Health Information Message Archiving and Mining System
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Healthcare organizations face challenges in effectively archiving and mining vast amounts of health information exchanged among different computer systems, which limits their ability to gain insights into disease spread, patient health, and treatment correlations.
Innovation Solution
A system that utilizes a client-server network architecture to collect, archive, and mine health information messages using standards like HL7, DICOM, and XDS, employing data mining techniques to analyze and provide insights, and includes a message processing module for normalization, indexing, and transformation of data for efficient querying and reporting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If health information messages are archived and mined using data mining techniques, then valuable insights into disease spread, patient health, and treatment correlations can be obtained, but the complexity of the system increases due to the need for centralized archiving, data processing, and analysis infrastructure
Solution Approach 1:
The patent introduces a centralized archiving system and data mining infrastructure as an intermediary between healthcare computer systems and insight generation. This intermediary captures, stores, and processes health information messages, transforming raw data into valuable insights about disease spread, patient health, and treatment correlations without requiring changes to the existing healthcare systems
Solution Approach 2:
The archiving system is designed to handle multiple types of health information messages from various healthcare systems simultaneously. The data mining infrastructure performs multiple functions including capturing messages, storing them in archives, processing the data, and generating diverse insights across different healthcare domains
2Reliability
If a centralized platform is implemented to collect and analyze health information messages, then better patient care and population health monitoring can be achieved, but the difficulty of detecting and measuring data patterns increases due to the vast amount of information exchanged among different computer systems
Solution Approach 1:
The patent extracts specific patterns and relationships from the vast amount of health information messages through data mining techniques. The system identifies and extracts valuable insights such as disease spread patterns, patient health trends, and treatment correlations, separating meaningful patterns from the overwhelming volume of raw data exchange
Solution Approach 2:
The system performs preliminary data processing, normalization, and archiving of health information messages before analysis. By pre-processing and organizing the data in advance, the system reduces the complexity of pattern detection and measurement when insights are needed for patient care and population health monitoring
Data Source
AI summary
Messages having patient healthcare information are exchanged between various healthcare IT systems. The messages are formatted according to various specific healthcare communication standards. The standards enable communication of the patient healthcare information among the healthcare IT systems. The messages are collected into a repository. Data mining is performed on the collected messages in order to make health-related findings.