Adaptive analytical behavioral and health assistant system and related method of use

• US 8,838,513 B2
• Filed: 03/23/2012
• Issued: 09/16/2014
• Est. Priority Date: 03/24/2011
• Status: Active Grant

• Current Assignee: WellDoc, Inc
• Original Assignee: WellDoc, Inc
• Inventors: Sudharsan, Bharath
• Primary Examiner(s): CHEN, ALAN S
• Application Number:
  US13/428,763
• Publication Number:
  US 20120246102A1
• Time in Patent Office: 907 Days
• US Class Current: 706/25
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

This present disclosure relates to systems and methods for providing an Adaptive Analytical Behavioral and Health Assistant. These systems and methods may include collecting one or more of patient behavior information, clinical information, or personal information; learning one or more patterns that cause an event based on the collected information and one or more pattern recognition algorithms; identifying one or more interventions to prevent the event from occurring or to facilitate the event based on the learned patterns; preparing a plan based on the collected information and the identified interventions; and/or presenting the plan to a user or executing the plan.

Claims

1. A computer-implemented method for providing a health assistant system for dynamically creating a plan, the method comprising:

collecting one or more of patient behavior information, clinical information, or personal information;

learning one or more patterns that cause an event based on the collected information and one or more pattern recognition algorithms;

identifying one or more interventions to prevent the event from occurring or to facilitate the event based on the learned patterns;

preparing the plan based on the collected information and the identified interventions;

presenting the plan to a user or executing the plan;

electronically receiving patient feedback relating to the plan; and

automatically revising the plan based on the feedback.

2. The computer-implemented method of claim 1, wherein:

the feedback is one or more patient behaviors that occur after the plan is prepared or presented to the user; and

the revised plan includes one or more additional interventions automatically selected based on the feedback.

3. The computer-implemented method of claim 2, wherein the one or more patient behaviors that occur after the plan is prepared or presented to the user include a behavior transition.

4. The computer-implemented method of claim 1, the method further comprising determining one or more persons to associate with the identified one or more interventions.

5. The computer-implemented method of claim 1, further comprising:

automatically revising probabilities from the collected information; and

storing the revised probabilities, wherein the revised probabilities are used to determine the plan.

6. The computer-implemented method of claim 1, the method further comprising automatically making one or more inferences based on machine learning using one or more of the clinical information, behavior information, or personal information.

8. The computer-implemented method of claim 1, further comprising collecting patient qualitative behavioral information.

9. The computer implemented method of claim 1, further comprising collecting patient social interactions.

10. The computer implemented method of claim 1, wherein at least one of the one or more interventions is a behavioral intervention.

7. An information processing device for determining a plan, the device comprising:

a processor for processing a set of instructions; and

a computer-readable storage medium for storing the set of instructions, wherein the instructions, when executed by the processor, perform a method comprising;

collecting one or more of patient behavior information, clinical information, or personal information;

learning one or more patterns that cause an event based on the collected information and one or more pattern recognition algorithms;

identifying one or more interventions to prevent the event from occurring or to facilitate the event based on the learned patterns;

preparing the plan based on the collected information and the identified interventions;

presenting the plan to a user or executing the plan;

electronically receiving patient feedback relating to the plan; and

automatically revising the plan based on the feedback.

11. The information processing device of claim 7, wherein:

the feedback is one or more patient behaviors that occur after the plan is prepared or presented to the user; and

the revised plan includes one or more additional interventions automatically selected based on the feedback.

12. The information processing device of claim 11, wherein the one or more patient behaviors that occur after the plan transition is prepared or presented to the user include a behavior transition.

13. The information processing device of claim 7, the method further comprising determining one or more persons to associate with the identified intervention.

14. The information processing device of claim 7, the method further comprising:

automatically revising probabilities from the collected information; and

storing the revised probabilities, wherein the revised probabilities are used to determine the plan.

15. The information processing device of claim 7, wherein the one or more inferences are automatically made based on machine learning using one or more of the clinical information, behavior information, or personal information.

16. A non-transitory computer-readable medium storing a set of instructions that, when executed by a processor, perform a method for determining a plan, the method comprising:

collecting one or more of patient behavior information, clinical information, or personal information;

learning one or more patterns that cause an event based on the collected information and one or more pattern recognition algorithms;

identifying one or more interventions to prevent the event from occurring or to facilitate the event based on the learned patterns;

preparing a plan based on the collected information and the identified interventions;

presenting the plan to a user or executing the plan;

electronically receiving patient feedback relating to the plan; and

automatically revising the plan based on the feedback.

17. The non-transitory computer-readable medium of claim 16, wherein:

the feedback is one or more patient behaviors that occur after the plan is prepared or presented to the user; and

the revised plan includes one or more additional interventions automatically selected based on the feedback.

18. The non-transitory computer-readable medium of claim 17, wherein the one or more patient behaviors that occur after the plan is prepared or presented to the user include a behavior transition.

19. The non-transitory computer-readable medium of claim 16, the method further comprising determining one or more persons to associate with the identified one or more interventions.

20. The non-transitory computer-readable medium of claim 16, the method further comprising:

automatically revising probabilities from the collected information; and

storing the revised probabilities, wherein the revised probabilities are used to determine the plan.