Application US20190252079

SYSTEM AND METHOD FOR DECISION SUPPORT
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US20190252079

1. A system comprising: (6) (4)

a glucose concentration sensor configured to detect a host glucose concentration;

a communication circuit configured to receive the host glucose concentration from the glucose concentration sensor;

a memory circuit including a stored model; and

a processor configured to: receive host glucose concentration data sensed by the glucose concentration sensor;

determine a host state change associated with the host glucose concentration data;

determine a guidance message based at least in part on the host state change; and

delivering the guidance message through a user interface.

2. The system of claim 1, wherein the processor is further configured to determine that the host state change is atypical, wherein the determining of the guidance message is based at least in part on the atypicality of the state change. (0)

3. The system of claim 1, wherein determining the host state change comprises determining from a model that a low-probability state transition has occurred or is likely to occur, wherein the determining of the guidance message is based at least in part on the determination that the low-probability state transition has occurred or is likely to occur. (0)

4. The system of claim 1, wherein determining the host state change comprises identifying a likely transition to an undesirable host state and the guidance message is determined and delivered at a time such that the host can intervene to avoid the transition to the undesirable host state. (0)

5. The system of claim 1, wherein the system includes a mobile device, the mobile device including the memory circuit, and the processor. (1) (0)

8. The system of claim 1, further comprising an insulin delivery system. (0)

9. The system of claim 1, wherein the state change is from a first disease state describing a first host disease stage to a second disease state indicating a second host disease stage, wherein the processor is further configured go determine a second guidance message based at least in part on the second disease stage. (0)

10. A method of delivering physiologic glucose concentration management guidance comprising: (7) (5)

receiving a datum indicative of a glucose concentration;

determining a patient state by applying the datum to a model;

determining whether the patient state is atypical;

determining a guidance message based on the atypicality of the patient state; and

delivering the guidance message through a user interface.

11. The method of claim 10, wherein determining whether the patient state is atypical includes determining whether the patient state is atypical for a given set of conditions. (0)

12. The method of claim 10, wherein determining whether the patient state is atypical includes determining whether a low-likelihood state transition has occurred. (0)

13. The method of claim 10, wherein determining a guidance message includes determining whether a low-likelihood state transition is projected to occur. (0)

14. The method of claim 10, wherein determining a patient state includes determining a physiological state and a behavioral state and determining whether the physiological state is atypical for the determined behavioral state. (0)

15. The method of claim 10, wherein determining whether the patient state is atypical includes identifying a blood glucose concentration level that deviates from a controlled blood glucose concentration range a time or in a circumstance when blood glucose concentration is typically in a controlled range. (0)

16. The method of claim 10, wherein determining whether the patient state is atypical includes identifying a blood glucose concentration trend leading to a high or low blood glucose concentration state a time or in a circumstance when blood glucose concentration is typically in a controlled range. (0)

17. The method of claim 10, wherein determining whether the patient state is atypical includes anticipating a shift to a low blood glucose concentration state at a time or in a circumstance when blood glucose concentration is typically well controlled. (0)

18. A method of delivering physiologic glucose concentration management guidance comprising: (4) (4)

receiving a datum indicative of a glucose concentration;

determining a patient state by applying the datum to a model;

determining from the model that a low-probability state transition has occurred or is likely to occur; and

delivering through a user interface a guidance message based on the determination that the low-probability state transition has occurred or is likely to occur.

19. The method of claim 18, wherein the method includes determining that a low-probability state transition is likely to occur, wherein the guidance message provides advance notice of the low-probability state transition. (0)

20. The method of claim 18, wherein the low-probability physiologic state transition includes a transition to a low glucose concentration level or a high glucose concentration level. (0)

21. The method of claim 18, wherein determining a guidance message includes determining that the low-probability state transition is likely to occur at a time that is inconvenient. (2) (0)

24. The method of claim 18, wherein delivering the guidance message includes determining a time period when the patient or a caregiver is likely to be available to take action to prevent the low-probability state transition and delivering the guidance message during the determined time period. (2) (0)

28. A method of delivering physiologic glucose concentration management guidance comprising: (11) (5)

receiving a datum indicative of a glucose concentration;

receiving one or more behavioral, environmental or contextual inputs;

identifying a likely transition to an undesirable patient state by applying the datum and the one or more behavioral, environmental or contextual input to a model;

determining a guidance message based on the likely transition to an undesirable patient state; and

delivering the guidance message, wherein the guidance message is determined and delivered at a time such that the patient can intervene to avoid the transition to an undesirable patient state.

29. The method of claim 28, wherein receiving a behavioral, environmental or contextual input includes receiving accelerometer data. (0)

30. The method of claim 28, wherein receiving a behavioral, environmental or contextual input includes receiving information from a calendar about a scheduled event. (0)

31. The method of claim 28, wherein receiving a behavioral, environmental or contextual input includes receiving input from a user through a user interface. (0)

32. The method of claim 28, wherein receiving a behavioral, environmental or contextual input includes receiving information from a user about completion, initiation, or anticipation of exercise. (0)

33. The method of claim 28, wherein receiving a behavioral, environmental or contextual input includes detecting that a user is driving. (0)

34. The method of claim 28, wherein receiving one or more behavioral, environmental or contextual input includes receiving location information. (0)

35. The method of claim 28, wherein receiving one or more behavioral, environmental or contextual input includes receiving an ambient temperature or an ambient pressure. (0)

36. The method of claim 28, further comprising receiving a body temperature, heart rate, or respiration rate. (1) (0)

37. The method of claim 28, further comprising learning the model based upon one or more patterns of received information. (1) (0)

40. The method of claim 28, further comprising determining a user query and providing the user query to a user, wherein the behavioral, environmental or contextual input is received in response to the user query. (0)

41. The method of claim 28, wherein receiving a datum indicative of a glucose concentration includes receiving a datum from a continuous glucose concentration monitoring system. (0)

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Application US20190252079

SYSTEM AND METHOD FOR DECISION SUPPORT

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