Real Time Management of Data Relating to Physiological Control of Glucose Levels

• US 20140344280A1
• Filed: 08/01/2014
• Published: 11/20/2014
• Est. Priority Date: 07/23/2009
• Status: Active Grant

• Current Assignee: Abbott Diabetes Care Incorporated (Abbott Laboratories Incorporated)
• Original Assignee: Abbott Diabetes Care Incorporated (Abbott Laboratories Incorporated)
• Inventors: Wei, Charles, Hayter, Gary Alan
• Granted Patent: US 10,872,102 B2
• Time in Patent Office: Days
• US Class Current: 707/740
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: A61M 2005/14208 with a programmable infusion control system, characterised by the infusion program
• CPC Class Codes: A61M 2205/3592 using telemetric means, e.g. radio or optical transmission
• CPC Class Codes: A61M 2205/52 with memories providing a history of measured variating parameters of apparatus or patient
• CPC Class Codes: A61M 2230/201 Glucose concentration
• CPC Class Codes: A61M 5/1723 using feedback of body parameters, e.g. blood-sugar, pressure measurement of body parameters A61B5/00
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 40/60 for the operation of medical equipment or devices
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

Continuous glucose monitoring (CGM) data and insulin delivery data are used to generate more reliable projected alarms related to a projected glucose levels. A memory stores endogenous data related to measurements of glucose level in a patient, and also stores exogenous data, such as insulin on board, both of which are used by a processor to create projected alarms. Profiles of CGM data are created for use in tuning patient-specific insulin data, such at basal rate, carb ratio, and insulin sensitivity. A processor searches for patterns in the data profiles and if found, recommended changes to patient-specific insulin data are provided to permit more accurate control over a patient'"'"'s glucose levels.

Claims

1. An integrated glucose management system, comprising:

a memory configured to store glucose measurement data, and to store exogenous data including attributes tagged to the stored glucose measurement data; and

a processor configured to implement computer-executable instructions to;

store the glucose measurement data into the memory during a defined time period;

tag the stored glucose measurement data with a corresponding exogenous attribute selected to identify the stored data as associated with a particular category of monitored condition;

compare a stored profile to detect a persistent pattern of measured glucose levels in a profile;

provide an output if the persistent pattern is detected in the profile; and

output a recommended change to medication data as a result of the detected persistent pattern;

wherein the processor configured to implement the computer-executable instructions is further configured to provide a modification to the medication data; and

further

wherein the processor configured to implement the computer-executable instructions is further configured to prioritize a recommended increase in carbohydrate intake lower than a recommended modification to medication delivery.

2. The integrated glucose management system of claim 1, wherein the medication data comprises one or more of a basal rate, a carb ratio, or an insulin sensitivity.

3. The integrated glucose management system of claim 1, wherein the profile includes one or more of a skip-meal profile, a meal test profile, or a correction bolus test profile.

4. The integrated glucose management system of claim 1, wherein the processor comprises a computer-executable instruction to determine a minimum number of profiles outside a safe range before providing the recommended change to the medication data.

5. The integrated glucose management system of claim 1, wherein the processor comprises a computer-executable instruction to compare the stored profile to detect the persistent pattern within a selected time period.

6. The integrated glucose management system of claim 1, wherein the processor comprises a computer-executable instruction to determine a recommendation for change of a basal rate, a carb ratio, or an insulin sensitivity does not exceed a predetermined amount.

7. The integrated glucose management system of claim 1, wherein the processor comprises a computer-executable instruction to store the glucose measurement data into the memory during the defined time period upon receiving a manual start signal or an automatic start control.

8. The integrated glucose management system of claim 1, wherein the tag includes at least one of meal data, breakfast data, high-fat meal data, or post-prandial data.

9. The integrated glucose management system of claim 1, wherein the glucose measurement data is obtained using a glucose sensor comprising a plurality of electrodes including a working electrode, wherein the working electrode comprises a glucose-responsive enzyme and a mediator, wherein at least one of the glucose-responsive enzyme and the mediator is chemically bonded to a polymer disposed on the working electrode, and wherein the at least one of the glucose-responsive enzyme and the mediator is crosslinked with the polymer.

10. A method, comprising:

storing glucose measurement data during a defined time period;

storing exogenous data including attributes tagged to the stored glucose measurement data;

tagging the stored glucose measurement data with a corresponding exogenous attribute selected to identify the stored data as associated with a particular category of monitored condition;

comparing a stored profile to detect a persistent pattern of measured glucose levels in a profile;

providing an output if the persistent pattern is detected in the profile;

generating a recommended change to a medication data based on the detected persistent pattern; and

prioritizing a recommended increase in carbohydrate intake lower than a recommended modification to medication delivery.

11. The method of claim 10, wherein the medication data comprises one or more of a basal rate, a carb ratio, or an insulin sensitivity.

12. The method of claim 10, wherein the profile includes one or more of a skip-meal profile, a meal test profile, or a correction bolus test profile.

13. The method of claim 10, further including determining a minimum number of profiles outside a safe range before providing the recommended change to the medication data.

14. The method of claim 10, wherein the profile for comparison was obtained within a selected time period.

15. The method of claim 10, further including determining that a recommendation for a change of a basal rate, a carb ratio, or an insulin sensitivity does not exceed a predetermined amount.

16. The method of claim 10, further including storing the glucose measurement data during the defined time period upon receiving a manual start signal or an automatic start control.

17. The method of claim 10, wherein the tag includes at least one of meal data, breakfast data, high-fat meal data, or post-prandial data.

18. The method of claim 10, wherein the glucose measurement data is obtained using a glucose sensor comprising a plurality of electrodes including a working electrode, wherein the working electrode comprises a glucose-responsive enzyme and a mediator, wherein at least one of the glucose-responsive enzyme and the mediator is chemically bonded to a polymer disposed on the working electrode, and wherein the at least one of the glucose-responsive enzyme and the mediator is crosslinked with the polymer.