Diabetes therapy management system for recommending bolus calculator adjustments

• US 10,391,242 B2
• Filed: 06/05/2013
• Issued: 08/27/2019
• Est. Priority Date: 06/07/2012
• Status: Active Grant

• Current Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Original Assignee: Medtronic Minimed Incorporated (Medtronic Plc)
• Inventors: Agrawal, Pratik, Kannard, Brian T., Kaufman, Francine R.
• Primary Examiner(s): Lam, Eliza A
• Application Number:
  US13/910,766
• Publication Number:
  US 20130345663A1
• Time in Patent Office: 2,274 Days
• Field of Search: 705 2- 3
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• 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: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 40/63 for local operation
• 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 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

A method of managing use of an insulin infusion device is presented here. The method identifies bolus calculator event data from glucose data for a user of the infusion device. The bolus calculator event data corresponds to use of a bolus calculator that calculates bolus dosage recommendations based on a user entered carbohydrate consumption value, a user entered current blood glucose value, a user specific carbohydrate ratio value, and a user specific insulin sensitivity value. The method filters the bolus calculator event data to remove glucose data associated with certain conditions, and analyzes the filtered data to detect an event occurrence that is indicative of potential maladjustment of the carbohydrate ratio value or the insulin sensitivity value. The method outputs a recommendation to adjust the carbohydrate ratio value or the insulin sensitivity value, based on characteristics of the detected event occurrence.

Claims

1. An insulin infusion system comprising:

an insulin infusion device; and

an electronic device comprising;

a processor device; and

at least one memory element associated with the processor device, the at least one memory element storing processor-executable instructions that, when executed by the processor device, perform a method of managing use of the insulin infusion device, the method comprising;

receiving glucose data for a user of the insulin infusion device, the glucose data indicating blood glucose levels of the user for a plurality of days and for periods of time during which the insulin infusion device is regulating delivery of insulin to the user;

reviewing the received glucose data to identify bolus calculator event data corresponding to use of a bolus calculator of the insulin infusion device, wherein the reviewing uses a pattern recognition technique on the received glucose data, wherein the bolus calculator calculates each bolus dosage recommendation based on a respective user-entered carbohydrate consumption value, a respective user-entered current blood glucose value, a user-specific insulin sensitivity value, and a user-specific carbohydrate ratio value;

filtering the identified bolus calculator event data to isolate correction bolus events having no food bolus component or a minimal food bolus component, wherein the filtering uses a pattern recognition technique on the identified bolus calculator event data;

filtering the identified bolus calculator event data to isolate food bolus events having no correction bolus component or a minimal correction bolus component, wherein the filtering uses a pattern recognition technique on the identified bolus calculator event data;

analyzing the isolated correction bolus events to check for event occurrences that are indicative of potential maladjustment of the insulin sensitivity value;

analyzing the isolated food bolus events to check for event occurrences that are indicative of potential maladjustment of the carbohydrate ratio value;

wherein event occurrences are checked in a predetermined sequence, utilizing a prioritization scheme to ensure that conflicting recommendations are not provided and to make only one recommendation at a time;

determining, based on the analyzing and the prioritization scheme, that a particular recommendation corresponding to a detected event occurrence is needed;

outputting a first recommendation and one or more commands to the insulin infusion device to adjust the insulin sensitivity value in response to the determining, and in response to detection of an event occurrence indicative of potential maladjustment of the insulin sensitivity value; and

outputting a second recommendation and one or more commands to the insulin infusion device to adjust the carbohydrate ratio value in response to the determining, and in response to detection of an event occurrence indicative of potential maladjustment of the carbohydrate ratio value;

wherein the insulin infusion device automatically adjusts the insulin sensitivity value in accordance with the one or more commands for the first recommendation, or automatically adjusts the carbohydrate ratio value in accordance with the one or more commands for the second recommendation, and

wherein the predetermined sequence includes checks performed in the following order;

(1) check for long term hypoglycemia, post-bolus;

(2) check for short term hypoglycemia, post-bolus;

(3) check for long term high glycemic variability;

(4) check for short term high glycemic variability;

(5) check for long term hyperglycemia; and

(6) check for short term hyperglycemia.

2. The insulin infusion system of claim 1, wherein the received glucose data comprises sensor glucose data obtained from a continuous glucose monitor sensor.

3. The insulin infusion system of claim 1, wherein the outputting comprises:

generating a report that includes the recommendation.

4. The insulin infusion system of claim 1, wherein the method performed by the processor-executable instructions further comprises:

filtering the identified bolus calculator event data to remove glucose data associated with an override of a bolus dosage recommendation, an active insulin condition, or a back-to-back bolus condition, resulting in filtered bolus calculator event data;

wherein the analyzing step analyzes the filtered bolus calculator event data.

5. The insulin infusion system of claim 1, wherein:

the detected event occurrence comprises a long term hypoglycemic event occurring after a food bolus event; and

the recommendation comprises a suggestion to increase the carbohydrate ratio value.

6. The insulin infusion system of claim 1, wherein:

the detected event occurrence comprises a long term hyperglycemic event occurring after a food bolus event; and

the recommendation comprises a suggestion to decrease the carbohydrate ratio value.

7. The insulin infusion system of claim 1, wherein:

the detected event occurrence comprises a limited increase or decrease in blood glucose level occurring at a designated time after a food bolus event; and

the recommendation comprises a suggestion to increase the carbohydrate ratio value.

8. The insulin infusion system of claim 1, wherein:

the detected event occurrence comprises a large increase in blood glucose level occurring at a designated time after a food bolus event; and

the recommendation comprises a suggestion to decrease the carbohydrate ratio value.

9. The insulin infusion system of claim 1, wherein:

the detected event occurrence comprises a long term hypoglycemic event occurring after a correction bolus event; and

the recommendation comprises a suggestion to increase the insulin sensitivity value.

10. The insulin infusion system of claim 1, wherein:

the detected event occurrence comprises a long term hyperglycemic event occurring after a correction bolus event; and

the recommendation comprises a suggestion to decrease the insulin sensitivity value.

11. The insulin infusion system of claim 1, wherein:

the detected event occurrence comprises a rapid decrease in blood glucose level occurring at a designated time after a correction bolus event; and

the recommendation comprises a suggestion to increase the insulin sensitivity value.

12. The insulin infusion system of claim 1, wherein:

the detected event occurrence comprises a limited decrease or increase in blood glucose level occurring at a designated time after a correction bolus event; and

the recommendation comprises a suggestion to decrease the insulin sensitivity value.

13. The insulin infusion system of claim 1, wherein:

the detected event occurrence comprises a long term high glucose variability event occurring after a food bolus event; and

the recommendation comprises a suggestion related to dietary habits of the user.

14. The insulin infusion system of claim 1, wherein:

the detected event occurrence comprises a high glucose variability event occurring at a designated time after a food bolus event; and

the recommendation comprises a suggestion related to dietary habits of the user.

15. The insulin infusion system of claim 1, wherein:

the detected event occurrence comprises a high negative rate of change event occurring at a food bolus event; and

the recommendation comprises a suggestion to consume a meal earlier, relative to a corresponding food bolus infusion time.

16. The insulin infusion system of claim 1, wherein:

the detected event occurrence comprises a high positive rate of change event occurring at a food bolus event; and

the recommendation comprises a suggestion to consume a meal later, relative to a corresponding food bolus infusion time.

17. The insulin infusion system of claim 1, wherein:

the detected event occurrence comprises a long term high glucose variability event occurring after a correction bolus event; and

the recommendation comprises a suggestion related to use of a glucose meter and a glucose sensor.

19. The insulin infusion system of claim 1, wherein:

the detected event occurrence comprises a high glucose variability event occurring at a designated time after a correction bolus event; and

the recommendation comprises a suggestion related to use of a glucose meter and a glucose sensor.

18. A method of managing use of an insulin infusion device, the method comprising:

identifying bolus calculator event data from glucose data for a user of the insulin infusion device, the identified bolus calculator event data corresponding to use of a bolus calculator of the insulin infusion device over a plurality of days, wherein the identifying uses a pattern recognition technique on the glucose data, wherein the bolus calculator calculates each bolus dosage recommendation based on a respective user-entered carbohydrate consumption value, a respective user-entered current blood glucose value, a user-specific carbohydrate ratio value, and a user-specific insulin sensitivity value;

filtering the identified bolus calculator event data to remove glucose data associated with an override of a bolus dosage recommendation, an active insulin condition, or a back-to-back bolus condition, resulting in filtered bolus calculator event data, and to isolate correction bolus events having no food bolus component or a minimal food bolus component, and to isolate food bolus events having no correction bolus component or a minimal correction bolus component, wherein the filtering uses a pattern recognition technique on the identified bolus calculator event data;

analyzing the filtered bolus calculator event data to check for event occurrences that are indicative of potential maladjustment of the user-specific carbohydrate ratio value or the user-specific insulin sensitivity value, wherein event occurrences are checked in a predetermined sequence, utilizing a prioritization scheme to ensure that conflicting recommendations are not provided and to make only one recommendation at a time;

determining, based on the analyzing and the prioritization scheme, that a particular recommendation corresponding to a detected event occurrence is needed;

outputting the particular recommendation and one or more commands to the insulin infusion device to adjust the user-specific carbohydrate ratio value or the user-specific insulin sensitivity value, based on characteristics of the detected event occurrence; and

automatically adjusting the carbohydrate ratio value or the insulin sensitivity value at the insulin infusion device, in accordance with the one or more commands;

wherein the predetermined sequence includes checks performed in the following order;

(1) check for long term hypoglycemia, post-bolus;

(2) check for short term hypoglycemia, post-bolus;

(3) check for long term high glycemic variability;

(4) check for short term high glycemic variability;

(5) check for long term hyperglycemia; and

(6) check for short term hyperglycemia.

20. The method of claim 18, wherein the outputting comprises:

generating a report that includes the particular recommendation.

21. The method of claim 18, wherein:

the detected event occurrence comprises a long term hypoglycemic event occurring after a food bolus event; and

the particular recommendation comprises a suggestion to increase the carbohydrate ratio value.

22. The method of claim 18, wherein:

the detected event occurrence comprises a long term hyperglycemic event occurring after a food bolus event; and

the particular recommendation comprises a suggestion to decrease the carbohydrate ratio value.

23. The method of claim 18, wherein:

the detected event occurrence comprises a limited increase or decrease in blood glucose level occurring at a designated time after a food bolus event; and

the particular recommendation comprises a suggestion to increase the carbohydrate ratio value.

24. The method of claim 18, wherein:

the detected event occurrence comprises a large increase in blood glucose level occurring at a designated time after a food bolus event; and

the particular recommendation comprises a suggestion to decrease the carbohydrate ratio value.

25. The method of claim 18, wherein:

the detected event occurrence comprises a high glucose variability event occurring after a food bolus event; and

the particular recommendation comprises a suggestion related to dietary habits of the user.

26. The method of claim 18, wherein:

the detected event occurrence comprises a long term hypoglycemic event occurring after a correction bolus event; and

the particular recommendation comprises a suggestion to increase the insulin sensitivity value.

27. The method of claim 18, wherein:

the detected event occurrence comprises a long term hyperglycemic event occurring after a correction bolus event; and

the particular recommendation comprises a suggestion to decrease the insulin sensitivity value.

28. The method of claim 18, wherein:

the detected event occurrence comprises a rapid decrease in blood glucose level occurring at a designated time after a correction bolus event; and

the particular recommendation comprises a suggestion to increase the insulin sensitivity value.

29. The method of claim 18, wherein:

the detected event occurrence comprises a limited decrease or increase in blood glucose level occurring at a designated time after a correction bolus event; and

the particular recommendation comprises a suggestion to decrease the insulin sensitivity value.

30. The method of claim 18, wherein:

the detected event occurrence comprises a high glucose variability event occurring at a designated time after a food bolus event; and

the particular recommendation comprises a suggestion related to dietary habits of the user.

31. The method of claim 18, wherein:

the detected event occurrence comprises high negative rate of change event occurring at a food bolus event; and

the particular recommendation comprises a suggestion to consume a meal earlier, relative to a corresponding bolus infusion time.

32. The method of claim 18, wherein:

the detected event occurrence comprises a high positive rate of change event occurring at a food bolus event; and

the particular recommendation comprises a suggestion to consume a meal later, relative to a bolus infusion time.

33. The method of claim 18, wherein:

the detected event occurrence comprises a long term high glucose variability event occurring after a correction bolus event; and

the particular recommendation comprises a suggestion related to use of a glucose meter and a glucose sensor.

34. The method of claim 18, wherein:

the detected event occurrence comprises a high glucose variability event occurring at a designated time after a correction bolus event; and

the particular recommendation comprises a suggestion related to use of a glucose meter and a glucose sensor.