Blood Glucose Data Analysis System for Insulin Therapy Assessment
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Solution Overview
Problem
Current methods for managing diabetes, particularly multiple daily injection therapy, lack clear criteria for success or failure, leading to inadequate glycemic control and increased risk of hypoglycemia, and the vast data from continuous glucose monitors overwhelm both patients and healthcare professionals, making it difficult to determine the effectiveness of treatments.
Innovation Solution
A system and method that analyzes blood glucose data using a computing device to assess sufficiency, hypoglycemic risk, glycemic control, and variability, providing recommendations for therapy changes, such as switching from multiple daily injection therapy to continuous subcutaneous insulin infusion therapy based on calculated metrics like average testing frequency, Low Blood Glucose Index, and standard deviation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous glucose monitor data is collected to provide more complete glycemic control information, then measurement precision is improved, but device complexity increases and information overload occurs
Solution Approach 1:
The patent segments the continuous glucose monitor data into distinct analytical components: time in range metrics, glycemic variability metrics, hypoglycemia risk metrics, and glucose pattern recognition. This segmentation transforms the overwhelming continuous data stream into discrete, manageable categories that can be independently evaluated and presented to clinicians and patients.
Solution Approach 2:
The patent introduces an intermediary data processing system that acts as a mediator between the continuous glucose monitor and the end user. This intermediary automatically calculates complex metrics such as time in range, glycemic variability, and hypoglycemia risk, presenting simplified results that bridge the gap between raw data and actionable clinical insights.
2Ease of operation
If traditional HbA1c metrics are used for diabetes management, then ease of operation is maintained, but measurement precision of glycemic control is insufficient
Solution Approach 1:
The patent merges the simplicity of traditional HbA1c monitoring with the precision of continuous glucose monitoring by integrating multiple metrics into a comprehensive assessment system. It combines time in range data, glycemic variability measures, and hypoglycemia risk evaluation with traditional glycemic control assessment, maintaining ease of use while dramatically improving measurement precision.
3Measurement precision
If multiple daily injection therapy is implemented to improve glycemic control, then glycemic control improves, but hypoglycemic risk increases
Solution Approach 1:
The patent implements a feedback system that continuously monitors glucose levels and provides real-time information about hypoglycemia risk. By calculating hypoglycemia risk metrics and time below range data, the system provides feedback that allows patients and clinicians to adjust therapy to maintain glycemic control while minimizing hypoglycemic events.
Solution Approach 2:
The patent performs preliminary analysis of glucose patterns and hypoglycemia risk before critical events occur. By identifying trends and predicting potential hypoglycemic episodes based on historical data and current patterns, the system enables preventive actions to be taken before harmful hypoglycemic events occur.
Data Source
AI summary
A system and technique are enclosed for determining the effectiveness of a blood glucose therapy treatment. Examples of this technique include analyzing sufficiency of blood glucose data collected from a patient with a computing device, analyzing hypoglycemic risk based on the blood glucose data with the computing device, analyzing glycemic control for the blood glucose data with the computing device, analyzing glycemic variability of the blood glucose data with the computing device, and outputting results from said analyzing the sufficiency, said analyzing the hypoglycemic risk, said analyzing the glycemic control, and said analyzing the glycemic variability with the computing device.