Medical Data Workflow System with Message Broker Cleansing
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Solution Overview
Problem
Current infrastructure lacks an efficient method for securely transferring and normalizing large volumes of medical information from disparate healthcare sites to medical research facilities, where the data is represented in various formats, for storage in a production database.
Innovation Solution
A system and method for transferring medical information that involves receiving and parsing data into a standard format, using a message broker to stream and cleanse the information, and propagating it to a staging database before storage, with error identification and reporting capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If medical information is transferred from disparate healthcare sites to medical research facilities, then the quantity of data available for research increases, but the complexity of managing various data formats and standards increases
Solution Approach 1:
The patent introduces an intermediary system comprising a message broker, data store, staging database, and cleansing unit that mediates between diverse healthcare data sources and the research database. This intermediary infrastructure receives data in various formats from different healthcare sites, normalizes and cleanses the data, then transfers it to the research facility, thereby managing format diversity without increasing overall system complexity
Solution Approach 2:
The data transfer and processing system is segmented into distinct functional components: a message broker for receiving data, a data store for temporary holding, a staging database for normalization, and a cleansing unit for validation. This segmentation allows each component to handle specific aspects of data management independently, making the overall complex process manageable and maintainable
2Manufacturing precision
If medical information is normalized and cleansed before storage, then the quality and accuracy of stored data improves, but the processing time and complexity of the transfer process increases
Solution Approach 1:
The system performs normalization and cleansing actions preliminarily during the data transfer process itself, rather than as separate post-processing steps. The cleansing unit validates and normalizes data as it is being transferred from the staging database to the research database, ensuring data quality is established early in the workflow
Solution Approach 2:
The patent implements continuous data flow through the system where the message broker continuously receives messages, the data store continuously holds incoming data, the staging database continuously processes normalization, and the cleansing unit continuously validates data during propagation. This continuous processing minimizes idle time and maintains steady throughput throughout the data pipeline
3Reliability
If large volumes of medical information are transferred securely, then the reliability of data transfer improves, but the complexity of securing and managing the transfer infrastructure increases
Solution Approach 1:
The message broker and associated infrastructure are designed to handle multiple functions: receiving data from various healthcare sites, validating message formats, routing data to appropriate destinations, and managing secure transfer protocols. This multi-functionality consolidates what would otherwise require multiple separate systems into a single unified infrastructure, reducing overall complexity while maintaining security
Data Source
AI summary
A method and apparatus for information repository workflows enables the transfer of information between healthcare sites and medical research facilities. Large quantities of medical information may be directly transferred to an information repository or indirectly transferred to the repository through the use of pointers. The information is cleansed and normalized prior to storage in a production database within the repository. The cleansing process is conducted while ensuring integrity of the production database is maintained and while continuing to receive additional information transfers. Errors encountered during processing are logged and reported.