Transforming Ventilator Data Management: Achieving Real-Time Streaming and Analysis for Enhanced Patient Care

Statement:

The hospital faced challenges in managing ventilator data effectively due to the 15-minute delay inherent in the Azure batch processing system. This delay in data processing hindered real-time decision-making, which is vital in critical care environments.

Additionally, the existing system lacked a robust fail-safe mechanism to handle power outages, posing risks to continuous patient care.

Resolution:

Transition to AWS with Real-Time Streaming: The project shifted from Azure to AWS, utilizing IoT Core as the first point of entry. This move enabled real-time data processing, eliminating delays in critical data handling.

Data Flow and Storage Optimization: Utilizing Kinesis Data Stream and Firehose, data streaming was optimized, enhancing the efficiency of real-time data analysis. Data was then stored in DynamoDB, ensuring fast and reliable access.

Visualization and Analysis with QuickSight: Integration with QuickSight provided advanced data visualization tools, allowing for more informed decision-making based on real-time data analytics.

Robust .NET Framework Application: A multi-threaded .NET framework application was developed to handle data from 15 ventilators, scaling inputs efficiently. Running as a service, it ensured continuity even during power outages, with fail-safe mechanisms in place.

Future Expansion Plans: To further enhance data management, plans include the integration of a data warehouse using AWS S3 or Redshift. Additionally, the possibility of transitioning to MySQL from DynamoDB is being explored to optimize data handling and storage.