Clinical Data Workflow Engine for Secure Multi-Standard Integration
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Solution Overview
Problem
Existing clinical data integration systems face challenges in adhering to HIPAA regulations, managing large data volumes, and ensuring secure and efficient data transmission and translation across diverse medical standards like DICOM, HL7, and FHIR, while handling complex workflows and customizations.
Innovation Solution
A workflow engine that processes clinical data as a directed acyclic graph, allowing dynamic reconfiguration without programming, using a cloud-based IoT configuration service to manage data queues and transmission protocols, and supports various medical data formats through a set of Activity elements and Queue elements, enabling seamless integration and transformation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If clinical data is transmitted across multiple medical standards (DICOM, HL7, FHIR), then data integration capability is improved, but transmission security and compliance complexity increase
Solution Approach 1:
The patent introduces a workflow engine as an intermediary component that mediates data transmission between different medical standards (DICOM, HL7, FHIR). This engine implements standardized interfaces and protocols, ensuring secure and compliant data exchange while maintaining adaptability across multiple standards. The workflow engine acts as a trusted mediator that enforces security policies and compliance rules during data transmission.
Solution Approach 2:
The workflow engine is designed with multi-functionality to handle various medical data standards simultaneously. It can process DICOM images, HL7 messages, and FHIR resources through a unified architecture, providing universal data integration capability while maintaining consistent security and compliance measures across all standard types.
2Quantity of substance
If large volume clinical data files are uploaded and downloaded, then data completeness is improved, but transmission time and system load increase
Solution Approach 1:
The patent implements segmentation by dividing large clinical data files into smaller manageable chunks or packets during transmission. The workflow engine can split large DICOM studies, HL7 bundles, or FHIR resources into multiple smaller data units, transmit them separately, and reassemble them at the destination. This reduces transmission time and system load while maintaining complete data transfer.
Solution Approach 2:
The system performs preliminary actions by pre-processing and optimizing data before transmission. This includes compressing large clinical data files, pre-validating data formats, and preparing transmission schedules. By performing these actions beforehand, the system reduces actual transmission time and minimizes system load during critical data exchange operations.
3Manufacturing precision
If mapping processes are customized for bigger organizations, then data translation accuracy is improved, but system complexity and configuration difficulty increase
Solution Approach 1:
The workflow engine implements dynamic mapping configurations that can be adjusted without redeploying software artifacts. Organizations can customize mapping processes for different data standards and requirements through configurable parameters and rules that can be modified at runtime. This maintains high data translation accuracy while reducing system complexity by separating configuration from deployment.
Solution Approach 2:
The system provides pre-configured mapping templates and dictionaries for common medical standards (DICOM, HL7, FHIR). These preliminary configurations reduce the complexity of customization by providing ready-to-use frameworks that organizations can adapt rather than build from scratch, maintaining translation accuracy while simplifying the configuration process.
4Adaptability or versatility
If workflows are reconfigured to handle complex scenarios, then process flexibility is improved, but software deployment and maintenance complexity increase
Solution Approach 1:
The workflow engine enables dynamic reconfiguration of workflows without requiring software redeployment. Complex scenarios can be handled by modifying workflow definitions, activity sequences, and configuration parameters at runtime. This provides high process flexibility while simplifying deployment and maintenance by separating workflow logic from software code.
Solution Approach 2:
The system provides pre-built workflow templates and activity libraries for common clinical data integration scenarios. These preliminary workflows can be customized and activated without full software deployment, reducing maintenance complexity while maintaining the ability to handle complex scenarios through configuration rather than code changes.
Data Source
AI summary
Systems and method are described to share large amounts of data in a secure and hierarchical manner across computer systems. The sharing process includes techniques to manage access to data and to manage physical storage locations throughout a hierarchy of computer systems. An intermediary level of storage may be provided to “cache” large data files to minimize repeated transfer of large data files throughout a given level of the hierarchy. For example, access from client devices will be served, when available, from an intermediary level rather than from a parent cloud system of stored data.