QR-Based Patient Medication and Regimen Management System: A Smart Healthcare System for Secure Regimen Monitoring

Abstract

This paper presents a comprehensive study and practical implementation of a QR-based patient medication and regimen management system. The system integrates mobile and web applications, QR code generation and scanning, cloud-based storage, and secure database management to ensure accurate tracking of patient medications and adherence to prescribed regimens. A key feature of the system is its ability to generate unique QR codes for each prescribed medication, which patients can scan to record intake and update adherence status in real-time. Additionally, the system provides separate dashboards for doctors and patients, enabling doctors to remotely monitor patient compliance, modify prescriptions, and send alerts for missed doses. The backend server ensures data consistency, security, and synchronization across devices, safeguarding sensitive patient information through authentication and encryption mechanisms. Comparative analysis with traditional manual or paper-based medication tracking highlights improvements in patient compliance, accuracy, security, and overall healthcare efficiency. The proposed system demonstrates the practical feasibility of integrating QR code technology, mobile and web applications, and secure cloud databases to create a modern, reliable, and user-friendly solution for patient medication and regimen management.

Introduction

Efficient medication management is crucial for patient safety, adherence, and healthcare quality. Traditional methods—paper records, manual logs, and verbal reminders—are error-prone, inefficient, and can lead to missed doses or incorrect intake. The proposed solution is a QR-based patient medication and regimen management system that integrates mobile and web applications, QR codes, cloud databases, backend servers, and real-time notifications to improve tracking, adherence, and oversight.

Key Features and Components:

• Mobile Devices & Apps: Patients scan QR codes on medications, log intake, receive reminders, and track schedules.

• Web Application: Doctors monitor adherence, generate prescriptions/QR codes, and send alerts.

• Backend & Cloud Database: Secure storage, real-time synchronization, authentication, and encryption ensure data integrity and privacy.

• Offline Support: Intake can be logged without internet, syncing automatically when connectivity is restored.

• Security Mechanisms: User authentication, data encryption, audit logs, and fraud prevention maintain patient privacy and system reliability.

System Operations:

1. Prescription Management: Doctors create prescriptions, generate QR codes, link patients, and update the database.

2. Medication Adherence Tracking: Patients scan QR codes, intake is logged, and notifications are sent for missed doses.

3. Real-Time Monitoring: Doctors can intervene based on adherence reports.

Advantages:

• Improves efficiency, accuracy, security, and transparency.

• Enhances patient adherence with reminders and real-time feedback.

• Supports scalability for multiple patients and medications.

• Offers convenience for patients and remote oversight for doctors.

Novelty and Contribution:

• Combines QR code technology with web/mobile platforms for real-time adherence tracking.

• Supports offline operation with automatic synchronization.

• Provides a robust, secure, and user-friendly alternative to traditional manual medication management systems.

Conclusion

This project presents an integrated QR code and IoT-based patient medication management system optimized for accurate medication tracking and adherence monitoring. The combination of QR codes, web/mobile portals, and MongoDB ensures real-time updates, offline-first logging, and secure data storage. Future work includes integrating AI-based dosage reminders, smart pill dispensers, and expanding the system for multi-hospital and pharmacy networks to further improve patient care and treatment compliance.

References

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Copyright

Copyright © 2025 Vaishnav Jedhe, Anushka Parulekar, Tanvi Mohite, Prof. S. S. Dighe. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.