Basal Insulin Parameter Adjustment via Delivery Record Analysis
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Solution Overview
Problem
People with Type 1 diabetes face challenges in determining optimal clinical parameters for insulin delivery, leading to inefficiencies and potential health risks due to manual adjustments and outdated open loop parameters.
Innovation Solution
A device with a processor, memory, wireless communication, and an artificial pancreas application that determines the total insulin delivered, calculates the proportion of basal insulin, and adjusts the basal dosage to maintain an optimal average delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual adjustment of clinical parameters is used, then ease of operation is improved, but measurement precision and reliability of insulin delivery parameters deteriorate
Solution Approach 1:
The system performs self-optimization by automatically analyzing insulin delivery records and adjusting basal parameters without requiring manual intervention. The processor evaluates delivery data, identifies optimization opportunities, and modifies parameters autonomously, allowing the system to serve itself rather than relying on manual user adjustment.
Solution Approach 2:
The system implements closed-loop feedback by continuously monitoring insulin delivery records, comparing actual delivery against target parameters, and using this information to automatically adjust basal settings. This feedback mechanism ensures that parameters are constantly optimized based on real delivery data rather than remaining static or manually adjusted.
2Device complexity
If open loop parameters are not updated, then device complexity is reduced, but reliability of insulin delivery deteriorates due to outdated parameters
Solution Approach 1:
The system performs preliminary analysis of insulin delivery records to identify trends and optimization opportunities before making parameter adjustments. By proactively evaluating delivery data and predicting optimal parameter values in advance, the system maintains reliability without requiring complex real-time manual intervention.
Solution Approach 2:
The system automatically updates its own parameters by analyzing delivery records and adjusting basal settings without external intervention. This self-service capability maintains parameter accuracy and reliability while avoiding the complexity of manual update procedures.
3Productivity
If automated insulin delivery systems are used, then productivity of glucose control is improved, but adaptability to individual user needs deteriorates due to rigid algorithms
Solution Approach 1:
The system transitions from static algorithms to dynamic parameter adjustment by continuously adapting basal settings based on actual insulin delivery records. The processor modifies parameters in response to real delivery data, enabling the automated system to adapt to individual user needs while maintaining high productivity in glucose control.
Solution Approach 2:
The system automatically modifies delivery parameters by analyzing insulin delivery records and adjusting basal parameters accordingly. This parameter change capability allows the automated delivery system to adapt to individual user patterns and needs while maintaining the productivity benefits of automation.
Data Source
AI summary
Disclosed are techniques and a device operable to determine a total amount of insulin delivered to the user over a predetermined time period. The total amount of insulin includes a total basal dosage delivered in basal dosages and a total bolus dosage delivered in bolus dosages over the predetermined time period. A proportion of the total amount of insulin delivered to the user provided via the total basal dosage amount over the predetermined time period is calculated. In response determining the proportion of the total amount of insulin attributed to the total basal dosage amount of insulin exceeds a threshold, an average basal dosage to be delivered within a subsequent time period that is approximately equal to the threshold may be determined. An instruction may be generated and output to deliver a modified basal dosage that substantially maintains the average basal dosage over the subsequent time period.