Rapid Cohort Analysis System for Health Insurance Data
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Solution Overview
Problem
Current methods for analyzing health insurance data are cumbersome, costly, and require excessive processing time, hindering effective disease management and insight into disease causes and cures.
Innovation Solution
A system and method for rapid cohort analysis that includes an interface and processor to search databases for specific record groups based on index attributes, calculate statistics, and aggregate data, enabling efficient identification of trends and insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional data mining methods are used to analyze health insurance data, then comprehensive statistical analysis can be performed, but the processing time and computational resources required become unworkably high
Solution Approach 1:
The patent segments the large-scale data analysis problem into multiple processing stages: (1) data loading and indexing phase that pre-processes and organizes data into efficient data structures, (2) cohort identification phase that quickly retrieves relevant record groups using the pre-built indexes, and (3) statistical calculation phase that computes results on the segmented, pre-organized data. This segmentation allows comprehensive statistical analysis while dramatically reducing processing time by avoiding full-scan operations.
Solution Approach 2:
The patent performs preliminary actions by pre-loading data into memory and pre-building index structures before actual analysis queries are executed. The system pre-organizes data into cohort-based groupings and creates efficient data structures that enable rapid retrieval during analysis. This preliminary preparation eliminates the need for time-consuming data scanning and processing during the actual statistical analysis phase.
2Loss of information
If comprehensive health insurance data is analyzed to gain insights into disease causes and cures, then valuable medical insights can be obtained, but the computational cost and resource requirements become excessive
Solution Approach 1:
The patent extracts and isolates specific cohorts (groups of patients with common characteristics) from the larger health insurance database. By identifying and extracting these relevant subgroups based on disease characteristics, demographics, or treatment patterns, the system focuses computational resources only on the necessary data subsets rather than processing the entire database. This extraction approach maintains comprehensive disease insight quality while significantly reducing computational resource requirements.
3Measurement precision
If detailed cohort analysis is performed on health insurance records, then accurate disease management insights can be achieved, but the system complexity and implementation difficulty increase
Solution Approach 1:
The patent implements self-service through automated cohort identification and analysis. The system automatically loads data, identifies relevant cohorts based on predefined or user-specified criteria, performs the statistical analysis, and generates results without requiring manual data processing or complex configuration. This automation maintains high cohort analysis accuracy while reducing system implementation complexity by encapsulating the complex operations into self-executing procedures.
Data Source
AI summary
An apparatus, system, and method for rapid cohort analysis. In one embodiment, the apparatus includes an interface and a processor. The interface may receive an identifier of a first index attribute. The processor may search the database for a first group of records associated with the first index attribute, search the database for a second group of records, each record in the second group of records sharing a common second index attribute with a record in the first group of records, but not associated with the first index attribute, and calculate a statistic in response to information associated with the first group of records and the second group of records.