Healthcare Data Extractor for Reliable Integration
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Solution Overview
Problem
Current systems face challenges in reliably and securely integrating and managing diverse healthcare data sources across heterogeneous infrastructure and workflow software, due to infrastructure heterogeneity, software variability, security compliance, and the need for autonomous deployment of updates, which existing tools such as Visual Analytic Platforms, Internet of Things Platforms, Database Replication Tools, Data Integration Platforms, and Healthcare Integration Engines do not adequately address.
Innovation Solution
A method and system that packages software as executable assets, installs parent and child modules as operating system services to monitor and recover from failures, and securely extracts or mutates data using logically isolated infrastructure resources with a data extractor that connects to data sources, updates assets automatically, and rotates authentication credentials for enhanced security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If diverse healthcare data sources are integrated across heterogeneous infrastructure, then data extraction capability is improved, but system reliability deteriorates due to infrastructure variability and security compliance challenges
Solution Approach 1:
The patent introduces a data extractor as an intermediary component that mediates between the subject infrastructure and object infrastructure. This extractor implements standardized interfaces and protocols, allowing diverse data sources to be accessed through a unified mechanism that ensures reliable and secure data extraction while maintaining system stability across heterogeneous environments
Solution Approach 2:
The system is segmented into distinct modular components including the data extractor, subject infrastructure, and object infrastructure. Each component operates independently with well-defined interfaces, allowing the system to adapt to different data sources while maintaining overall reliability through localized failure containment and independent component management
2Ease of operation
If software systems are updated autonomously without direct interaction with external infrastructure, then ease of operation is improved, but device complexity increases due to self-management requirements
Solution Approach 1:
The data extractor is designed with self-service capabilities that enable autonomous operation including automatic health monitoring, self-diagnosis, and self-repair mechanisms. The system can detect failures, attempt recovery autonomously, and manage its own authentication credentials without requiring direct human intervention or complex external infrastructure interactions
Solution Approach 2:
The system implements continuous feedback loops through health monitoring mechanisms that track the operational status of the data extractor and connected systems. This feedback enables autonomous decision-making for updates and repairs, with the system automatically adjusting its operation based on real-time status information while maintaining manageable complexity through standardized feedback protocols
3Object-affected harmful factors
If authentication credentials are rotated frequently for enhanced security, then security compliance is improved, but loss of time increases due to credential management overhead
Solution Approach 1:
The system performs preliminary actions by pre-configuring authentication credential rotation schedules and automatically managing credential lifecycle events before security issues arise. Credentials are rotated according to predetermined security policies without manual intervention, and the system proactively handles credential expiration and renewal to prevent operational disruptions
Solution Approach 2:
The data extractor implements self-service authentication credential management that automatically handles rotation, renewal, and expiration without requiring manual intervention. The system autonomously manages the credential lifecycle, reducing security risks through automated rotation while minimizing time loss through efficient self-management mechanisms
Data Source
AI summary
Known extraction or mutation of information enclosed in data sources associated with workflow software in a reliable, resilient and secure fashion at scale is a complex task. According to the present invention, there are provided methods and systems for improving reliability and resiliency of a computer-based software system installed on an object infrastructure managed by an external party. One method includes: packaging a computer-based system for as an executable asset; installing an executable asset of a first parent module as an operating system service; installing an executable asset of a second parent module as an operating system primitive; configuring the first parent module to execute said computer-based system as a child process; configuring the first and second parent process to respectively execute a child process for monitoring health of the other parent module and child processes, and attempting recovery of detected failures.