Multi-state engagement with continuous glucose monitoring systems

Patent metadata

Field	Value
Publication number	US-12558003-B2
Application number	US-202017114182-A
Country	US
Kind code	B2
Filing date	Dec 7, 2020
Priority date	Dec 16, 2019
Publication date	Feb 24, 2026
Grant date	Feb 24, 2026

Abstract

Multi-state engagement with continuous glucose monitoring (CGM) systems is described. Given the number of people that wear CGM systems and because CGM systems produce measurements continuously, a platform that provides a CGM system may have an enormous amount of data. This amount of data is practically, if not actually, impossible for humans to process. In implementations, a CGM platform includes a data analytics platform that obtains packages of glucose measurements provided by a CGM system and also obtains additional data associated with a user. The data analytics platform generates state information for the user by processing these CGM packages and the additional data, at least in part, by using one or more models. Based on this state information, the data analytics platform controls communication with the user, which may include generating intervention strategies to prevent users from transitioning to a negative state such as discontinuing use of the CGM system.

First claim

What is claimed is:

1 . A method comprising:
obtaining, over a network, data describing health-related online activity with one or more websites or social networks from a computing device of a user wearing a continuous glucose monitoring system, the data comprising search queries related to diabetes; generating a feature vector based on the data; generating, using a state engagement model, state information for the user based on the feature vector, the state information including at least a predicted engagement state of the user with the continuous glucose monitoring system, wherein the predicted engagement state is one of a plurality of engagement states, and the plurality of engagement states comprises an active use state, an erratic use state, and a discontinued use state; customizing health-related digital content for the user based on the predicted engagement state; sending, over the network, the health-related digital content to the computing device for display to the user; and when the predicted engagement state is the erratic use state or the discontinued use state, monitoring glucose data received from the continuous glucose monitoring system.

2 . The method as described in claim 1 , wherein the engagement state model is a machine learning model that is trained to predict the engagement states based on data describing health-related online activity obtained from a user population.

3 . The method as described in claim 1 , wherein:
the active use state is associated with using the continuous glucose monitoring system by the user; the erratic use state is associated with a decline in a level of use of the continuous glucose monitoring system by the user; and the discontinued use state is associated with discontinued use of the continuous glucose monitoring system by the user.

4 . The method as described in claim 3 , wherein:
the data further comprise navigation to diabetes-related websites, interactions with diabetes-related mobile applications, and interactions with diabetes-related social networks; and the health-related digital content includes information pertaining to using the continuous glucose monitoring system.

5 . The method as described in claim 1 , wherein the health-related digital content is displayed in a user interface of the one or more websites or social networks.

6 . The method as described in claim 1 , wherein the computing device is a mobile phone or a smart watch of the user.

7 . The method as described in claim 1 , wherein the health-related digital content is displayed as a text message or an email message.

8 . The method as described in claim 1 , wherein the health-related digital content comprises information regarding:
the continuous glucose monitoring system; ease of using the continuous glucose monitoring system to improve user health; how to contact customer support representatives of the continuous glucose monitoring system; health conditions that arise due to diabetes; or how to contact medical providers.

9 . One or more computer-readable storage media having instructions stored thereon that are executable by one or more continuous glucose monitoring platform server processors to perform operations, the operations comprising:
obtaining, over a network, data describing health-related online activity with one or more websites or social networks from a computing device of a user wearing a continuous glucose monitoring system, the data comprising search queries related to diabetes; generating a feature vector based on the data; generating, using a state engagement model, state information for the user based on the feature vector, the state information including at least a predicted engagement state of the user with the continuous glucose monitoring system, wherein the predicted engagement state is one of a plurality of engagement states, and the plurality of engagement states comprises an active use state, an erratic use state, and a discontinued use state; customizing health-related digital content for the user based on the predicted engagement state; and sending, over the network, the health-related digital content to the computing device for display to the user, when the predicted engagement state is the erratic use state or the discontinued use state, monitoring glucose data received from the continuous glucose monitoring system.

10 . The one or more computer-readable storage media as described in claim 9 , wherein the engagement state model is a machine learning model that is trained to predict the engagement states based on data describing health-related online activity obtained from a user population.

11 . The one or more computer-readable storage media as described in claim 9 , wherein:
the active use state is associated with using the continuous glucose monitoring system by the user; the erratic use state is associated with a decline in a level of use of the continuous glucose monitoring system by the user; and the discontinued use state is associated with discontinued use of the continuous glucose monitoring system by the user.

12 . The one or more computer-readable storage media as described in claim 11 , wherein:
the data further comprise navigation to diabetes-related websites, interactions with diabetes-related mobile applications, and interactions with diabetes-related social networks; and the health-related digital content includes information pertaining to using the continuous glucose monitoring system.

13 . The one or more computer-readable storage media as described in claim 9 , wherein the health-related digital content is displayed in a user interface of the one or more websites or social networks.

14 . The one or more computer-readable storage media as described in claim 9 , wherein the computing device is a mobile phone or a smart watch of the user.

15 . The one or more computer-readable storage media as described in claim 9 , wherein the health-related digital content is displayed as a text message or an email message.

16 . The one or more computer-readable storage media as described in claim 9 , wherein the health-related digital content comprises information regarding:
the continuous glucose monitoring system; ease of using the continuous glucose monitoring system to improve user health; how to contact customer support representatives of the continuous glucose monitoring system; health conditions that arise due to diabetes; or how to contact medical providers.

17 . A system comprising:
a continuous glucose monitoring system worn by a user; a computing device coupled to a network; and a continuous glucose monitoring server coupled to the network, the continuous glucose monitoring server comprising:
at least one memory; and
a processor coupled to the memory and configured to perform operations, the operations comprising:
obtaining, from the computing device over the network, data describing health-related online activity with one or more websites or social networks by the user, the data comprising search queries related to diabetes;
generating a feature vector based on the data;
generating, using a state engagement model, state information for the user based on the feature vector, the state information including at least a predicted engagement state of the user with the continuous glucose monitoring system, wherein the predicted engagement state is one of a plurality of engagement states, and the plurality of engagement states comprises an active use state, an erratic use state, and a discontinued use state;
customizing health-rela

Assignees

• Dexcom Inc

Inventors

• Parker Andrew Scott
• Jimenez Annika Emilie Kristina
• Patterson Chad
• Pai Subrai Girish
• Kamath Apurv Ullas

Classifications

• A61B5/7475

  User input or interface means, e.g. keyboard, pointing device, joystick · CPC title

• A61B5/742

  using visual displays (displays for heart-related electrical signals, e.g. ECG, A61B5/339) · CPC title

• G06Q30/0201 Primary

  Market modelling; Market analysis; Collecting market data · CPC title

• A61B5/7275

  Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor · CPC title

• A61B5/7264

  Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems · CPC title