Insulin Dosage Adjustment Algorithm for Glycemic Balance
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Solution Overview
Problem
Current diabetes management systems, including glucose meters and insulin pumps, are inadequate in providing real-time, proactive adjustments to insulin dosages, leading to sub-optimal glycemic control due to infrequent healthcare professional visits and the inability to predict dynamic changes in insulin needs, particularly in response to activities like exercise, resulting in inefficient hypoglycemic event corrections.
Innovation Solution
A system comprising a processor and a computer-readable medium that stores and analyzes a patient's insulin dosage regimen, continuously updates based on blood glucose level measurements, tags measurements with identifiers, and determines adjustments to insulin components to maintain a desired balance point, reducing the frequency of hypoglycemic events without significantly reducing the total insulin dosage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time insulin dosage adjustments are implemented, then glycemic control is improved, but system complexity increases
Solution Approach 1:
The system enables self-service by automatically analyzing blood glucose measurements and adjusting insulin dosages without requiring constant healthcare professional intervention. The processor continuously monitors glucose levels, compares them against target ranges, and proactively modifies insulin components based on predefined algorithms, allowing the system to serve itself in maintaining glycemic balance.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring blood glucose measurements and using this information to adjust insulin dosages. The processor receives glucose data, evaluates it against target ranges and hypoglycemic event thresholds, and modifies insulin components accordingly. This closed-loop feedback ensures glycemic control is dynamically optimized based on real-time patient data.
2Reliability
If frequent healthcare professional visits are required for dosage adjustments, then dosage optimization is improved, but time loss increases
Solution Approach 1:
The system performs self-service by autonomously analyzing blood glucose data and adjusting insulin dosages without requiring frequent healthcare professional visits. The processor continuously monitors glucose measurements, identifies trends, and proactively modifies insulin components based on algorithmic decision-making, eliminating the need for constant professional intervention while maintaining dosage optimization.
Solution Approach 2:
The system applies preliminary action by proactively adjusting insulin dosages before hypoglycemic events occur or before glucose levels become problematic. The processor analyzes trends in blood glucose measurements and anticipates potential issues, making preventive adjustments to insulin components. This proactive approach avoids the need for reactive visits to healthcare professionals.
3Object-affected harmful factors
If insulin dosage is reduced to prevent hypoglycemic events, then patient safety is improved, but glycemic control deteriorates
Solution Approach 1:
The system implements dynamics by continuously and adaptively adjusting insulin dosages based on real-time blood glucose measurements and patient-specific parameters. Rather than using fixed dosages, the processor dynamically modifies insulin components in response to changing glucose trends, activity levels, and individual response patterns. This dynamic adjustment allows the system to prevent hypoglycemia while maintaining optimal glycemic control.
Solution Approach 2:
The system applies parameter changes by modifying various insulin dosage parameters (amount, timing, frequency, type) based on analyzed blood glucose data. The processor changes these parameters adaptively, adjusting insulin components to prevent hypoglycemic events while maintaining glycemic balance. Multiple parameters can be modified simultaneously or independently to achieve the desired balance.
4Reliability
If insulin components are adjusted frequently, then glycemic balance is improved, but device complexity increases
Solution Approach 1:
The system applies segmentation by dividing the insulin dosage into separate components (different types, timings, and amounts) that can be independently adjusted. The processor analyzes which specific component needs modification based on the blood glucose pattern, allowing targeted adjustments rather than changing the entire dosage regimen. This segmented approach simplifies the adjustment process while maintaining glycemic balance.
Data Source
AI summary
Systems, methods and/or devices for optimizing a patient's insulin dosage regimen over time, comprising at least a first memory for storing data inputs corresponding at least to one or more components in a patient's present insulin dosage regimen, and data inputs corresponding at least to the patient's blood-glucose-level measurements determined at a plurality of times, and a processor operatively connected to the at least first memory. The processor is programmed at least to determine from the data inputs corresponding to the patient's blood-glucose-level measurements determined at a plurality of times whether and by how much to vary at least one of the one or more components in the patient's present insulin dosage regimen. Also disclosed are systems, methods and/or devices for treating a patient's diabetes by providing treatment guidance, wherein the patient's current glycemic state is determined relative to a desired balance point; and determining from at least one of a plurality of the data corresponding to the patient's blood glucose-level measurements whether and by how much to vary at least one of the one or more components in the patient's present insulin dosage regimen to get closer to the patient's desired balance point; wherein the desired balance point is the patient's lowest blood glucose-level within a predetermined range achievable before increasing the frequency of hypoglycemic events above a predetermined threshold.