IP Library Granted Patent US 11,133,091
Granted Patent B2
US 11,133,091 · App. 16/026,641 · Granted Sep 28, 2021

Automated analysis system and method

Inventors: Oscar Ferrandez-Escamez (Melrose, MA); John E. Ortega, Jr. (New York, NY); Neil Barrett (Longueuil, CA); Brian Delaney (Bolton, MA); Ravi Kumar Kondadadi (Lakeville, MN)
Assignee: Nuance Communications, Inc.
G16H10/60G06Q20/14G06Q30/04G16H15/00G16H40/20G16H50/30
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Quick Facts
Patent No.
US 11,133,091
App. No.
16/026,641
Granted
Sep 28, 2021
Kind
B2
Abstract

A method, computer program product, and computing system for processing content concerning a plurality of patients using a CAC system to define one or more billing codes concerning a social habit status of one or more patients of the plurality of patients. The one or more billing codes concerning the social habit status of the one or more patients are provided to a user for review. Feedback is received from the user concerning the accuracy of the one or more billing codes. The feedback concerning the one or more billing codes is automatically processed to define one or more confidence scores. The CAC system is trained based, at least in part, upon the one or more confidence scores.

Claims (61)

1. A computer-implemented method, executed on a computing device, comprising:

processing content concerning a plurality of patients using a computer assisted coding (CAC) system to define one or more billing codes concerning a social habit status of one or more patients of the plurality of patients;

receiving, from a human user, feedback concerning accuracy of the one or more billing codes, wherein receiving the feedback comprises receiving user input indicating whether the one or more billing codes were accepted, rejected or modified by the human user;

automatically processing the feedback concerning the accuracy of the one or more billing codes to define one or more confidence scores, wherein automatically processing the feedback comprises automatically processing the received user input indicating whether the one or more billing codes were accepted, rejected or modified by the human user to define the one or more confidence scores;

defining a first confidence score based on a first billing code accuracy score for a first portion of the content that concerns a first social habit status of a patient;

defining a second confidence score based on a second billing code accuracy score for a second portion of the content that concerns a second social habit status of the patient, wherein the second confidence score is higher than the first confidence score; and

training the CAC system based, at least in part, upon the one or more confidence scores, wherein training the CAC system based, at least in part, upon the one or more confidence scores comprises training, based on the first and second confidence scores, a model that in determining a social habit status for a subsequent content favors a social habit status associated with a second portion of the subsequent content over a social habit status associated with a first portion of the subsequent content.

2. The computer-implemented method of claim 1 , wherein the social habit status of one or more patients includes one or more of:

a smoking status of the one or more patients;

a drinking status of the one or more patients; and

a drug use status of the one or more patients.

3. The computer-implemented method of claim 1 , wherein automatically processing the feedback concerning the accuracy of the one or more billing codes to define the one or more confidence scores includes:

identifying a plurality of portions of the content that concern differing social habit statuses of the patient.

4. The computer-implemented method of claim 3 , wherein automatically processing the feedback concerning the accuracy of the one or more billing codes to define the one or more confidence scores further includes:

defining a billing code accuracy score for each of the plurality of portions of the content that concern differing social habit statuses of the patient.

5. The computer-implemented method of claim 4 , wherein automatically processing the feedback concerning the accuracy of the one or more billing codes to define the one or more confidence scores further includes:

defining the one or more confidence scores based, at least in part, upon the billing code accuracy score defined for each of the plurality of portions of the content that concern differing social habit statuses of the patient.

6. The computer-implemented method of claim 1 , wherein training the CAC system based, at least in part, upon the one or more confidence scores includes:

applying the model to an output of the CAC system.

7. A computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising:

processing content concerning a plurality of patients using a computer assisted coding (CAC) system to define one or more billing codes concerning a social habit status of one or more patients of the plurality of patients;

receiving, from a human user, feedback concerning accuracy of the one or more billing codes, wherein receiving the feedback comprises receiving user input indicating whether the one or more billing codes were accepted, rejected or modified by the human user;

automatically processing the feedback concerning the accuracy of the one or more billing codes to define one or more confidence scores, wherein automatically processing the feedback comprises automatically processing the received user input indicating whether the one or more billing codes were accepted, rejected or modified by the human user to define the one or more confidence scores;

defining a first confidence score based on a first billing code accuracy score for a first portion of the content that concerns a first social habit status of a patient;

defining a second confidence score based on a second billing code accuracy score for a second portion of the content that concerns a second social habit status of the patient, wherein the second confidence score is higher than the first confidence score; and

training the CAC system based, at least in part, upon the one or more confidence scores, wherein training the CAC system based, at least in part, upon the one or more confidence scores comprises training, based on the first and second confidence scores, a model that in determining a social habit status for a subsequent content favors a social habit status associated with a second portion of the subsequent content over a social habit status associated with a first portion of the subsequent content.

8. The computer program product of claim 7 , wherein the social habit status of one or more patients includes one or more of:

a smoking status of the one or more patients;

a drinking status of the one or more patients; and

a drug use status of the one or more patients.

9. The computer program product of claim 7 , wherein automatically processing the feedback concerning the accuracy of the one or more billing codes to define the one or more confidence scores includes:

identifying a plurality of portions of the content that concern differing social habit statuses of the patient.

10. The computer program product of claim 9 , wherein automatically processing the feedback concerning the accuracy of the one or more billing codes to define the one or more confidence scores further includes:

defining a billing code accuracy score for each of the plurality of portions of the content that concern differing social habit statuses of the patient.

11. The computer program product of claim 10 , wherein automatically processing the feedback concerning the accuracy of the one or more billing codes to define the one or more confidence scores further includes:

defining the one or more confidence scores based, at least in part, upon the billing code accuracy score defined for each of the plurality of portions of the content that concern differing social habit statuses of the patient.

12. The computer program product of claim 7 , wherein training the CAC system based, at least in part, upon the one or more confidence scores includes:

applying the model to an output of the CAC system.

13. A computing system including a processor and memory configured to perform operations comprising:

processing content concerning a plurality of patients using a computer assisted coding (CAC) system to define one or more billing codes concerning a social habit status of one or more patients of the plurality of patients;

receiving, from a human user, feedback concerning accuracy of the one or more billing codes, wherein receiving the feedback comprises receiving user input indicating whether the one or more billing codes were accepted, rejected or modified by the human user;

automatically processing the feedback concerning the accuracy of the one or more billing codes to define one or more confidence scores, wherein automatically processing the feedback comprises automatically processing the received user input indicating whether the one or more billing codes were accepted, rejected or modified by the human user to define the one or more confidence scores;

defining a first confidence score based on a first billing code accuracy score for a first portion of the content that concerns a first social habit status of a patient;

defining a second confidence score based on a second billing code accuracy score for a second portion of the content that concerns a second social habit status of the patient, wherein the second confidence score is higher than the first confidence score; and

training the CAC system based, at least in part, upon the one or more confidence scores, wherein training the CAC system based, at least in part, upon the one or more confidence scores comprises training, based on the first and second confidence scores, a model that in determining a social habit status for a subsequent content favors a social habit status associated with a second portion of the subsequent content over a social habit status associated with a first portion of the subsequent content.

14. The computing system of claim 13 , wherein the social habit status of one or more patients includes one or more of:

a smoking status of the one or more patients;

a drinking status of the one or more patients; and

a drug use status of the one or more patients.

15. The computing system of claim 13 , wherein automatically processing the feedback concerning the accuracy of the one or more billing codes to define the one or more confidence scores includes:

identifying a plurality of portions of the content that concern differing social habit statuses of the patient.

16. The computing system of claim 15 , wherein automatically processing the feedback concerning the accuracy of the one or more billing codes to define the one or more confidence scores further includes:

defining a billing code accuracy score for each of the plurality of portions of the content that concern differing social habit statuses of the patient.

17. The computing system of claim 16 , wherein automatically processing the feedback concerning the accuracy of the one or more billing codes to define the one or more confidence scores further includes:

defining the one or more confidence scores based, at least in part, upon the billing code accuracy score defined for each of the plurality of portions of the content that concern differing social habit statuses of the patient.

18. The computing system of claim 13 , wherein training the CAC system based, at least in part, upon the one or more confidence scores includes:

applying the model to an output the CAC system.

19. The computer-implemented method of claim 3 , wherein identifying the plurality of portions of the content that concern differing social habit statuses of the patient comprises:

identifying the plurality of portions of the content that simultaneously specify conflicting social habit statuses of the patient.

20. The computer-implemented method of claim 4 , wherein defining the billing code accuracy score for each of the plurality of portions of the content that concern differing social habit statuses of the patient comprises:

determining, for each of the plurality of portions of the content, whether a respective social habit status indicated in the portion of the content aligns with the feedback.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 9, 2023
From: NUANCE COMMUNICATIONS, INC.
To: MICROSOFT TECHNOLOGY LICENSING, LLC
Reel/Frame 065531/0665 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 27, 2019
From: FERRANDEZ-ESCAMEZ, OSCAR; ORTEGA, JOHN E, JR; BARRETT, NEIL; DELANEY, BRIAN; KONDADADI, RAVI KUMAR
To: NUANCE COMMUNICATIONS, INC
Reel/Frame 048145/0988 →