Glucose-Guided Insulin Titration for Personalized Dose Recommendations
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Solution Overview
Problem
Patients with diabetes face challenges in determining proper medication doses to maintain glucose levels within a target range, as interpreting analyte data and adjusting medication is time-consuming and burdensome for both patients and healthcare professionals.
Innovation Solution
A method for titrating medication doses using a processor to analyze glucose data, detect fasting periods, adjust schedules, and recommend dose changes based on glucose patterns and event counting analyses, implemented in a dose guidance system that includes algorithms executed on various electronic devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If patients manually monitor glucose levels and determine medication doses, then glucose control can be maintained, but the process becomes time-consuming and burdensome
Solution Approach 1:
The system enables self-service by allowing the glucose monitoring device to automatically analyze glucose data and generate medication dose recommendations without requiring patient intervention for dose calculation, thus maintaining glucose control while reducing the time burden on patients
Solution Approach 2:
The manual mechanical process of patients interpreting glucose data and determining doses is replaced by an automated electronic system that processes glucose data and generates dose recommendations, eliminating the time-consuming manual analysis while maintaining control reliability
2Reliability
If patients carefully monitor glucose levels and adjust medication, then hypoglycemia can be avoided, but interpreting analyte data becomes challenging
Solution Approach 1:
The system introduces an intermediary processing layer between glucose data collection and dose determination, where the processor automatically analyzes glucose patterns and translates complex analyte data into actionable dose recommendations, making the process easier while maintaining hypoglycemia avoidance
Solution Approach 2:
The system implements feedback by continuously monitoring glucose levels and using this information to generate real-time dose recommendations, automatically adjusting medication dosing based on measured glucose patterns to prevent hypoglycemia while simplifying the interpretation process
3Measurement precision
If healthcare professionals guide treatment using analyte data, then proper dosing can be determined, but the process remains complex and time-consuming
Solution Approach 1:
The complex manual process of healthcare professionals analyzing analyte data is replaced by automated electronic processing that performs pattern recognition and dose calculation, maintaining dosing accuracy while dramatically improving treatment guidance efficiency by eliminating manual data interpretation steps
Data Source
AI summary
Dose guidance systems and methods for titrating medication doses are described. The dose guidance system may receive glucose data from a continuous glucose monitor and may receive medication data related to medication administered by the user. The dose guidance system may initialize dose guidance parameters, recommend medication doses, titrate medication doses, and provide alerts based on the glucose data and medication data.


