Healthcare Data Aggregation via Standardized Intermediary Model
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Solution Overview
Problem
Healthcare data is often fragmented and not standardized, making it difficult for stakeholders to access comprehensive datasets for effective health outcomes, and users lack access to their own health data across disparate platforms and providers.
Innovation Solution
A system and method for collecting and standardizing healthcare data from various sources into a common data model, generating user healthcare profiles, identifying data gaps, and providing actionable insights and reports through graphical user interfaces, utilizing algorithms to enhance healthcare risk prevention and detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If healthcare data is collected from multiple data sources with various data models, then data comprehensiveness is improved, but data standardization and accessibility deteriorate
Solution Approach 1:
The patent introduces a standardized data model as an intermediary layer between multiple heterogeneous data sources and the applications that consume the data. This intermediary standardizes data from various sources (EHR systems, wearables, labs, pharmacies) into a common format, enabling comprehensive data aggregation while maintaining standardization. The standardized data model acts as a mediator that translates diverse input formats into a unified structure without requiring changes to the source systems.
2Adaptability or versatility
If data is fragmented across multiple platforms and providers, then data source diversity is improved, but user access to comprehensive health data deteriorates
Solution Approach 1:
The patent creates a universal data aggregation platform that can interface with multiple different data sources (various EHR systems, wearable devices, laboratories, pharmacies) through a common standardized data model. This multi-functional system serves diverse data sources while providing unified access to users through a single interface, eliminating the need for users to access each platform separately.
3Adaptability or versatility
If customized data models are used by healthcare applications, then application-specific functionality is improved, but interoperability and data sharing deteriorate
Solution Approach 1:
The patent segments the data architecture into two distinct layers: a standardized data collection layer that ensures interoperability across all sources, and an application layer that can implement customized data models for specific functionalities. The standardized layer maintains reliable data exchange and interoperability, while the application layer can customize data processing and presentation without compromising the underlying data interoperability.
Data Source
AI summary
Described herein are systems and methods for receiving healthcare data from a plurality data sources that generate and store data in various data model regimes, many of which are not standardized or are variants of a standard. The stored data may then be used to provide a plurality of customized execution environments and graphical user interfaces (GUIs) to users, based on each user's electronic healthcare records, insurance records, and wearable device data.