System and method for decision support

Patent metadata

Field	Value
Publication number	US-11766194-B2
Application number	US-201916269480-A
Country	US
Kind code	B2
Filing date	Feb 6, 2019
Priority date	Feb 9, 2018
Publication date	Sep 26, 2023
Grant date	Sep 26, 2023

Abstract

Systems and methods are provided to provide guidance to a user regarding management of a physiologic condition such as diabetes. The determination may be based upon a patient glucose concentration level. The glucose concentration level may be provided to a stored model to determine a state. The guidance may be determined based at least in part on the determined state.

First claim

What is claimed is:

1. A system comprising:
a glucose concentration sensor configured to detect a glucose concentration level of a host;
a communication circuit configured to receive the glucose concentration level from the glucose concentration sensor; and
a processor configured to:
receive a real-time datum indicative of the glucose concentration level;
determine a temporal pattern of behavior of the host, an engagement state of the host with decision support guidance, a risk tolerance of the host, and an unavailability of the host to receive a guidance message, wherein:
the temporal pattern of behavior corresponds to a learned pattern of behavior of the host correlated to time;
the engagement state is determined based on a consistency and response time of the host responding to prior guidance messages as correlated to time;
the risk tolerance corresponds to at least one of:
a comfort of the host based on experience of the host with intervention; or
an availability of caregivers for intervention; and

the unavailability of the host is due to one or more of: a location of the host, a calendar event scheduled for the host, and the host being in a car;

predict, based on the temporal pattern and the engagement state, a time period during which the host will be unavailable to receive the guidance message;
predict, based on the real-time datum, that the glucose concentration level of the host will not be within a first range during the time period during which the host will be unavailable;
determine, based on the real-time datum, a risk level associated with the glucose concentration level of the host not being within the first range during the time period;
determine a content of the guidance message based at least in part on the real-time datum, the temporal pattern, and the engagement state, wherein the content of the guidance message is related to an action to be performed prior to the time period; and
provide the guidance message to the host prior to the time period, wherein providing the guidance message to the host is based on a function of the risk tolerance of the host, the risk level associated with the glucose concentration level of the host not being within the first range during the time period, and the unavailability of the host.

2. The system of claim 1 , further comprising a memory circuit configured to store a physiologic model, wherein the processor is further configured to determine a physiologic state of the host using the physiologic model and the real-time datum, and wherein the processor is configured to predict that the glucose concentration level of the host will not be within the first range further based on the physiologic state.

3. The system of claim 2 , wherein the content of the guidance message is further based at least in part on the physiologic state.

4. The system of claim 2 , wherein in determining the physiologic state, the processor is configured to determine an insulin state, an energy absorption state, or an energy expenditure state.

5. The system of claim 1 , further comprising a mobile device including a memory circuit, the processor, and a user interface configured to display the guidance message, wherein the mobile device is configured to receive user input through the user interface, and wherein the processor is configured to predict that the glucose concentration level of the host will not be within the first range further based on the user input.

6. The system of claim 1 , wherein the system includes a mobile device, the mobile device including a memory circuit and the processor, and wherein the mobile device includes a user interface configured to provide the guidance message, the system further comprising an insulin delivery system.

7. The system of claim 1 , wherein the processor is further configured to predict the time period based at least in part on an upcoming event in a calendar.

8. The system of claim 7 , wherein the processor is configured to predict that the glucose concentration level of the host will not be within the first range further based at least in part on a projected change in insulin sensitivity calculated based at least in part on the upcoming event in the calendar.

9. The system of claim 7 , wherein the processor is further configured to automatically receive event data about the upcoming event whenever the upcoming event is newly input by the host, and wherein the processor is configured to predict the time period based on the received event data.

10. The system of claim 1 , further comprising a memory configured to store a physiologic model, wherein the processor is configured to predict that the glucose concentration level of the host will not be within the first range further based at least in part on the physiologic model indicating that a transition to an undesirable physiologic state is likely to occur.

11. The system of claim 10 , the processor is further configured to determine an intervention to avoid the transition to the undesirable physiologic state; and wherein the content of the guidance message indicates the intervention.

12. The system of claim 1 , wherein the processor is further configured to determine a delivery time before the time period for delivery of the guidance message using the temporal pattern.

13. The system of claim 12 , wherein the processor is configured to select the delivery time when the host is likely to be available based at least in part on the temporal pattern.

14. The system of claim 1 , wherein the action is configured to promote glucose concentration stability during the time period.

15. The system of claim 1 , wherein the processor is further configured to:
determine a messaging frequency based at least in part on the engagement state; and
determine a time before the time period for delivering the guidance message based at least in part on the messaging frequency.

16. The system of claim 15 , wherein the processor is further configured to:
determine that the engagement state has changed to a changed engagement state;
determine a new messaging frequency based at least in part on the changed engagement state; and
determine a second time for delivering a second guidance message based at least in part on the new messaging frequency.

17. The system of claim 1 , wherein the time period is predicted further based on a behavioral input.

18. The system of claim 17 , wherein the behavioral input comprises patient activity information.

19. The system of claim 1 , wherein the processor is further configured to automatically adjust a predicted patient glucose concentration level of the host based on the real-time datum.

20. The system of claim 1 , wherein the processor is further configured to:
predict a second time period during which a caregiver of the host will be unavailable; and
provide the guidance message to the host or caregiver prior to the second time period.

21. The system of claim 1 , wherein the unavailability of the host to receive the guidance message further due to the host being asleep.

22. A method of delivering physiologic glucose concentration management guidance comprising:
receiving a real-time datum indicative of a glucose concentration level of a host, wherein the glucose concentration level is detected by a glucose concentration sensor;
determining a temporal pattern of behavior of the host, an engagement state of the host with decision support guidance, a risk tolerance of the host, and an unavailability of the host to receive

Assignees

• Dexcom Inc

Inventors

• Constantin Alexandra Elena
• Belliveau Scott M
• Bhavaraju Naresh C
• Blackwell Jennifer
• Cohen Eric
• Dattaray Basab
• Davis Anna Leigh
• Draeger Rian
• Garcia Arturo
• Gray John Michael
• Hampapuram Hari
• Heintzman Nathaniel David
• Jepson Lauren Hruby
• Johnson Matthew Lawrence
• Kamath Apurv Ullas
• Koehler Katherine Yerre
• Mayou Phil
• McBride Patrick Wile
• Mensinger Michael Robert
• Mikami Sumitaka
• Pal Andrew Attila
• Polytaridis Nicholas
• Pupa Philip Thomas
• Reihman Eli
• Simpson Peter C
• Walker Tomas C
• Wiedeback Daniel Justin
• Pai Subrai Girish
• Vogel Matthew T

Classifications

• A61B5/14532 Primary

  for measuring glucose, e.g. by tissue impedance measurement · CPC title

• A61B5/0022

  Monitoring a patient using a global network, e.g. telephone networks, internet · CPC title

• A61B5/01

  Measuring temperature of body parts {; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue} (clinical contact thermometers G01K13/20) · CPC title

• A61B5/02055

  Simultaneously evaluating both cardiovascular condition and temperature · CPC title

• A61B5/1118

  Determining activity level · CPC title