Inspiration
The idea for MediTrack AI was born from the challenges elderly patients face in managing their medication schedules. Many elderly people suffer from chronic conditions such as diabetes, hypertension, and arthritis, which require constant medication management. In India, particularly in rural areas, patients often miss doses or take their medications incorrectly due to forgetfulness or difficulty accessing them regularly. This inspired us to create an AI-driven solution that would help provide timely medication reminders and ensure consistent medicine delivery without delays, improving healthcare outcomes for the elderly.
What it does
MediTrack AI is an intelligent hospital management system focused on streamlining the medication process for elderly patients. It offers the following core functionalities:
Personalized Medication Scheduling: AI-driven medicine scheduling based on patient health profiles.
Timely Reminders: Sends automated notifications, reminders, and voice calls to ensure patients take their medicine on time.
Monthly Medicine Distribution: Coordinates with health workers for monthly medicine distribution directly to patients in specific neighborhoods.
Real-Time Coordination: Enables real-time tracking and coordination between patients and health workers, ensuring no medication delivery is missed.
How we built it
We used a combination of technologies to build MediTrack AI:
Frontend: Built with React.js for a dynamic and responsive user interface.
Backend: PHP, XAMPP stack for handling server-side logic and database interactions.
Database: MySQL to store patient information, medication schedules, and delivery logs.
AI Integration: Utilized IBM Granite and Agent Development Kit (ADK) to create intelligent workflows for scheduling, reminders, and delivery planning.
APIs: Integrated Twilio for voice and SMS reminders and Google Maps API for delivery route optimization.
Challenges we ran into
Real-Time Reminders: Implementing accurate and timely reminders without overwhelming patients with notifications was challenging. We needed a fine balance to send reminders in the right window (e.g., every 5 minutes between 7:50 AM and 8:15 AM).
Logistics for Medicine Distribution: Coordinating with health workers for monthly deliveries across multiple streets required us to design an efficient mapping and scheduling system, which was complex to optimize.
AI Workflow Integration: Ensuring that the AI was smart enough to adapt to different patient needs and medication schedules without manual intervention was challenging.
Accomplishments that we're proud of
AI-powered Reminder System: We successfully implemented an AI-based reminder system that sends notifications and voice calls at the correct time.
Seamless Medicine Distribution Coordination: We developed a system that coordinates monthly medicine deliveries and integrates real-time data between patients and health workers, making the process more efficient.
User-Centered Design: The system was designed to be intuitive and user-friendly, catering to elderly patients, who are often not familiar with technology.
What we learned
User-Centered Design: We learned the importance of designing for the user first, particularly when it comes to elderly patients who may have limited tech knowledge.
AI for Real-World Impact: We saw firsthand how AI can be leveraged to solve real-world issues, from automating mundane tasks to making critical healthcare processes more efficient.
Cross-functional Integration: Building a system that integrates AI, real-time logistics, and user communication taught us how to effectively combine various technologies into a seamless, cohesive product.
What's next for MediTrack AI
Expand AI Capabilities: We plan to further refine the AI’s decision-making capabilities, such as dynamically adjusting medication schedules based on patient condition and usage patterns.
Mobile Application: A dedicated mobile app to allow patients to track their medications, receive notifications, and communicate with health workers.
Integration with Healthcare Providers: Partner with healthcare institutions to allow doctors to monitor patient progress and adjust medication plans directly from the platform.
Scaling the Solution: Extend the platform to support a larger patient base and integrate more advanced features like predictive analytics and emergency alerts.
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