Network Data Structure Extraction for Claims Data Integration

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Solution Overview

Problem

The challenge lies in efficiently querying and managing massive healthcare claims data across disparate databases maintained by various entities, which are often isolated and lack standard integration, leading to inefficiencies, incomplete data access, and potential harm due to irrelevant prescriptions.

Innovation Solution

A centralized database query service aggregates claims data using a standard template, applies heuristics and data mining to identify alternative prescriptions, and facilitates communication between entities to improve data access and prescription management.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If claims data are stored across multiple separate databases by different entities, then data volume and coverage are increased, but data integration and accessibility deteriorate

Engineering Contradiction:

Improvedata volumeVSAvoiddata integration

Core Design Contradiction:

Quantity of substanceVSDevice complexity

Solution Approach 1:

The patent merges multiple separate entity databases into a single centralized database that stores claims data from multiple sources (providers, pharmacies, insurers) in a unified structure, eliminating the need for complex inter-database integration while maintaining data from all entities

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The centralized database serves multiple functions: storing claims data, enabling querying across all entities, supporting collaborative filtering, and providing a universal access point for all stakeholders in the healthcare claims ecosystem

Inventive Principle:

Principle #6Universality (Multi-functionality)

2Adaptability or versatility

If collaborative filtering is used to query claims data, then data selection capability is improved, but data sparsity and irrelevance increase

Engineering Contradiction:

Improvedata selection capabilityVSAvoiddata sparsity

Core Design Contradiction:

Adaptability or versatilityVSLoss of information

Solution Approach 1:

The system pre-computes and stores similarity metrics and candidate matches in the centralized database before queries are executed, so that when a query arrives, the system can quickly retrieve pre-prepared results rather than computing from scratch, addressing the sparsity problem by having data ready in advance

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system uses feedback from query results to refine future searches and recommendations, learning from which claims data are relevant and which are not, thereby improving data selection capability while reducing sparsity through iterative refinement

Inventive Principle:

Principle #23Feedback

3Adaptability or versatility

If entities maintain separate databases, then data autonomy is preserved, but time and resource consumption increase

Engineering Contradiction:

Improvedata autonomyVSAvoidtime and resource consumption

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

Entities can independently contribute their claims data to the centralized database and independently query it for their needs, serving themselves without requiring complex inter-entity coordination or resource sharing agreements, thereby maintaining autonomy while reducing time and resource consumption

Inventive Principle:

Principle #25Self-service

4Loss of information

If multiple separate databases are queried, then data completeness is improved, but network bandwidth and computing resources are wasted

Engineering Contradiction:

Improvedata completenessVSAvoidnetwork bandwidth and computing resources

Core Design Contradiction:

Loss of informationVSLoss of energy

Solution Approach 1:

By consolidating all claims data into a single centralized database, the system eliminates the need to query multiple separate databases, thereby maintaining data completeness while avoiding the network bandwidth and computing resource waste associated with distributed queries

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS20250292881A1Systems and methods for extracting data structures in network environments to generate instructions

Publication Date: 2025.09.18 MOLAR SOLUTIONS INC D B A COUNTER HEALTH

AI summary

Presented herein are systems and methods for aggregating claims data. A database query service may aggregate claims data from patients, care providers, pharmacy services, and a multitude of other entities to store and maintain on a centralized database. The claims data may be stored and maintained as one or more data structures in accordance with a standard template across the database to facilitate access by the entities using the database. The claims data may also identify information for entities available for provision to address health conditions of patients. The service may also establish a communication session to facilitate exchange of messages through an interface between a patient and the entities. The service may monitor for usage of an electronic card at the pharmacy service.