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Next.js
Supabase
Healthcare
AI
Full-Stack
TypeScript
PostgreSQL

Building a Healthcare App with Next.js and Supabase: A Complete Guide

Learn how to build a full-stack healthcare application using Next.js, Supabase, and AI integration. From authentication to real-time data management and AI-powered features.

UK

Vaibhav Parmar

Full Stack Developer

December 15, 2024
2 min read

Introduction

Building a healthcare application requires careful consideration of data security, user experience, and scalability. In this comprehensive guide, I'll walk you through how I built the Community Health Assistant using Next.js, Supabase, and AI integration.

Why This Tech Stack?

Next.js for Performance and SEO

Next.js provides excellent performance optimizations out of the box, which is crucial for healthcare applications where users need quick access to information. The App Router offers better code organization and improved developer experience.

Supabase for Backend-as-a-Service

Supabase provides a complete backend solution with:

  • Authentication: Built-in user management with email/password and social logins
  • Database: PostgreSQL with real-time subscriptions
  • Storage: Secure file storage for user data
  • Row Level Security: Essential for healthcare data protection

AI Integration with Gemini

Google's Gemini API provides powerful AI capabilities for symptom checking and health insights while maintaining user privacy.

Project Architecture

src/
├── app/
│   ├── (auth)/
│   │   ├── login/
│   │   └── register/
│   ├── dashboard/
│   ├── symptoms/
│   └── facilities/
├── components/
│   ├── ui/
│   ├── forms/
│   └── charts/
├── lib/
│   ├── supabase/
│   ├── ai/
│   └── utils/
└── types/

Key Features Implementation

1. User Authentication with Supabase

// lib/supabase/client.ts
import { createClientComponentClient } from '@supabase/auth-helpers-nextjs';
 
export const supabase = createClientComponentClient();
 
// Authentication functions
export const signUp = async (email: string, password: string) => {
  const { data, error } = await supabase.auth.signUp({
    email,
    password,
  });
  return { data, error };
};

2. AI-Powered Symptom Checker

// lib/ai/symptom-checker.ts
import { GoogleGenerativeAI } from '@google/generative-ai';
 
const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY!);
 
export const analyzeSymptoms = async (symptoms: string, userInfo: any) => {
  const model = genAI.getGenerativeModel({ model: 'gemini-pro' });
 
  const prompt = `
    Analyze these symptoms: ${symptoms}
    User age: ${userInfo.age}
    Medical history: ${userInfo.medicalHistory}
    
    Provide general health insights and recommendations.
    Remember: This is not a substitute for professional medical advice.
  `;
 
  const result = await model.generateContent(prompt);
  return result.response.text();
};

3. Real-time Data Management

// components/MedicineReminder.tsx
import { useEffect, useState } from 'react';
import { supabase } from '@/lib/supabase/client';
 
export const MedicineReminder = () => {
  const [reminders, setReminders] = useState([]);
 
  useEffect(() => {
    const channel = supabase
      .channel('medicine_reminders')
      .on('postgres_changes', { event: '*', schema: 'public', table: 'reminders' }, (payload) => {
        setReminders((prev) => [...prev, payload.new]);
      })
      .subscribe();
 
    return () => supabase.removeChannel(channel);
  }, []);
 
  // Component implementation...
};

Security Considerations

Row Level Security (RLS)

-- Enable RLS on user data
ALTER TABLE user_health_data ENABLE ROW LEVEL SECURITY;
 
-- Policy to ensure users can only access their own data
CREATE POLICY "Users can only access their own health data" ON user_health_data
  FOR ALL USING (auth.uid() = user_id);

Data Encryption

  • All sensitive data is encrypted at rest
  • HTTPS enforced for all communications
  • API keys stored securely in environment variables

Performance Optimizations

1. Image Optimization

import Image from 'next/image'
 
<Image
  src="/healthcare-icon.webp"
  alt="Healthcare"
  width={500}
  height={300}
  priority
  placeholder="blur"
  blurDataURL="data:image/jpeg;base64,..."
/>

2. Database Query Optimization

// Use Supabase's built-in query optimization
const { data, error } = await supabase
  .from('health_facilities')
  .select('id, name, address, distance')
  .eq('city', userCity)
  .order('distance', { ascending: true })
  .limit(10);

Deployment and Monitoring

Vercel Deployment

// vercel.json
{
  "functions": {
    "app/api/**/*.ts": {
      "maxDuration": 30
    }
  },
  "env": {
    "SUPABASE_URL": "@supabase_url",
    "SUPABASE_ANON_KEY": "@supabase_anon_key",
    "GEMINI_API_KEY": "@gemini_api_key"
  }
}

Lessons Learned

  1. Privacy First: Always implement proper data protection measures
  2. User Experience: Healthcare apps need intuitive interfaces
  3. Performance: Fast loading times are crucial for user trust
  4. Scalability: Design for growth from the beginning

Conclusion

Building a healthcare application with Next.js and Supabase provides a solid foundation for creating secure, scalable, and user-friendly health solutions. The combination of modern web technologies with proper security measures ensures both developer productivity and user safety.

The key is to always prioritize user privacy and data security while maintaining excellent performance and user experience.


This blog post is based on my experience building the Community Health Assistant. You can view the live application at ai-health-assistant-rho.vercel.app and the source code on GitHub.

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Vaibhav Parmar

Vaibhav Parmar

Software Engineer & Technical Writer

Passionate about building privacy-focused applications and seamless user experiences. I specialize in React.js, React Native, Next.js, and mobile development. Always exploring new tools and techniques to create better digital experiences.