Conversational virtual healthcare assistant

• US 9,824,188 B2
• Filed: 07/29/2014
• Issued: 11/21/2017
• Est. Priority Date: 09/07/2012
• Status: Active Grant

• Current Assignee: Verint Americas Incorporated (Verint Systems Incorporated)
• Original Assignee: Next IT Corporation (Verint Systems Incorporated)
• Inventors: Brown, Fred A, Lawrence, Mitchell G., Morrison, Victor O'Brien
• Primary Examiner(s): KANAAN, MAROUN P
• Application Number:
  US14/446,153
• Publication Number:
  US 20140337048A1
• Time in Patent Office: 1,211 Days
• Field of Search: 705 2, 705 3
• CPC Class Codes: G06F 3/04886 by partitioning the display area of the touch-screen or the surface of the digitising tablet into independently controllable areas, e.g. virtual keyboards or menus
• CPC Class Codes: G06F 3/167 Audio in a user interface, e.g. using voice commands for navigating, audio feedback
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G10L 15/08 Speech classification or search
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders

Abstract

A conversation user interface enables patients to better understand their healthcare by integrating diagnosis, treatment, medication management, and payment, through a system that uses a virtual assistant to engage in conversation with the patient. The conversation user interface conveys a visual representation of a conversation between the virtual assistant and the patient. An identity of the patient, including preferences and medical records, is maintained throughout all interactions so that each aspect of this integrated system has access to the same information. The conversation user interface presents allows the patient to interact with the virtual assistant using natural language commands to receive information and complete task related to his or her healthcare.

Claims

1. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform acts comprising:

causing display of a conversation user interface along with a visual representation of a virtual assistant, the virtual assistant being configured with a persona;

learning one or more characteristics about a medical-related user from a conversation with the medical-related user via the conversation user interface;

receiving user input of the medical-related user during a later conversation, the user input comprising at least one of verbal input, keypad input, or touch input;

parsing the user input to identify one or more concepts expressed therein;

determining an intent of the medical-related user based at least in part on the one or more concepts;

determining a response to the user input based at least in part on (i) a medical history for the medical-related user, (ii) the intent of the medical-related user, (iii) the one or more learned characteristics about the medical-related user, (iv) a disease management algorithm indicating information to mitigate or treat a disease or symptom, and (v) assumptions used to interpret the user input or previous user input; and

representing the response in the conversation user interface as a message from the virtual assistant, the response including content to assist the medical-related user in managing a medical condition of the medical-related user.

2. The one or more non-transitory computer-readable media as recited in claim 1, wherein the user input is verbal input, and the verbal input is represented in the conversation user interface in a text format through a speech recognition engine.

3. The one or more non-transitory computer-readable media as recited in claim 1, wherein:

the user input is verbal input; and

the acts further comprise authenticating an identity of the medical-related user through analysis of voice patterns contained in the verbal input.

4. The one or more non-transitory computer-readable media as recited in claim 1, wherein the response to the user input is determined based at least in part on past behavior of the medical-related user.

5. The one or more non-transitory computer-readable media as recited in claim 1, wherein the response to the user input is determined based at least in part on a status of the medical-related user as checked in or checked out of a healthcare facility.

6. The one or more non-transitory computer-readable media as recited in claim 1, wherein the response to the user input is determined based on at least one of medical research results, nutrition information, or insurance information.

7. The one or more non-transitory computer-readable media as recited in claim 1, wherein the response to the user input is determined based on at least one of:

whether or not the medical-related user has checked in with a healthcare entity;

a status of a medical device used by the medical-related user;

a level of insurance coverage available to the medical-related user;

a prescription medication used by the medical-related user;

a diagnosed condition of the medical-related user;

a time of day at which the medical-related user provides the user input to the virtual assistant;

a date on which the medical-related user provides the user input to the virtual assistant;

an age of the medical-related user;

a location of the medical-related user;

or

a device type from which the medical-related user provides the user input.

8. The one or more non-transitory computer-readable media as recited in claim 1, wherein the acts further comprise causing an action to be performed on behalf of the medical-related user, the action comprising at least one of:

scheduling a medical appointment on behalf of the medical-related user;

initiating a prescription refill request on behalf of the medical-related user;

accessing data from a medical device on behalf of the medical-related user;

communicating with an insurance provider on behalf of the medical-related user;

or

altering a previously initiated action on behalf of the medical-related user.

9. A portable computing device comprising:

the one or more non-transitory computer-readable media as recited in claim 1; and

the one or more processors to execute the computer-executable instructions stored on the one or more non-transitory computer-readable media to perform the acts.

10. A computing system comprising:

one or more servers for hosting content;

the one or more non-transitory computer-readable media as recited in claim 1; and

the one or more processors to execute the computer-executable instructions stored on the one or more non-transitory computer-readable media to perform the acts.

11. The one or more non-transitory computer-readable media as recited in claim 1, wherein each of the one or more characteristics includes at least one of a health status of the medical-related user or a treatment regimen of the medical-related user.

12. The one or more non-transitory computer-readable media as recited in claim 1, wherein the acts further comprise:

determining that a voice of the user is modified by a health condition; and

correcting a word or a phase in the user based at least in part on determining that the voice of the user is modified by the health condition.

13. A method comprising:

initiating, by one or more processors, a conversation with a user by causing information representing a virtual assistant to be displayed via a mobile device, the virtual assistant being configured with a persona;

learning one or more characteristics about the user from the conversation with the user;

receiving, by the one or more processors, a medical query during the conversation with the virtual assistant, the medical query comprising at least one of verbal input, keypad input, or touch input;

performing natural language processing with the medical query to identify one or more concepts of the medical query;

determining, by the one or more processors, a response to the medical query based at least in part on (i) a medical history for the user, (ii) an intent of the user, (iii) the one or more learned characteristics, (iv) the one or more concepts of the medical query, and (v) medical information, the medical information comprising at least one of;

a treatment regimen;

health insurance eligibility;

a medical diagnostic algorithm;

nutrition information;

prescription medication for the user;

a healthcare entity for the user;

a reading of a medical device;

or

an insurance record of the user; and

providing, by the one or more processors, the response for output via the mobile device as a message from the virtual assistant.

14. The method as recited in claim 13, wherein the response from the virtual assistant is provided as audio output.

15. The method as recited in claim 13, wherein the medical query relates to a medical condition of the user.

16. The method as recited in claim 13, wherein the response includes information about a comparison between a metric of the user and a metric for another user.

17. The method as recited in claim 16, wherein the metric of the user is obtained from at least one of an electronic medical record of the user, input provided by the user, a result of a test administered to the user, or data from the medical device.

18. A computing device comprising:

one or more computer-readable media storing computer-executable instructions; and

the one or more processors to execute the computer-executable instructions stored on the one or more computer-readable media to perform the method of claim 13.

19. A system comprising:

one or more processors; and

memory storing computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising;

initiating a conversation with a user by causing information representing a virtual assistant to be displayed via a mobile device, the virtual assistant being configured with a persona;

learning one or more characteristics about the user from the conversation with the user;

receiving a medical query during the conversation with the virtual assistant, the medical query comprising at least one of verbal input, keypad input, or touch input;

performing natural language processing with the medical query to identify one or more concepts of the medical query;

determining a response to the medical query based at least in part on (i) a medical history for the user, (ii) an intent of the user, (iii) the one or more learned characteristics, (iv) the one or more concepts of the medical query, and (v) medical information, the medical information comprising at least one of;

a treatment regimen;

health insurance eligibility;

a medical diagnostic algorithm;

nutrition information;

prescription medication for the user;

a healthcare entity for the user;

a reading of a medical device;

or

an insurance record of the user; and

providing the response for output via the mobile device as a message from the virtual assistant.

20. The system as recited in claim 19, wherein the response from the virtual assistant is provided as audio output.

21. The system as recited in claim 19, wherein the medical query relates to a medical condition of the user.

22. The system as recited in claim 19, wherein the response includes information about a comparison between a metric of the user and a metric for another user.

23. The system as recited in claim 22, wherein the metric of the user is obtained from at least one of an electronic medical record of the user, input provided by the user, a result of a test administered to the user, or data from the medical device.

24. The system as recited in claim 19, wherein the response is determined based on at least one of:

whether or not the user has checked in with the healthcare entity;

a status of the medical device;

a level of insurance coverage available to the user;

or

a diagnosed condition of the user.

25. The system as recited in claim 19, wherein the response is determined based on at least one of:

a time of day at which the user provides the medical query;

a date on which the user provides the medical query;

an age of the user;

a location of the user;

or

a device type from which the user provides the medical query.