and real-time monitoring.

These agents communicate with each other using FHIR-based data exchange, enabling a unified and structured flow of medical information. A central coordinator agent ensures smooth interaction between agents, allowing them to collaborate effectively and provide actionable insights to healthcare providers.

How we built it

We designed a modular multi-agent architecture consisting of:

• A Triage Agent for prioritizing patient cases
• A Diagnosis Agent for analyzing symptoms and medical history
• A Monitoring Agent for tracking real-time patient data
• A Data Agent for handling FHIR-compliant medical records
• A Coordinator Agent to manage inter-agent communication (A2A)

We integrated healthcare data standards like FHIR to ensure interoperability and used AI models to process and interpret patient data. The system was built with a scalable backend and a simple interface for interaction.

Challenges we ran into

One of the main challenges was ensuring seamless communication between multiple agents while maintaining structured medical data flow. Implementing FHIR standards and mapping data correctly across agents required careful design.

Another challenge was balancing accuracy and performance in AI-driven decision-making, especially in a healthcare context where reliability is critical.

Accomplishments that we're proud of

• Successfully designed and implemented a multi-agent healthcare system where different AI agents collaborate in real time
  
• Integrated FHIR-based data exchange to ensure interoperability between agents, aligning with real-world healthcare standards
  
• Built a modular architecture that can be easily scaled and extended for additional healthcare use cases
  
• Demonstrated how AI can move beyond chatbots into coordinated, system-level decision support
  
• Delivered a functional prototype within a limited hackathon timeframe
  

What we learned

• Gained hands-on experience with healthcare interoperability standards like FHIR
  
• Understood the complexity of designing multi-agent systems and coordinating agent-to-agent (A2A) communication
  
• Learned how to structure medical data for meaningful AI-driven insights
  
• Explored the challenges of applying AI in high-stakes environments like healthcare, where accuracy and reliability are critical
  
• Improved our ability to rapidly prototype and collaborate under time constraints
  

What's next for MediAgents

• Integrating real-time data from wearable devices for continuous patient monitoring
  
• Enhancing diagnostic capabilities using more advanced and specialized AI models
  
• Connecting with hospital systems and electronic health records (EHRs) for real-world deployment
  
• Adding explainable AI features to improve transparency and trust for medical professionals
  
• Scaling the platform into a fully interoperable healthcare ecosystem supporting multiple institutions
  

Built With

• a2a
• agents
• an
• and
• api
• apis
• aws/vercel
• backend
• between
• building
• cloud
• communication
• components
• core
• data
• deployment
• development
• exchange
• express.js
• fhir
• for
• frontend
• github
• handling
• healthcare
• integration
• intelligent
• interactive
• interface
• javascript
• like
• mongodb
• multi-agent
• node.js
• openai
• platforms
• python
• react.js
• rest
• scalable
• services
• standards
• storage
• structured
• system
• using
• version
• with