Secure Integration of Sensor Networks and Distributed Web Systems for Electronic Health Records and Custom CRM.

Area of Science:

• Health Informatics
• Cybersecurity in Healthcare
• Internet of Things (IoT)

Background:

• Integrating sensor networks with electronic health records (EHR) presents challenges in data privacy, security, and interoperability.
• Real-time patient monitoring requires robust systems that can handle sensitive physiological data securely.

Purpose of the Study:

• To propose a secure distributed web system architecture for integrating real-time sensor data with EHR and a custom customer relationship management (CRM) module.
• To optimize patient monitoring and clinical decision-making through secure data integration.

Main Methods:

• Leveraging IoT-enabled medical sensors for physiological signal capture.
• Implementing secure communication channels for data transmission and storage in a modular EHR system.
• Embedding security mechanisms: data encryption, role-based access control, and distributed authentication.

Main Results:

• Experimental simulations validated the system's scalability, low latency, and robust data protection performance.
• The proposed architecture effectively addresses threats of unauthorized access and data breaches.
• The CRM module facilitates personalized healthcare management within strict privacy constraints.

Conclusions:

• Combining CRM, sensor data, and distributed technologies enhances healthcare delivery.
• The system demonstrates potential for secure and privacy-compliant healthcare data integration.
• The architecture supports optimized patient monitoring and improved clinical decision-making.