Handheld Glucose-Insulin Data Management Unit for Basal Insulin Adjustment
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Solution Overview
Problem
Conventional insulin therapy methods are complex and burdensome for patients and providers, requiring significant training and often leading to poor glycemic control due to difficulties in determining appropriate insulin dosages, especially for basal insulin adjustments.
Innovation Solution
A handheld glucose-insulin data management unit with an analyte test sensor, processor, and display that measures and collects blood glucose concentration values, performs safeguards against hypoglycemia, and recommends adjustments to basal insulin doses based on collected data, providing safety notifications and guiding users through the adjustment process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional insulin therapy methods are used, then insulin dosing can be performed, but the complexity of the method and device increases significantly
Solution Approach 1:
The system enables patients to independently perform basal insulin dose adjustments by automatically analyzing their own glucose data patterns. The device calculates recommended dose changes based on detected patterns without requiring external provider intervention for each adjustment, making the system self-serving for the patient's daily management needs.
Solution Approach 2:
The system continuously monitors glucose measurements and provides feedback through detected patterns that guide insulin dosing decisions. The feedback loop analyzes glucose data, identifies patterns indicating the need for dose adjustment, and recommends specific changes, creating a closed-loop control system that improves dosing accuracy while simplifying the process.
2Reliability
If detailed instructions and handwritten logs are used for insulin titration, then tracking is possible, but the ease of operation decreases
Solution Approach 1:
The system replaces the mechanical process of manual handwriting and paper-based tracking with electronic data capture and processing. Glucose measurements are automatically recorded and analyzed by the device, eliminating the need for patients to manually write logs and making the tracking process significantly easier while maintaining data accuracy.
Solution Approach 2:
The system creates an electronic copy of the paper-based insulin titration protocol and transforms it into an automated digital process. Instead of patients copying data onto paper forms, the device electronically captures, stores, and analyzes glucose data, reproducing the tracking function in a much simpler electronic format.
3Ease of operation
If patients independently determine insulin dosages, then autonomy is improved, but the risk of hypoglycemia increases
Solution Approach 1:
The system provides continuous feedback by monitoring glucose patterns and automatically detecting when adjustments are needed. This feedback mechanism guides patients in making safe dosing decisions, reducing hypoglycemia risk while maintaining autonomy by enabling patients to independently respond to their own glucose patterns with system-guided recommendations.
Solution Approach 2:
The system performs preliminary analysis of glucose data to identify patterns before patients make dosing decisions. By detecting patterns in advance and providing recommended adjustments beforehand, the system prepares patients with informed guidance, reducing the risk of unsafe independent dosing decisions while preserving patient autonomy.
Data Source
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AI summary
Described herein are various methods to ensure safety and the compliance of therapeutic diabetes protocols. The method can be achieved by performing safeguards against hypoglycemia of the user prior to any change in basal insulin dosage based on the plurality of data.