Bookd

💡 Inspiration

Canada's healthcare system struggles with reactive care, leading to higher costs and longer recovery times. Preventative care can reduce these costs and improve outcomes, but many Canadians don’t prioritize it. Existing solutions lack integration between healthcare recommendations and insurance benefits. Bookd bridges this gap, using AI to offer personalized preventative care suggestions and optimize insurance coverage.

🎯 What It Does

Bookd uses AI and data integration to offer proactive healthcare solutions:

User Profile & Health Data: Users input health details, and Bookd processes this data to provide personalized care recommendations.
Automated Reminders: Personalized reminders for preventive care are sent via SMS, email, or calendar sync.
AI Recommendations: Bookd refines suggestions over time based on user data, helping with proactive care.
Health Integration: Syncs with Apple Health and Google Fit to enhance recommendations based on real-time health metrics.
Symptom Checker: AI-driven tool to assess symptoms and offer health insights.
Insurance Benefits: Users can track insurance details, submit claims, and optimize scheduling based on insurance coverage.

🔨 How I Built It

Frontend: Built with Next.js, React, and Tailwind CSS for responsive design and performance.
Backend: TypeScript and Node.js handle the API and data processing, with GraphQL for flexible queries.
Database & Security: Supabase for user authentication, data storage, and real-time syncing, ensuring HIPAA and PIPEDA compliance.
AI Engine: OpenAI's GPT-3 powers personalized recommendations, and TensorFlow is used for model training.
Scheduling & Notifications: Integrated Google Calendar API and Twilio for automated appointment scheduling and reminders.

🚧 Challenges I Ran Into

Data Privacy: Ensuring compliance with healthcare regulations like HIPAA and PIPEDA was a challenge.
Insurance Integration: Standardizing insurance data formats across providers proved difficult.
AI Accuracy: Improving the AI model's recommendations required large datasets and continuous refinement.
User Engagement: Encouraging consistent user input and long-term engagement was challenging.
Health Data Syncing: Real-time data syncing from health devices required precision and constant updates.

🏆 Accomplishments I'm Proud Of

Developed a functional prototype with personalized preventative care recommendations.
Integrated AI-driven insights for improved health suggestions.
Built a scalable architecture for future growth and new features.
Successfully implemented HIPAA and PIPEDA-compliant systems for user data.