Statistical Information Integration Without Raw Data Exposure
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Solution Overview
Problem
Existing data integration methods for health care data, such as those in Patent Literatures 1-3, require data to be taken out of the organization, leading to potential data leaks and inability to construct accurate integration models when combining multiple data sets.
Innovation Solution
An integration device that acquires and integrates statistical information from multiple private environments without exposing the original data, using a processor to execute acquisition, integration, and output processing, allowing for the construction of an integration model without data loss.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is taken out of the organization for analysis, then statistical processing can be performed, but data security and personal information protection are compromised
Solution Approach 1:
The patent extracts only the necessary statistical information (aggregated data, model parameters) from the private data, leaving the original sensitive data within the organization. This allows statistical processing to be performed on extracted statistical information while the original data remains secure within the organization's premises.
Solution Approach 2:
The patent introduces statistical information as an intermediary between the private data and the analysis system. The statistical information serves as a mediator that carries the necessary analytical value without exposing the underlying sensitive data, enabling analysis while maintaining data security.
2Reliability
If pseudo data is used for integration modeling, then data security is maintained, but the accuracy of the integration model deteriorates
Solution Approach 1:
The patent transforms the raw private data into statistical information by changing the data parameters - aggregating individual records into summary statistics (counts, sums, averages). This parameter transformation maintains security while preserving the statistical properties needed for accurate integration modeling.
Solution Approach 2:
The patent creates a statistical information copy that represents the essential characteristics of the original data without being a direct replica. This statistical copy contains sufficient information for accurate modeling while being fundamentally different from the original sensitive data.
3Adaptability or versatility
If statistical information is integrated from multiple sources, then comprehensive analysis is enabled, but the complexity of integration increases
Solution Approach 1:
The patent segments the integration process into distinct stages: (1) each organization independently generates statistical information from its private data, (2) the integration device receives and processes these statistical information pieces, (3) integration is performed on the already-processed statistical information. This segmentation reduces overall complexity by distributing the processing burden.
Solution Approach 2:
The patent performs preliminary processing of data at each organization before integration - converting private data into statistical information locally. This preliminary action ensures that when integration occurs, the data is already in a standardized, processed format, significantly reducing the complexity of the integration operation itself.
Data Source
AI summary
Provided is an integration device that is accessible to statistical information based on analysis target data of each of a plurality of analysis target devices and includes a processor configured to execute a program and a storage device configured to store the program. The integration device executes acquisition processing of acquiring first statistical information and second statistical information from a plurality of pieces of statistical information, integration processing of integrating the first statistical information and the second statistical information acquired by the acquisition processing by statistical processing based on the number of first data of first analysis target data used for statistical processing of the first statistical information and the number of second data of second analysis target data used for statistical processing of the second statistical information, and output processing of outputting integration statistical information obtained by the integration processing.