CareQueue AI

Smart Clinic Triage & Queue Management System

A complete MVP web application designed for small healthcare clinics and Barangay Health Centers to efficiently manage patient walk-ins, AI-based triage prioritization, live queue management, and clinic analytics.

---

🎯 Features

Patient Registration

• Simple registration form with required fields validation
• AI-based triage automatically classifies patients into Emergency, Urgent, or Normal priority
• Automatic queue number assignment
• Smart visit duration estimation based on symptoms and age
• Consultation type suggestion (General, Emergency, Specialist)

Live Queue Dashboard

• Real-time queue display (updates every 5 seconds)
• Priority-based sorting (Emergency → Urgent → Normal)
• Estimated wait times per patient
• Visual priority indicators with color-coded badges
• Mobile-responsive design

Analytics Dashboard

• Total patients today
• Priority breakdown (Emergency, Urgent, Normal)
• Active queue count
• Completed visits
• Average waiting time
• Real-time statistics

Staff/Admin Panel

• Simple staff login (no complex authentication for MVP)
• Queue management - Update patient status (Waiting → In Consultation → Done)
• Daily patient log - View all patients seen today
• Clear completed visits - End-of-day cleanup
• Daily report summary

---

🛠️ Tech Stack

• Frontend: React 18 + Vite
• Styling: TailwindCSS
• Backend: Node.js + Express
• Database: SQLite
• API: REST API

---

📂 Project Structure

carequeue-ai/
├── backend/
│   ├── data/
│   │   └── carequeue.db          # SQLite database (auto-generated)
│   ├── models/
│   │   ├── Patient.js            # Patient database operations
│   │   └── Staff.js              # Staff authentication
│   ├── routes/
│   │   ├── patients.js           # Patient registration endpoints
│   │   ├── queue.js               # Queue management endpoints
│   │   ├── auth.js                # Staff login endpoints
│   │   └── reports.js            # Analytics and reports endpoints
│   ├── utils/
│   │   └── triageLogic.js        # AI triage classification logic
│   ├── database.js                # Database initialization
│   ├── server.js                  # Express server
│   └── package.json
│
├── frontend/
│   ├── src/
│   │   ├── components/
│   │   │   ├── PatientForm.jsx      # Patient registration form
│   │   │   ├── QueueDashboard.jsx   # Live queue display
│   │   │   ├── AnalyticsDashboard.jsx # Analytics dashboard
│   │   │   ├── AdminPanel.jsx        # Staff management panel
│   │   │   └── AdminLogin.jsx        # Staff login
│   │   ├── api.js                   # API client
│   │   ├── App.jsx                  # Main app component
│   │   ├── main.jsx                # Entry point
│   │   └── index.css               # TailwindCSS styles
│   ├── index.html
│   ├── vite.config.js
│   ├── tailwind.config.js
│   └── package.json
│
├── README.md
└── SETUP.md

---

🚀 Quick Start

Prerequisites

• Node.js (v16 or newer) - Download
• npm (comes with Node.js)

Installation & Setup

1. Clone or navigate to the project directory

cd carequeue-ai

2. Install Backend Dependencies

cd backend
npm install

3. Install Frontend Dependencies

cd ../frontend
npm install

4. Start the Backend Server

From the backend directory:

npm start

You should see:

╔══════════════════════════════════════════╗
║     CareQueue AI - Backend Server        ║
║     Running on http://localhost:5000     ║
╚══════════════════════════════════════════╝

The SQLite database will be automatically created in backend/data/carequeue.db on first run.

5. Start the Frontend (New Terminal)

From the frontend directory:

npm run dev

The app will open at http://localhost:3000

---

📊 Database Schema

Patients Table

CREATE TABLE patients (
  id TEXT PRIMARY KEY,
  queue_number INTEGER NOT NULL,
  name TEXT NOT NULL,
  age INTEGER NOT NULL,
  contact_number TEXT,
  symptoms TEXT NOT NULL,
  temperature REAL,
  is_emergency INTEGER DEFAULT 0,
  priority TEXT NOT NULL,              -- 'emergency', 'urgent', 'normal'
  priority_reason TEXT,
  status TEXT DEFAULT 'waiting',        -- 'waiting', 'in_consultation', 'done'
  estimated_duration INTEGER,          -- minutes
  consultation_type TEXT,               -- 'General', 'Emergency', 'Cardiology', etc.
  created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
  updated_at DATETIME DEFAULT CURRENT_TIMESTAMP,
  completed_at DATETIME
);

Staff Table

CREATE TABLE staff (
  id INTEGER PRIMARY KEY AUTOINCREMENT,
  username TEXT UNIQUE NOT NULL,
  password TEXT NOT NULL,
  role TEXT DEFAULT 'staff',
  created_at DATETIME DEFAULT CURRENT_TIMESTAMP
);

Default Admin Credentials:

• Username: admin
• Password: carequeue123

---

🔌 API Endpoints

Patient Registration

POST /api/patients

• Register a new patient
• Request body: { name, age, contactNumber?, symptoms, temperature?, isEmergency? }
• Returns: Patient object with queue number and priority

GET /api/patients

• Get all patients (admin)

Queue Management

GET /api/queue

• Get sorted live queue (by priority, then arrival time)
• Returns: Array of patients with estimated wait times

PATCH /api/queue/:id/status

• Update patient status
• Request body: { status: 'waiting' | 'in_consultation' | 'done' }

DELETE /api/queue/completed

• Clear all completed patients

Authentication

POST /api/auth/login

• Staff login
• Request body: { username, password }
• Returns: User object

Reports & Analytics

GET /api/reports/daily

• Get daily statistics
• Returns: Report object with counts and averages

GET /api/reports/log

• Get daily patient log
• Returns: Array of all patients seen today

---

🤖 AI Triage Logic

The system uses rule-based classification to automatically prioritize patients:

Emergency Priority (🔴)

Triggered by:

• Symptoms containing: chest pain, difficulty breathing, unconscious, severe bleeding, stroke, seizure, etc.
• Temperature ≥ 40°C
• Manual emergency checkbox checked

Urgent Priority (🟠)

Triggered by:

• Symptoms containing: high fever, infection, severe abdominal pain, wound, dehydration, etc.
• Temperature 38.5°C - 40°C

Normal Priority (🟢)

• All other cases

Visit Duration Estimation

The system estimates consultation duration based on:

• Priority level (Emergency: 45min, Urgent: 30min, Normal: 15min)
• Age (Pediatric +10min, Elderly +5min)
• Symptom complexity (Multiple symptoms +10min)
• Consultation type (Specialist consultations add time)

---

✅ Validation

The application includes client and server-side validation:

• Patient Name: Required, non-empty
• Age: Required, must be ≥ 0
• Symptoms: Required, non-empty
• Contact Number: Optional, validated format
• Temperature: Optional, numeric range 35-45°C

---

🎨 UI Features

• Modern, clean design with TailwindCSS
• Responsive layout - works on desktop, tablet, and mobile
• Color-coded priority badges for quick visual identification
• Real-time updates - Queue refreshes automatically
• Intuitive navigation - Easy to use for clinic staff

---

📝 Example Test Data

Register a Patient

POST /api/patients
{
  "name": "Juan Dela Cruz",
  "age": 35,
  "contactNumber": "09123456789",
  "symptoms": "chest pain and difficulty breathing",
  "temperature": 37.5,
  "isEmergency": false
}

Expected Response:

{
  "success": true,
  "message": "Patient registered successfully",
  "patient": {
    "id": "P1234567890-abc123",
    "queueNumber": 1,
    "name": "Juan Dela Cruz",
    "priority": "emergency",
    "status": "waiting",
    "estimatedDuration": 45,
    "consultationType": "Cardiology",
    "estimatedWait": 5
  }
}

---

🚢 Deployment Guide

Backend Deployment (Render/Railway)

1. Create a new Node.js service
2. Set build command: cd backend && npm install
3. Set start command: cd backend && npm start
4. Set environment variable: PORT=5000
5. The SQLite database file will persist in the service

Frontend Deployment (Vercel/Netlify)

1. Connect your repository
2. Set build command: cd frontend && npm install && npm run build
3. Set output directory: frontend/dist
4. Set environment variable: VITE_API_URL=https://your-backend-url.com/api

Note: For production, consider migrating to PostgreSQL or MongoDB instead of SQLite for better scalability.

---

🔒 Security Notes (MVP)

This is an MVP for internship presentation. For production use:

• ✅ Replace simple password auth with JWT tokens
• ✅ Use environment variables for secrets
• ✅ Add rate limiting
• ✅ Implement proper session management
• ✅ Add input sanitization
• ✅ Use HTTPS
• ✅ Add database backups

---

📄 License

MIT — Feel free to use and modify for your clinic.

---

👥 Support

For questions or issues, please refer to the project documentation or contact the development team.

---

Built with ❤️ for small healthcare clinics