Personalized Insulin Bolus Dosing With Continuous Glucose Sensing
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Solution Overview
Problem
Existing systems for managing insulin bolus doses in diabetes patients are inadequate in accurately determining and delivering precise bolus doses based on individual patient needs, leading to potential hyperglycemic or hypoglycemic events.
Innovation Solution
A system and method that utilizes a continuous glucose sensor to determine a bolus dose by receiving glucose concentration data, processing it with a set of configuration parameters, and displaying the dose through a user interface, optionally involving multiple question rounds to refine parameter settings and integrating with an insulin delivery system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing systems use standard bolus dose calculation methods, then the process is simple and quick, but the precision of bolus dose determination is insufficient leading to hyperglycemic or hypoglycemic events
Solution Approach 1:
The system performs preliminary configuration to obtain patient-specific parameters (insulin sensitivity factor, carbohydrate ratio, target glucose range) before actual bolus calculation. This pre-setup enables precise, personalized dose determination without complicating the moment-of-use process.
Solution Approach 2:
The system continuously receives glucose concentration data from sensors and uses this feedback to dynamically adjust bolus dose calculations. The closed-loop feedback mechanism ensures dose precision by adapting to real-time physiological states.
2Adaptability or versatility
If the system collects multiple patient parameters through multiple question rounds, then the adaptability to individual patient needs improves, but the time required for dose determination increases
Solution Approach 1:
Patient-specific parameters are collected during an initial configuration phase before actual bolus dosing occurs. This preliminary data collection enables personalized calculations without delaying acute dose determination, as the parameters are stored for rapid reuse.
Solution Approach 2:
The system maintains stored patient parameters and automatically retrieves them during dosing events without requiring repeated patient input. This self-service approach to parameter management eliminates redundant questioning while maintaining adaptability.
Data Source
AI summary
Various examples are directed to systems and methods for generating a bolus dose for a host. A bolus application may display a first bolus configuration parameter question at a user interface and receive, through the user interface, a first answer to the first bolus configuration parameter question. The first answer may describe a previous bolus determination technique of the host. The bolus application may select a second bolus configuration parameter question using the first answer and provide the second bolus configuration parameter question at the user interface. The bolus application may determine a set of at least one bolus configuration parameter using the first answer and a second answer to the second bolus configuration parameter question.