Masked Data Record Access for Personalized Healthcare Selection
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Solution Overview
Problem
Current healthcare and other industries face challenges in selecting the most appropriate products, services, and providers for individuals due to biases and inefficiencies in data collection, leading to suboptimal treatment outcomes and increased costs.
Innovation Solution
The use of pangenetic data, combining genetic and epigenetic information, to determine associations between individual characteristics and successful outcomes with specific products, services, and providers, facilitating personalized selections through databases and statistical correlations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional data collection methods are used for selecting products, services, and providers, then the process is simpler to implement, but treatment outcomes are suboptimal and costs increase
Solution Approach 1:
The patent segments data collection into multiple specialized components: genetic data collection, epigenetic data collection, environmental data collection, and lifestyle data collection. Each component targets specific types of information, allowing the system to gather comprehensive data while maintaining manageable complexity through modular organization of data sources and analysis methods.
Solution Approach 2:
The patent introduces computational algorithms and statistical analysis systems as intermediaries between raw data collection and treatment selection. These intermediary processing layers transform complex multi-source data into actionable insights, enabling reliable treatment outcomes without requiring direct complex interactions between all data elements.
2Adaptability or versatility
If comprehensive genetic and epigenetic data is collected and analyzed, then personalized treatment selection improves, but data processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary data processing by pre-collecting and organizing genetic, epigenetic, environmental, and lifestyle data before treatment selection is needed. This advance preparation of comprehensive patient profiles enables rapid treatment matching when needed, reducing processing time during actual treatment selection while maintaining high personalized accuracy.
Solution Approach 2:
The patent transforms complex biological data into standardized parameters and statistical correlations that can be efficiently processed. By converting genetic sequences, epigenetic markers, and environmental exposures into quantifiable parameters with established statistical relationships to treatment outcomes, the system achieves both high adaptability and efficient processing.
3Reliability
If statistical correlations are used to determine associations between individual characteristics and outcomes, then treatment success rates improve, but the complexity of analysis increases
Solution Approach 1:
The patent develops universal statistical correlation methods that can analyze multiple types of data (genetic, epigenetic, environmental, lifestyle) using the same analytical framework. This multi-functional approach improves treatment success rates by comprehensively evaluating all relevant factors while avoiding the need for separate complex analysis systems for each data type.
Solution Approach 2:
The patent implements feedback mechanisms where treatment outcomes are fed back into the statistical correlation analysis to continuously refine and improve the relationships between individual characteristics and treatment success. This iterative feedback process enhances treatment success rates over time while the established statistical framework maintains analysis manageability.
Data Source
AI summary
A computer based method and system for masked data record access are presented in which data masks are applied to sensitive personal information so that non-masked portions of that information can be used in the selection of products, services and service providers for a consumer. In one application the method and system are utilized in the selection of healthcare products, services and providers based on pangenetic (genetic and epigenetic) and non-pangenetic information associated with the consumer.