Hospital Data Meta Model for Adaptable Business Intelligence Access
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Solution Overview
Problem
Business intelligence applications in hospitals face challenges in identifying and accessing relevant data due to the complexity of hospital environments, including diverse medical devices and changing data layouts, which hampers their ability to provide effective evaluations.
Innovation Solution
A data meta model that is configurable, updatable, and evolvable is used to identify and store data from medical devices, allowing business intelligence applications to negotiate with hospital data sources and adapt to changes in the hospital environment, thereby facilitating seamless data access and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If business intelligence applications directly access hospital data sources, then data access speed is improved, but adaptability to changing hospital environments deteriorates
Solution Approach 1:
The patent introduces a data meta model as an intermediary layer between business intelligence applications and hospital data sources. This mediator contains configurable representations of data sources, data attributes, and access paths that can be updated without modifying the applications themselves, thus maintaining both fast access and adaptability to environmental changes.
Solution Approach 2:
The system performs preliminary actions by pre-configuring and storing data source metadata, access paths, and attribute definitions in the data meta model before actual data access occurs. This preparation work enables rapid data retrieval while allowing the metadata to be updated in advance to reflect changes in the hospital environment.
2Measurement precision
If business intelligence applications are customized for each hospital setup, then measurement precision of relevant data is improved, but device complexity increases
Solution Approach 1:
The data meta model serves as a universal configuration framework that can represent multiple different hospital data sources, data formats, and organizational structures using a common model. This allows a single business intelligence application to work across diverse hospital environments by simply updating the meta model configurations rather than customizing each application.
Solution Approach 2:
The system achieves adaptability through parameter changes in the data meta model, where data source locations, access methods, and attribute definitions can be modified as parameters without changing the application structure. This allows precise adaptation to different hospital setups while maintaining a unified application architecture.
3Measurement precision
If manual code development is used to access hospital data, then data access accuracy is improved, but productivity decreases
Solution Approach 1:
The data meta model enables self-service data access by automatically providing configured access paths and data definitions to business intelligence applications. The system serves itself by maintaining the metadata that describes how to access data, eliminating the need for manual code development and continuous customization while preserving accurate data access.
Data Source
AI summary
A system and method for negotiating between a business intelligence application and one or more data sources. Business data from devices is received, identified and stored using a data meta model that is updated as devices and the hospital environment change. The data meta model allows the business intelligence application to negotiate with the hospital data sources to access relevant data for evaluations. The data meta model includes an object model that is configurable, updatable, adaptable, and evolvable over time.