Layered Patient Data Management for Personalized Glucose Control
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Solution Overview
Problem
Existing infusion pump systems struggle to provide personalized and context-sensitive glucose control due to variations in insulin response and patient-specific factors, lacking effective methods for predicting future physiological conditions and providing tailored therapy recommendations.
Innovation Solution
A system and method for patient-specific monitoring and prediction using sensing arrangements, user inputs, and prediction models to forecast future physiological conditions, combined with a database system that maintains and analyzes historical data to generate personalized therapy recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional infusion pump systems are used for glucose control, then the device complexity is low, but the ability to provide personalized and context-sensitive glucose control is insufficient
Solution Approach 1:
The system segments patient data into multiple logical layers (patient layer, lifestyle layer, therapy layer, diabetes management layer, diabetes knowledge layer) with each layer containing specific types of data. This segmentation allows the complex system to manage personalized glucose control by organizing data in manageable, queryable units while maintaining overall system adaptability.
Solution Approach 2:
The patent introduces a multi-dimensional database structure with five distinct logical layers that organize patient data differently from traditional single-dimension storage. This dimensional organization enables sophisticated querying and analysis capabilities for personalized glucose control without requiring complex processing at the device level.
2Measurement precision
If comprehensive patient data is collected and analyzed, then the therapy recommendation accuracy is improved, but the data processing time and system complexity increase
Solution Approach 1:
The system performs preliminary organization of patient data into a structured five-layer database framework in advance. By pre-organizing data into logical layers (patient, lifestyle, therapy, diabetes management, and diabetes knowledge layers) with defined relationships, the system enables rapid querying and analysis when therapy recommendations are needed, reducing real-time processing requirements.
3Productivity
If multiple logical layers are used in the database system, then the query efficiency for personalized recommendations is improved, but the database structure complexity increases
Solution Approach 1:
The database is segmented into five distinct logical layers, each serving a specific function: patient layer (demographics and medical history), lifestyle layer (diet and exercise data), therapy layer (insulin delivery records), diabetes management layer (glucose measurements and events), and diabetes knowledge layer (clinical guidelines and research). This segmentation enables efficient querying by allowing the system to access only relevant layers for specific queries rather than searching through a monolithic database structure.
Data Source
AI summary
Infusion devices and related medical devices, patient data management systems, and methods are provided for monitoring a physiological condition of a patient. An exemplary method of querying a database involves receiving an input query from a client device, identifying a logical layer of a plurality of different logical layers of the database for searching based at least in part on the input query, generating a query statement for searching the identified logical layer of the plurality of different logical layers of the database based at least in part on the input query, querying the identified logical layer of the database using the query statement to obtain result data, and providing a search result influenced by the result data.