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Development of a Scalable and Secure Electronic Medical Record (EMR) System with Clinical Trial Integration
  1. case
  2. Development of a Scalable and Secure Electronic Medical Record (EMR) System with Clinical Trial Integration

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Development of a Scalable and Secure Electronic Medical Record (EMR) System with Clinical Trial Integration

syberry.com
Medical
Information technology

Current Challenges in Patient Data Management

Fragmented third-party systems prevent centralized patient data access, leading to inefficiencies in chronic care management and clinical trial processes. Existing systems struggle with HIPAA compliance, scalability for large data volumes, and providing explainable AI-driven insights for clinical decision-making.

About the Client

Healthcare technology company specializing in medical software solutions

Project Goals

  • Automate patient data tracking, storage, and analysis
  • Enhance Chronic Care Management (CCM) programs and clinical trial efficiency
  • Ensure seamless integration with existing EHR systems
  • Implement HIPAA-compliant security protocols
  • Develop scalable architecture for high-volume data processing
  • Incorporate explainable AI for clinical decision support

Core System Functionalities

  • Secure centralized repository for patient records
  • Automated reminders for chronic care management
  • Clinical trial recruitment and management tools
  • Real-time analytics dashboard
  • EHR system integration capabilities
  • Role-based access control for HIPAA compliance
  • User-friendly interface for reduced training time

Technology Stack

AWS
Java 8
MySQL
Maven
VMware

System Integrations

  • Existing EHR systems
  • Clinical trial management platforms

Non-Functional Requirements

  • HIPAA-compliant data encryption and access controls
  • Horizontal scalability for large patient data volumes
  • High-performance data processing with low latency
  • Explainable AI implementation for clinical transparency

Expected Business Impact

Improved workflow efficiency through automated data management, enhanced patient outcomes via AI-driven insights, accelerated clinical trial processes with integrated tools, reduced administrative burden from streamlined workflows, and compliance with healthcare data regulations.

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