IP Library Granted Patent US 12,062,016
Granted Patent B2
US 12,062,016 · App. 17/678,791 · Granted Aug 13, 2024

Automated clinical documentation system and method

Inventors: Daniel Paulino Almendro Barreda (London, GB); Dushyant Sharma (Mountain House, CA); Joel Praveen Pinto (Aachen, DE); Uwe Helmut Jost (Groton, MA); Patrick A. Naylor (Reading, GB)
Assignee: Microsoft Technology Licensing, LLC
G06Q10/10G06F3/165G06F40/117G06F40/30G06T7/20G10L15/22G10L15/26G10L15/30G10L25/45G10L25/51G16H10/20G16H10/40G16H10/60G16H15/00G16H50/70H04R1/406H04R3/005G06T2207/30196
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Quick Facts
Patent No.
US 12,062,016
App. No.
17/678,791
Granted
Aug 13, 2024
Kind
B2
Abstract

A method, computer program product, and computing system for obtaining encounter information of a patient encounter, wherein the encounter information includes machine vision encounter information; and processing the encounter information to generate an encounter transcript.

Claims (44)

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

obtaining encounter information of a patient encounter, wherein the encounter information includes machine vision encounter information;

processing the encounter information to identify a speaker within the patient encounter, wherein processing the encounter information to identify the speaker within the patient encounter includes comparing the machine vision encounter information of the encounter information to one or more humanoid models;

determining that a first encounter participant is speaking using the one or more humanoid models;

steering one or more audio recording beams toward the first encounter participant based upon, at least in part, determining that the first encounter participant is speaking;

processing the encounter information to generate an encounter transcript;

processing the machine vision encounter information of the encounter information to associate a first portion of the encounter information with the first encounter participant; and

processing at least a portion of the encounter transcript to populate at least a portion of a medical record associated with the patient encounter.

2. The computer-implemented method of claim 1 wherein the one or more humanoid models includes a speaking humanoid model of the first encounter participant and a listening humanoid model of the first encounter participant.

3. The computer-implemented method of claim 1 wherein the encounter information further includes audio encounter information.

4. The computer-implemented method of claim 2 wherein steering the one or more audio recording beams toward the first encounter participant is based upon, at least in part, determining that the first encounter participant is speaking using the speaking humanoid model.

5. The computer-implemented method of claim 1 further comprising assigning a first role to the first encounter participant in the encounter transcript based upon the machine vision encounter information.

6. The computer-implemented method of claim 5 wherein the first role is one of a medical professional, a patient, and a third party.

7. The computer-implemented method of claim 1 wherein processing the encounter information to generate an encounter transcript includes:

processing the encounter information to compartmentalize the encounter information into a plurality of encounter stages.

8. 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:

obtaining encounter information of a patient encounter, wherein the encounter information includes machine vision encounter information;

processing the encounter information to identify a speaker within the patient encounter, wherein processing the encounter information to identify the speaker within the patient encounter includes comparing the machine vision encounter information of the encounter information to one or more humanoid models;

determining that a first encounter participant is speaking using the one or more humanoid models;

steering one or more audio recording beams toward the first encounter participant based upon, at least in part, determining that the first encounter participant is speaking;

processing the encounter information to generate an encounter transcript;

processing the machine vision encounter information of the encounter information to associate a first portion of the encounter information with the first encounter participant; and

processing at least a portion of the encounter transcript to populate at least a portion of a medical record associated with the patient encounter.

9. The computer program product of claim 8 wherein the one or more humanoid models includes a speaking humanoid model of the first encounter participant and a listening humanoid model of the first encounter participant.

10. The computer program product of claim 8 wherein the encounter information further includes audio encounter information.

11. The computer program product of claim 9 wherein steering the one or more audio recording beams toward the first encounter participant is based upon, at least in part, determining that the first encounter participant is speaking using the speaking humanoid model.

12. The computer program product of claim 8 further comprising assigning a first role to the first encounter participant in the encounter transcript based upon the machine vision encounter information.

13. The computer program product of claim 12 wherein the first role is one of a medical professional, a patient, and a third party.

14. The computer program product of claim 8 wherein processing the encounter information to generate an encounter transcript includes:

processing the encounter information to compartmentalize the encounter information into a plurality of encounter stages.

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

obtaining encounter information of a patient encounter, wherein the encounter information includes machine vision encounter information;

processing the encounter information to identify a speaker within the patient encounter, wherein processing the encounter information to identify the speaker within the patient encounter includes comparing the machine vision encounter information of the encounter information to one or more humanoid models;

determining that a first encounter participant is speaking using the one or more humanoid models;

steering one or more audio recording beams toward the first encounter participant based upon, at least in part, determining that the first encounter participant is speaking;

processing the encounter information to generate an encounter transcript;

processing the machine vision encounter information of the encounter information to associate a first portion of the encounter information with the first encounter participant; and

processing at least a portion of the encounter transcript to populate at least a portion of a medical record associated with the patient encounter.

16. The computing system of claim 15 wherein the one or more humanoid models includes a speaking humanoid model of the first encounter participant and a listening humanoid model of the first encounter participant.

17. The computing system of claim 15 wherein the encounter information further includes audio encounter information.

18. The computing system of claim 16 wherein steering the one or more audio recording beams toward the first encounter participant is based upon, at least in part, determining that the first encounter participant is speaking using the speaking humanoid model.

19. The computing system of claim 15 further comprising assigning a first role to the first encounter participant in the encounter transcript based upon the machine vision encounter information.

20. The computing system of claim 15 wherein processing the encounter information to generate an encounter transcript includes:

processing the encounter information to compartmentalize the encounter information into a plurality of encounter stages.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 9, 2023
From: NUANCE COMMUNICATIONS, INC.
To: MICROSOFT TECHNOLOGY LICENSING, LLC
Reel/Frame 065532/0152 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 23, 2022
From: BARREDA, DANIEL PAULINO ALMENDRO; SHARMA, DUSHYANT; PINTO, JOEL PRAVEEN; JOST, UWE HELMUT; NAYLOR, PATRICK A.
To: NUANCE COMMUNICATIONS, INC.
Reel/Frame 059082/0089 →
Continuity (3)
Continuation 16271329 · Feb 8, 2019
Provisional Application 62638809 · Mar 5, 2018
Related Publication 20220180318A1 · Jun 9, 2022
Cited By (2)
US 12,555,584 US 12,614,552