Centralized Claims Querying with Standardized Record Aggregation
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Solution Overview
Problem
The challenge of managing and querying vast volumes of electronic records across disparate databases, particularly in healthcare, leads to inefficiencies, incomplete data access, and increased resource consumption due to lack of integration and standardization, which can result in suboptimal patient care and potential adverse drug interactions.
Innovation Solution
A centralized database query service aggregates records from various entities, maintains them in a standardized format, and facilitates queries by identifying alternative records through a machine learning engine, enabling efficient data access and communication between client devices and services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If records data are stored across multiple separate databases with no direct integration, then each entity can maintain its own data independently, but data access becomes difficult and time-consuming
Solution Approach 1:
The patent implements a centralized data warehouse that consolidates records from multiple disparate databases into a single integrated repository. This allows data to be aggregated from various sources (healthcare providers, insurers, pharmacies) while maintaining the ability to query and access consolidated information efficiently, resolving the contradiction between data independence and data access speed.
Solution Approach 2:
The patent introduces a standardized data format and intermediary processing layer that translates data from different source databases into a common structure. This intermediary mechanism enables seamless integration and querying across previously siloed systems without requiring direct connections between all entities, thus reducing data access time while preserving data independence.
2Adaptability or versatility
If records data are stored in non-standardized formats across different entities, then each entity can maintain its own data structure, but data consistency and completeness deteriorate
Solution Approach 1:
The patent applies parameter changes by transforming diverse data formats into a standardized structure within the centralized data warehouse. The system accepts data in various formats from different entities, then converts and normalizes them into a consistent standardized format, enabling both format flexibility during ingestion and data consistency during storage and querying.
Solution Approach 2:
The patent creates a universal data structure that can accommodate records from multiple sources with different formats. The standardized template serves as a multi-functional framework that can represent various types of healthcare records (claims, prescriptions, patient information) in a unified manner, ensuring data consistency across all entities while maintaining adaptability to different source formats.
3Reliability
If multiple entities maintain records on separate databases, then data ownership is preserved, but resource consumption increases due to redundant access attempts
Solution Approach 1:
The patent merges data access operations by implementing a centralized query interface that consolidates multiple access requests into single queries against the unified data warehouse. This eliminates redundant network traffic that would occur if entities independently accessed separate databases, reducing network bandwidth consumption while preserving each entity's data ownership through controlled access mechanisms.
Solution Approach 2:
The patent introduces an intermediary data warehouse layer that sits between multiple entities and their source databases. This intermediary consolidates data access operations, allowing entities to query the centralized repository rather than directly accessing multiple separate databases, thereby reducing network traffic and resource consumption while maintaining data ownership through authorized access protocols.
4Productivity
If data are aggregated from multiple sources into a centralized database, then data access efficiency improves, but system complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the system into distinct modular components: data collection modules from various entities, a standardized data transformation layer, a centralized data warehouse storage system, and a query interface. This segmentation allows each component to be developed and maintained independently, reducing overall system complexity while enabling efficient data access through the integrated architecture.
Data Source
AI summary
Presented herein are systems and methods for aggregating claims data. A database query service may aggregate record data from clients, provider services, and a multitude of other entities to store and maintain on a centralized database. The records 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 records data may also identify information for entities. The service may also establish a communication session to facilitate exchange of messages through an interface between a client device and provider services. The service may monitor for usage of an electronic device at the provider service.