Dynamic Blood Glucose Reference Timing
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Solution Overview
Problem
Current methods for determining blood glucose reference sample times in insulin infusion therapy often follow a fixed schedule, which is not dynamically responsive to individual patient conditions, leading to inefficient glucose monitoring and potential glycemic excursions.
Innovation Solution
A processor-implemented method and system that dynamically determines the timing of blood glucose reference sample measurements based on continuous glucose sensor readings, considering factors like current glucose levels, rate of change, predicted values, and sensor reliability to tailor the frequency of metered blood glucose sample measurements to the patient's specific state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If fixed schedule blood glucose monitoring is used, then monitoring consistency is maintained, but monitoring efficiency decreases and unnecessary measurements increase
Solution Approach 1:
The patent implements dynamic adjustment of blood glucose monitoring frequency based on real-time sensor data and patient state. The system transitions from fixed-schedule monitoring to adaptive monitoring where the frequency of reference sample measurements is continuously adjusted according to glycemic stability, sensor reliability metrics, and rate of change indicators, thereby eliminating unnecessary measurements while maintaining safety.
Solution Approach 2:
The system changes the parameter of monitoring frequency from a static fixed value to a dynamic variable that adjusts based on multiple factors including sensor glucose readings, rate of change, predicted glucose values, and sensor reliability metrics. This parameter change enables the system to optimize monitoring efficiency by increasing frequency only when clinically necessary.
2Reliability
If frequent blood glucose sample measurements are taken, then glycemic control safety is improved, but patient burden and resource utilization worsen
Solution Approach 1:
The patent applies local quality by differentiating monitoring intensity based on specific patient states and risk factors. Rather than applying uniform frequent monitoring to all patients, the system identifies local conditions (such as rapid glucose changes, hypoglycemia risk, sensor malfunction indicators) and increases monitoring frequency only in those specific contexts, thereby maintaining safety while reducing overall patient burden.
Solution Approach 2:
The system implements feedback mechanisms where sensor glucose data, sensor reliability metrics, and patient responses to previous measurements are continuously fed back into the monitoring frequency determination algorithm. This feedback loop enables the system to maintain glycemic control safety by detecting when increased monitoring is needed while automatically reducing frequency when conditions are stable, thereby minimizing patient burden.
3Speed
If continuous glucose sensor monitoring is used, then real-time glucose tracking is improved, but measurement accuracy compared to metered samples decreases
Solution Approach 1:
The patent uses metered blood glucose samples as an intermediary reference standard to validate and calibrate continuous sensor measurements. The system strategically determines when reference samples are needed based on sensor reliability metrics, using these intermediary measurements to maintain accuracy while leveraging the speed advantage of continuous monitoring for real-time tracking between reference points.
Solution Approach 2:
The system applies partial action by using metered blood glucose samples only when necessary rather than continuously. The patent determines optimal timing for reference samples based on sensor performance indicators, applying the more accurate but invasive measurement method selectively rather than excessively, thereby maintaining overall measurement precision while preserving the benefits of continuous monitoring.
4Productivity
If adaptive monitoring frequency is implemented, then resource utilization is improved, but system complexity increases
Solution Approach 1:
The patent segments the monitoring system into distinct functional modules: sensor glucose measurement module, sensor reliability metric calculation module, reference sample timing determination module, and insulin infusion control module. This segmentation allows the complex adaptive algorithm to be implemented as coordinated subsystems, improving resource utilization while managing system complexity through modular design.
Data Source
AI summary
Techniques disclose herein relate to determining glucose reference sample times. The techniques may involve determining a first glucose reference sample measurement for a patient. The techniques may further involve determining timing information for obtaining a second glucose reference sample measurement based at least in part on readings from a continuous glucose sensor.