Dynamic API Generation for Healthcare Data Integration
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Solution Overview
Problem
Existing technologies face challenges in efficiently leveraging electronic health records (EHRs) to improve patient outcomes, reduce costs, and provide improved services due to difficulties in accessing and integrating patient data across different healthcare systems.
Innovation Solution
A computer system that dynamically determines a portion of a database schema and automatically generates an API based on specified configurations, allowing for real-time access and integration of patient data without the need for predefined software or static schema representations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static schema representations and predefined software are used, then system complexity is reduced, but data accessibility and integration capability deteriorate
Solution Approach 1:
The patent implements dynamic schema determination where the system automatically discovers and adapts to database schema changes in real-time. The API generation system dynamically queries the database metadata, interprets the schema structure, and generates appropriate API definitions without requiring static pre-definition. This allows the system to adapt to changing data structures while maintaining automated operation.
Solution Approach 2:
The system performs self-service by automatically determining the database schema, generating API definitions, and updating itself without external intervention. The computer system autonomously interacts with the database, interprets the source code and schema information, and produces the necessary API configurations, eliminating the need for manual schema documentation and API creation.
2Manufacturing precision
If manual schema determination and API generation are performed, then manufacturing precision is improved, but productivity deteriorates
Solution Approach 1:
The patent replaces manual mechanical processes with automated computer-based systems. Instead of manually examining database schemas and writing API definitions, the system uses automated interpretation of database metadata and source code to generate precise schema representations and API definitions. This substitution maintains high accuracy while dramatically increasing productivity through automation.
Solution Approach 2:
The system introduces an intermediary computer system that acts as a mediator between the database and the application layer. This intermediary automatically determines the schema, generates API definitions, and manages the integration process, eliminating the need for manual intervention while ensuring accurate data integration through systematic processing.
3Adaptability or versatility
If dynamic schema determination is implemented, then adaptability is improved, but device complexity worsens
Solution Approach 1:
The patent segments the complex task of schema determination and API generation into distinct automated processing steps: querying database metadata, interpreting source code, analyzing schema structure, generating API definitions, and updating configurations. This segmentation makes the overall complex process manageable through systematic breakdown into discrete automated operations.
Solution Approach 2:
The computer system performs multiple functions within a single integrated platform: it determines database schemas, generates API definitions, updates configurations, and manages data integration. This multi-functionality consolidates what would otherwise require multiple separate tools and processes into one universal system, managing complexity through integration rather than proliferation of components.
Data Source
AI summary
A computer system that detects a change and automatically performs a remedial action associated with an application programming interface (API) for an application is described. During operation, the computer system may receive data from a second computer system that implements a data-query engine for a database and the data may be associated with the database. Then, the computer system may detect the change in the data based at least in part on one or more of: a schedule of when to check for the change; a location in the database associated with the data; expected content of the data; or a relationship between the data and additional data. When the change is detected, the computer system may perform the remedial action, where the remedial action includes providing a notification with information specifying a data element associated with the API that is affected by the change.