DD
Dudoxx Dispatcher
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Dudoxx Dispatcher System Architecture

flowchart TD A[Frontend Layer] --> B[API Gateway] B --> C[Core Services] C --> D[Integration Layer] D --> E[Analytics] C --> F[Infrastructure]

System Architecture Overview

Dudoxx Dispatcher employs a modular, microservices-based architecture that leverages existing Dudoxx components while adding specialized services for patient dispatch and resource optimization.

Architecture Layers

1. Frontend Layer

The Frontend Layer provides user interfaces for different stakeholders:

  • Patient Portal: Web interface for patient self-registration (React, Next.js)
  • Provider Dashboard: Interface for healthcare providers (React, Redux)
  • Admin Console: System configuration interface (React, Material UI)
  • Mobile Applications: Native mobile apps (React Native)
  • Kiosk Interface: Touch-based interface for in-facility use (Electron, React)

2. API Gateway

  • Authentication Service: Handles user authentication (OAuth 2.0, JWT)
  • Rate Limiting: Prevents API abuse (Redis, Token Bucket Algorithm)
  • Request Routing: Directs requests to appropriate microservices (Envoy, Kong)
  • Logging & Monitoring: Captures detailed request logs (ELK Stack, Prometheus)
  • API Documentation: Interactive documentation (Swagger/OpenAPI)

Integration with Dudoxx Modules

Dudoxx Dispatcher leverages multiple core Dudoxx modules:

  • Dudoxx AI LLM: Powers clinical assessment algorithms and reasoning
  • Dudoxx Chat: Enables conversational patient interfaces
  • Dudoxx Audio: Processes voice recordings and transcription
  • Dudoxx Doc: Generates structured documentation and summaries
  • Dudoxx Extractor: Processes uploaded documents and images
  • Dudoxx Flowing: Orchestrates end-to-end patient workflows
  • Dudoxx Lake: Maintains the central patient data repository

Key Technical Components

ComponentTechnology StackDescription
Patient Intake ServiceNode.js, Express, MongoDBManages patient registration, data collection, and validation
Clinical Assessment EnginePython, FastAPI, PyTorchAI-powered analysis of patient information for triage and routing
Resource Management ServiceGo, PostgreSQLTracks and manages healthcare resources and availability
Scheduling OptimizerPython, OR-Tools, RedisOptimizes patient-provider matching and scheduling
Notification ServiceNode.js, RabbitMQ, TwilioManages communication with patients and providers
EHR ConnectorHL7 FHIR API, Node.jsIntegrates with Electronic Health Record systems
Analytics EngineApache Spark, TensorFlowProcesses operational metrics and generates insights