HealthLinc

HealthLinc Ecosystem — Agentic RCM & EHR System Template

Author: Dr. Mohamed El Fadil — BRAINSAIT برينسايت Founder & Lead Development and Innovations Date: 2025-05-12 Purpose: Template and detailed guide for building a full-stack Agentic Healthcare RCM & EHR system from scratch using FHIR, HL7, Cloudflare MCP, and AI-powered automation.

Overview
Core Components
System Architecture
Technology Stack
Backend Setup
Frontend Setup
Integration with FHIR & HL7
MCP Server & Client Setup
Agentic Workflow Design
Security & Compliance
Deployment & Scaling
Continuous Monitoring & Feedback
Appendices & Resources

1. Overview

The HealthLinc Ecosystem is a modular, secure, and intelligent platform for managing healthcare records and financial workflows. It combines modern interoperability (FHIR, HL7), cloud-native scalability (Cloudflare Workers), and an intelligent agent-based system (LINC agents) for automation and efficiency.

2. Core Components

RCM Module: Insurance, billing, claims, denials.
EHR Module: Patient charts, observations, clinical notes.
FHIR/HL7 Gateway: Interoperability layer.
MCP Server: Context-aware inference routing.
Agentic AI: Autonomous LINC agents for task handling.
Clinician Portal: Interface for doctors/staff.
Patient Portal: Self-service and records access.

3. System Architecture

Frontend (SwiftUI/Web)
    |
MCP Client (e.g., CoMasterLinc)
    |
MCP Server (Cloudflare Worker + KV)
    |
----------------------------
|     LINC Agents Layer     |
|   - ClaimLinc             |
|   - RecordLinc            |
|   - AuthLinc              |
|   - NotifyLinc            |
----------------------------
    |
FHIR/HL7 APIs  <-->  Healthcare Systems

4. Technology Stack

Layer	Technology
Frontend	SwiftUI (macOS, iPadOS, iOS), HTML/CSS/JS
Backend	FastAPI, Node.js (optional)
AI Agents	Python (LangChain/OpenAI/Claude SDKs)
Interoperability	FHIR (R4+), HL7 v2.x, HAPI FHIR
Serverless	Cloudflare Workers, KV storage
Automation	GitHub Actions, Docker, Coolify
Monitoring	Grafana, Loki, Promtail
Security	JWT, Bearer Tokens, TLS, GDPR/HIPAA

5. Backend Setup

Clone MCP Server template (e.g., brainsait-mcp-secure-worker)

Set up Cloudflare Worker project:

wrangler init healthlinc-mcp
wrangler login
wrangler publish

Add secure KV storage for token access:

wrangler kv:namespace create "HEALTHLINC_TOKENS"

Add MCP token validation logic:

// index.ts
async function authorize(request) {
  const token = request.headers.get("Authorization");
  // compare against KV
}

6. Frontend Setup (SwiftUI)

Create a new project HealthLincApp
Create MCPClient.swift:
- Handles SSE/REST requests to MCP Server
UI Components:
- PatientCardView
- ClaimSubmissionView
- ChatAgentView for AI agents

7. Integration with FHIR & HL7

Use hapi-fhir or firely-server for FHIR backend.
HL7 listener (MirthConnect) to transform v2.x into FHIR JSON.
Endpoint examples:
```
GET /fhir/Patient/123
POST /fhir/Claim
```

8. MCP Server & Client

Worker endpoint:

POST /query -> MCP routes to LINC Agent

Client (CoMasterLinc) handles UI and decisioning

Example call:

curl -X POST https://mcp.healthlinc.workers.dev/query \
  -H "Authorization: Bearer {token}" \
  -d '{"agent":"ClaimLinc","task":"submit","data":{...}}'

9. Agentic Workflow Design

Each LINC Agent is:

Stateless containerized service
Uses structured task + context + goal format
Runs AI-powered logic using OpenAI or Claude API
Logs via DocuLinc

Example agent repo structure:

agent-claimlinc/
├── main.py
├── Dockerfile
├── config.yaml
└── prompts/
    └── submit_claim.txt

10. Security & Compliance

Bearer Token via KV store
Enforce HTTPS + IP filtering
Encrypt all logs (DocuLinc)
GDPR consent records

11. Deployment & Scaling

Use Coolify for private deployments
Deploy agents as Docker containers:
```
docker compose up -d
```
Auto-scale MCP with Cloudflare
Add Cloudflare Tunnel for secure LAN access

12. Continuous Monitoring & Feedback

Grafana dashboard
Loki + Promtail for logs
Telegram notifications via NotifierLinc
MCP Inspector UI for visual graph of agent responses