U.S. patent application number 17/518479 was filed with the patent office on 2022-05-05 for communication system and method.
The applicant listed for this patent is Nuance Communications, Inc.. Invention is credited to George N. Kustas, David Rubin, Michael T. Trombly.
Application Number | 20220139514 17/518479 |
Document ID | / |
Family ID | |
Filed Date | 2022-05-05 |
United States Patent
Application |
20220139514 |
Kind Code |
A1 |
Rubin; David ; et
al. |
May 5, 2022 |
Communication System and Method
Abstract
A method, computer program product, and computing system for
receiving medical information; processing the medical information
to determine if the medical information includes one or more
actionable items; if it is determined that the medical information
includes one or more actionable items, determining an appropriate
action item response; and executing the action item response.
Inventors: |
Rubin; David; (Stamford,
CT) ; Kustas; George N.; (Poughkeepsie, NY) ;
Trombly; Michael T.; (Burlington, VT) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Nuance Communications, Inc. |
Burlington |
MA |
US |
|
|
Appl. No.: |
17/518479 |
Filed: |
November 3, 2021 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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63109219 |
Nov 3, 2020 |
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63113439 |
Nov 13, 2020 |
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63129301 |
Dec 22, 2020 |
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International
Class: |
G16H 15/00 20060101
G16H015/00; G16H 50/20 20060101 G16H050/20; G16H 30/20 20060101
G16H030/20; G16H 10/60 20060101 G16H010/60 |
Claims
1. A computer-implemented method, executed on a computing system,
comprising: receiving medical information; processing the medical
information to determine if the medical information includes one or
more actionable items; if it is determined that the medical
information includes one or more actionable items, determining an
appropriate action item response; and executing the action item
response.
2. The computer-implemented method of claim 1 wherein the medical
information includes one or more of: medical information dictated
by a clinician medical information obtained from at least one
disparate platform; medical information obtained from an existing
medical record; medical information obtained from an artificial
intelligence platform; medical information obtained from a form;
and medical information obtained from that is manually entered.
3. The computer-implemented method of claim 2 wherein the clinician
includes one or more of: a radiologist; a cardiologist; and a
pathologist.
4. The computer-implemented method of claim 1 wherein processing
the medical information to determine if the medical information
includes one or more actionable items includes: associating one or
more best practices with one or more actionable items.
5. The computer-implemented method of claim 4 wherein associating
one or more best practices with one or more actionable items
includes: using artificial intelligence to process a plurality of
previously-generated medical reports to associate one or more best
practices with one or more actionable items.
6. The computer-implemented method of claim 1 wherein determining
an appropriate action item response includes: determining a
severity for the one or more actionable items.
7. The computer-implemented method of claim 6 wherein determining
an appropriate action item response further includes: identifying
the appropriate action item response based, at least in part, upon
the severity for the one or more actionable items.
8. The computer-implemented method of claim 1 wherein executing the
action item response includes: identifying the one or more
actionable items to a clinician.
9. The computer-implemented method of claim 1 wherein executing the
action item response includes: suggesting to a clinician one or
more remedial courses of action concerning the one or more
actionable items.
10. The computer-implemented method of claim 1 wherein executing
the action item response includes: executing one or more remedial
courses of action concerning the one or more actionable items.
11. A computer program product residing on a computer readable
medium having a plurality of instructions stored thereon which,
when executed by a processor, cause the processor to perform
operations comprising: receiving medical information; processing
the medical information to determine if the medical information
includes one or more actionable items; if it is determined that the
medical information includes one or more actionable items,
determining an appropriate action item response; and executing the
action item response.
12. The computer program product of claim 11 wherein the medical
information includes one or more of: medical information dictated
by a clinician medical information obtained from at least one
disparate platform; medical information obtained from an existing
medical record; medical information obtained from an artificial
intelligence platform; medical information obtained from a form;
and medical information obtained from that is manually entered.
13. The computer program product of claim 12 wherein the clinician
includes one or more of: a radiologist; a cardiologist; and a
pathologist.
14. The computer program product of claim 11 wherein processing the
medical information to determine if the medical information
includes one or more actionable items includes: associating one or
more best practices with one or more actionable items.
15. The computer program product of claim 14 wherein associating
one or more best practices with one or more actionable items
includes: using artificial intelligence to process a plurality of
previously-generated medical reports to associate one or more best
practices with one or more actionable items.
16. The computer program product of claim 11 wherein determining an
appropriate action item response includes: determining a severity
for the one or more actionable items.
17. The computer program product of claim 16 wherein determining an
appropriate action item response further includes: identifying the
appropriate action item response based, at least in part, upon the
severity for the one or more actionable items.
18. The computer program product of claim 11 wherein executing the
action item response includes: identifying the one or more
actionable items to a clinician.
19. The computer program product of claim 11 wherein executing the
action item response includes: suggesting to a clinician one or
more remedial courses of action concerning the one or more
actionable items.
20. The computer program product of claim 11 wherein executing the
action item response includes: executing one or more remedial
courses of action concerning the one or more actionable items.
21. A computing system including a processor and memory configured
to perform operations comprising: receiving medical information;
processing the medical information to determine if the medical
information includes one or more actionable items; if it is
determined that the medical information includes one or more
actionable items, determining an appropriate action item response;
and executing the action item response.
22. The computing system of claim 21 wherein the medical
information includes one or more of: medical information dictated
by a clinician medical information obtained from at least one
disparate platform; medical information obtained from an existing
medical record; medical information obtained from an artificial
intelligence platform; medical information obtained from a form;
and medical information obtained from that is manually entered.
23. The computing system of claim 22 wherein the clinician includes
one or more of: a radiologist; a cardiologist; and a
pathologist.
24. The computing system of claim 21 wherein processing the medical
information to determine if the medical information includes one or
more actionable items includes: associating one or more best
practices with one or more actionable items.
25. The computing system of claim 24 wherein associating one or
more best practices with one or more actionable items includes:
using artificial intelligence to process a plurality of
previously-generated medical reports to associate one or more best
practices with one or more actionable items.
26. The computing system of claim 21 wherein determining an
appropriate action item response includes: determining a severity
for the one or more actionable items.
27. The computing system of claim 26 wherein determining an
appropriate action item response further includes: identifying the
appropriate action item response based, at least in part, upon the
severity for the one or more actionable items.
28. The computing system of claim 21 wherein executing the action
item response includes: identifying the one or more actionable
items to a clinician.
29. The computing system of claim 21 wherein executing the action
item response includes: suggesting to a clinician one or more
remedial courses of action concerning the one or more actionable
items.
30. The computing system of claim 21 wherein executing the action
item response includes: executing one or more remedial courses of
action concerning the one or more actionable items.
Description
RELATED APPLICATION(S)
[0001] This application claims the benefit of U.S. Provisional
Application No. 63/109,219, filed on 3 Nov. 2020, 63/113,439, filed
on 13 Nov. 2020, and 63/129,301, filed on 22 Dec. 2020; the entire
contents of which is herein incorporated by reference.
TECHNICAL FIELD
[0002] This disclosure relates to communication systems and methods
and, more particularly, to communications systems and methods that
enable the interoperation of disparate systems.
BACKGROUND
[0003] As is known in the art, medical processionals may use
various computer systems to review various pieces of medical
information. For example, a first computer system may be used to
review medical images, a second computer system may be used to
review medical records, and a third computer system may be used to
generate a medical report based upon their review of e.g., medical
images or medical records.
[0004] Unfortunately, these disparate systems tend to be
technological islands that are generally incapable of exchanging
meaningful data between these systems. Accordingly and when
generating such a medical report, findings made in one system may
need to be manually reentered into another system.
SUMMARY OF DISCLOSURE
[0005] In one implementation, a computer-implemented method is
executed on a computing system and includes: receiving medical
information; processing the medical information to determine if the
medical information includes one or more actionable items; if it is
determined that the medical information includes one or more
actionable items, determining an appropriate action item response;
and executing the action item response.
[0006] One or more of the following features may be included. The
medical information may include one or more of: medical information
dictated by a clinician; medical information obtained from at least
one disparate platform; medical information obtained from an
existing medical record; medical information obtained from an
artificial intelligence platform; medical information obtained from
a form; and medical information obtained from that is manually
entered. The clinician may include one or more of: a radiologist; a
cardiologist; and a pathologist. Processing the medical information
to determine if the medical information includes one or more
actionable items may include: associating one or more best
practices with one or more actionable items. Associating one or
more best practices with one or more actionable items may include:
using artificial intelligence to process a plurality of
previously-generated medical reports to associate one or more best
practices with one or more actionable items. Determining an
appropriate action item response may include: determining a
severity for the one or more actionable items. Determining an
appropriate action item response further may include: identifying
the appropriate action item response based, at least in part, upon
the severity for the one or more actionable items. Executing the
action item response may include: identifying the one or more
actionable items to a clinician. Executing the action item response
may include: suggesting to a clinician one or more remedial courses
of action concerning the one or more actionable items. Executing
the action item response may include: executing one or more
remedial courses of action concerning the one or more actionable
items.
[0007] In another implementation, a computer program product
resides on a computer readable medium and has a plurality of
instructions stored on it. When executed by a processor, the
instructions cause the processor to perform operations including:
receiving medical information; processing the medical information
to determine if the medical information includes one or more
actionable items; if it is determined that the medical information
includes one or more actionable items, determining an appropriate
action item response; and executing the action item response.
[0008] One or more of the following features may be included. The
medical information may include one or more of: medical information
dictated by a clinician; medical information obtained from at least
one disparate platform; medical information obtained from an
existing medical record; medical information obtained from an
artificial intelligence platform; medical information obtained from
a form; and medical information obtained from that is manually
entered. The clinician may include one or more of: a radiologist; a
cardiologist; and a pathologist. Processing the medical information
to determine if the medical information includes one or more
actionable items may include: associating one or more best
practices with one or more actionable items. Associating one or
more best practices with one or more actionable items may include:
using artificial intelligence to process a plurality of
previously-generated medical reports to associate one or more best
practices with one or more actionable items. Determining an
appropriate action item response may include: determining a
severity for the one or more actionable items. Determining an
appropriate action item response further may include: identifying
the appropriate action item response based, at least in part, upon
the severity for the one or more actionable items. Executing the
action item response may include: identifying the one or more
actionable items to a clinician. Executing the action item response
may include: suggesting to a clinician one or more remedial courses
of action concerning the one or more actionable items. Executing
the action item response may include: executing one or more
remedial courses of action concerning the one or more actionable
items.
[0009] In another implementation, a computing system includes a
processor and memory is configured to perform operations including:
receiving medical information; processing the medical information
to determine if the medical information includes one or more
actionable items; if it is determined that the medical information
includes one or more actionable items, determining an appropriate
action item response; and executing the action item response.
[0010] One or more of the following features may be included. The
medical information may include one or more of: medical information
dictated by a clinician; medical information obtained from at least
one disparate platform; medical information obtained from an
existing medical record; medical information obtained from an
artificial intelligence platform; medical information obtained from
a form; and medical information obtained from that is manually
entered. The clinician may include one or more of: a radiologist; a
cardiologist; and a pathologist. Processing the medical information
to determine if the medical information includes one or more
actionable items may include: associating one or more best
practices with one or more actionable items. Associating one or
more best practices with one or more actionable items may include:
using artificial intelligence to process a plurality of
previously-generated medical reports to associate one or more best
practices with one or more actionable items. Determining an
appropriate action item response may include: determining a
severity for the one or more actionable items. Determining an
appropriate action item response further may include: identifying
the appropriate action item response based, at least in part, upon
the severity for the one or more actionable items. Executing the
action item response may include: identifying the one or more
actionable items to a clinician. Executing the action item response
may include: suggesting to a clinician one or more remedial courses
of action concerning the one or more actionable items. Executing
the action item response may include: executing one or more
remedial courses of action concerning the one or more actionable
items.
[0011] The details of one or more implementations are set forth in
the accompanying drawings and the description below. Other features
and advantages will become apparent from the description, the
drawings, and the claims.
BRIEF DESCRIPTION OF THE DRAWINGS
[0012] FIG. 1 is a diagrammatic view of a plurality of disparate
systems that communicate via a communication process coupled to a
distributed computing network;
[0013] FIG. 2 is a flow chart of one implementation of the
communication process of FIG. 1 according to an implementation of
this disclosure;
[0014] FIG. 3 is a diagrammatic view of a workstation computing
system executing the communication process of FIG. 1;
[0015] FIG. 4 is a flow chart of another implementation of the
communication process of FIG. 1 according to an implementation of
this disclosure;
[0016] FIG. 5 is a flow chart of another implementation of the
communication process of FIG. 1 according to an implementation of
this disclosure;
[0017] FIG. 6 is a flow chart of another implementation of the
communication process of FIG. 1 according to an implementation of
this disclosure;
[0018] FIG. 7 is a flow chart of another implementation of the
communication process of FIG. 1 according to an implementation of
this disclosure;
[0019] FIG. 8 is a flow chart of another implementation of the
communication process of FIG. 1 according to an implementation of
this disclosure;
[0020] FIG. 9 is a flow chart of another implementation of the
communication process of FIG. 1 according to an implementation of
this disclosure;
[0021] FIG. 10 is a flow chart of another implementation of the
communication process of FIG. 1 according to an implementation of
this disclosure; and
[0022] FIG. 11 is a summary window rendered by the communication
process of FIG. 1.
[0023] Like reference symbols in the various drawings indicate like
elements.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
System Overview
[0024] Referring to FIG. 1, there is shown communication process
10. As will be discussed below in greater detail, communication
process 10 may be configured to allow for the communication and
transfer of data between various disparate systems.
[0025] Communication process 10 may be implemented as a server-side
process, a client-side process, or a hybrid server-side/client-side
process. For example, communication process 10 may be implemented
as a purely server-side process via communication process 10h.
Alternatively, communication process 10 may be implemented as a
purely client-side process via one or more of communication process
10cs1, communication process 10cs2, communication process 10rs, and
communication process 10ws. Alternatively still, communication
process 10 may be implemented as a hybrid server-side/client-side
process via communication process 10h in combination with one or
more of communication process 10cs1, communication process 10cs2,
communication process 10rs, and communication process 10ws.
[0026] Accordingly, communication process 10 as used in this
disclosure may include any combination of communication process
10h, communication process 10cs1, communication process 10cs2,
communication process 10rs, and communication process 10ws.
[0027] Communication process 10h may be a server application and
may reside on and may be executed by communication computing system
12, which may be connected to network 14 (e.g., the Internet or a
local area network). Communication computing system 12 may include
various components, examples of which may include but are not
limited to: a personal computer, a server computer, a series of
server computers, a mini computer, a mainframe computer, one or
more Network Attached Storage (NAS) systems, one or more Storage
Area Network (SAN) systems, one or more Platform as a Service
(PaaS) systems, one or more Infrastructure as a Service (IaaS)
systems, one or more Software as a Service (SaaS) systems, a
cloud-based computational system, and a cloud-based storage
platform.
[0028] As is known in the art, a SAN may include one or more of a
personal computer, a server computer, a series of server computers,
a mini computer, a mainframe computer, a RAID device and a NAS
system. The various components of communication computing system 12
may execute one or more operating systems, examples of which may
include but are not limited to: Microsoft Windows Server.sup.tm.
Redhat Linux.sup.un Unix, or a custom operating system, for
example.
[0029] The instruction sets and subroutines of communication
process 10h, which may be stored on storage device 16 coupled to
communication computing system 12, may be executed by one or more
processors (not shown) and one or more memory architectures (not
shown) included within communication computing system 12. Examples
of storage device 16 may include but are not limited to: a hard
disk drive; a RAID device; a random-access memory (RAM); a
read-only memory (ROM); and all forms of flash memory storage
devices.
[0030] Network 14 may be connected to one or more secondary
networks (e.g., network 18), examples of which may include but are
not limited to: a local area network; a wide area network; an
intranet; or the internet. Accordingly, network 14 may be a local
area network and network 18 may be the internet, thus allowing
communication process 10h to be a cloud-based resource.
[0031] Various pieces of data (e.g. data 20) may be transferred
between communication process 10h, communication process 10cs1,
communication process 10cs2, communication process 10rs, and
communication process 10ws. Examples of data 20 may include but are
not limited to data requests (e.g., data read requests and data
write requests) and the related data itself.
[0032] The instruction sets and subroutines of communication
process 10cs1, communication process 10cs2, communication process
10rs, and communication process 10ws, which may be stored on
storage devices 22, 24, 26, 28 (respectively) coupled to computing
systems 30, 32, 34, 36 (respectively), may be executed by one or
more processors (not shown) and one or more memory architectures
(not shown) incorporated into computing systems 30, 32, 34, 36
(respectively). Examples of storage devices 22, 24, 26, 28 may
include but are not limited to: hard disk drives; optical drives;
RAID devices; random access memories (RAM); read-only memories
(ROM), and all forms of flash memory storage devices. Examples of
computing systems 30, 32, 34, 36 may include, but are not limited
to, collaborating computing system 30 (e.g., a personal computer, a
workstation computer, a server computer, and a cloud-based
resource), collaborating computing system 32 (e.g., a personal
computer, a workstation computer, a server computer, and a
cloud-based resource), report computing system 34 (e.g., a personal
computer, a workstation computer, a server computer, and a
cloud-based resource), and workstation computing system 36 (e.g., a
smart telephone, a tablet computer, a notebook computer, a laptop
computer, a personal computer, a workstation computer, a server
computer, and a cloud-based resource).
[0033] As will be discussed below in greater detail, the
above-described platform (e.g., communication process 10 in
combination with computing systems 12, 30, 32, 34, 36) may be
configured to allow clinician 38 (e.g., a radiologist, a
cardiologist or a pathologist) to review medical information (e.g.,
data 20) and populate medical report 40. The medical information
(e.g., data 20) may be provided by one or more of the collaborating
systems (e.g., collaborating computing systems 30, 32), examples of
which may include but are not limited to a collaborating system
executing a PACS system and a collaborating system executing an EHR
system. [0034] As is known in the art, a PACS (Picture Archiving
and Communication System) system is a medical imaging technology
that provides economical storage and convenient access to images
from multiple modalities (source machine types). Electronic images
and reports may be transmitted digitally via PACS; thus eliminating
the need to manually file, retrieve and/or transport film jackets.
The universal format for PACS image storage and transfer is DICOM
(Digital Imaging and Communications in Medicine). Non-image data,
such as scanned documents, may be incorporated using consumer
industry standard formats like PDF (Portable Document Format), once
encapsulated in DICOM. [0035] As is known in the art, an EHR
(Electronic Health Record) system is a systematized collection of
patient and population electronically stored health information in
a digital format. These records may be shared across different
health care settings, wherein records maybe shared through
network-connected, enterprise-wide information systems or other
information networks and exchanges. An EHR system may define a
range of data, including demographics, medical histories,
medications and allergies, immunization status, laboratory test
results, radiology images, vital signs, personal statistics, and
billing information.
[0036] Accordingly and as will be discussed below in greater
detail, clinician 38 may utilize workstation computing system 36 to
review medical information (e.g., data 20) provided by the
collaborating systems (e.g., collaborating computing systems 30,
32). Report computing system 34 may be configured to allow
clinician 38 to populate medical report (e.g., medical report 40).
Communication process 10 may be configured to allow clinician 38 to
utilize audio input device 42 to provide verbal information/command
44 based upon information ascertained from the medical information
(e.g., data 20).
[0037] Examples of audio input device 42 may include but are not
limited to a lapel microphone, a desktop microphone, a wall-mounted
microphone, or a device-embedded microphone (e.g., a microphone
embedded into a laptop computer). As will be discussed below in
greater detail, communication computing system 12 may be configured
to allow all of the computing systems (e.g., computing systems 12,
30, 32, 34, 36) within the above-described platform to communicate
with each other and exchange information (e.g., data 20).
General Intersystem Communication
[0038] Referring also to FIG. 2, communication process 10 may
define 100 a communication computing system (e.g., communication
computing system 12) within a computing network (e.g., network 14
and/or network 18). The communication computing system (e.g.,
communication computing system 12) may be configured as a local
system or as a remote system. For example, communication computing
system 12 may be a local computing system directly coupled to e.g.,
computing systems 30, 32, 34, 36 via a local area network (e.g.,
network 14). Additionally/alternatively, communication computing
system 12 may be a cloud-based computing system (e.g., a
cloud-based resource) indirectly coupled to e.g., computing systems
30, 32, 34, 36 via network 18 (e.g., the internet). As will be
discussed below in greater detail, communication computing system
12 (in combination with communication process 10) may be configured
to effectuate communication between computing systems 30, 32, 34,
36.
[0039] As discussed above, this computing network (e.g., network 14
and/or network 18) may couple various computing systems (e.g.,
computing systems 12, 30, 32, 34, 36) configured to provide
information (e.g., data 20) concerning various topics. Disparate
platforms executed on these computing systems (e.g., computing
systems 12, 30, 32, 34, 36) may generate and/or modify information
(e.g., data 20), which may be provided to other computing systems
within the computing network (e.g., network 14 and/or network 18).
For example, a disparate platform executed on collaborating
computing system 30 may generate information (e.g., data 20) that
may be provided to workstation computing system 36 via the
computing network (e.g., network 14 and/or network 18).
[0040] As discussed above, communication process 10 may be
configured to allow clinician 38 (e.g., a radiologist, a
cardiologist or a pathologist) to utilize workstation computing
system 36 to review medical information (e.g., data 20) concerning
various patients and populate various medical reports (e.g.,
medical report 40). Accordingly, the plurality of disparate
platforms executed on these computing systems (e.g., computing
systems 12, 30, 32, 34, 36) may include a plurality of disparate
medical platforms (e.g., medical imaging platform 46; medical
report platform 48; medical record platform 50; conversational AI
platform 52; illumination platform 54 and/or medical analysis
platform 56.
[0041] At least a portion of the plurality of disparate platforms
(e.g., disparate platforms 46, 48, 50, 52, 54, 56) may be executed
on a single computing system. For example and referring also to
FIG. 3, workstation computing system 36 may be configured to
support multiple monitors (e.g., monitors 150, 152, 154), which may
be simultaneously used by clinician 38 to access and utilize the
various disparate platforms (e.g., disparate platforms 46, 48, 50,
52, 54, 56).
[0042] In this example, monitor 150 is shown to allow clinician 38
to access medical imaging platform 46, wherein monitor 152 is shown
to allow clinician 38 to access medical record platform 50. Assume
for this example that medical imaging platform 46 is being executed
on collaborating system 30, while medical record platform 50 is
being executed on collaborating system 32. Accordingly, at least a
portion of medical imaging platform 46 and at least a portion of
medical record platform 50 may be executed on a single computing
system (e.g., workstation computing system 36), wherein: [0043]
medical image platform portion 156 may interact with medical image
platform 46 being executed on collaborating system 30 and may
enable clinician 38 to review the medical images provided by
medical image platform 46 on workstation computing system 36; and
[0044] medical record platform portion 158 may interact with
medical record platform 50 being executed on collaborating system
32 and may enable clinician 38 to review the medical records
provided by medical record platform 50 on workstation computing
system 36.
A) Passing of Observational Data
[0045] Communication process 10 may enable 102 a first of the
plurality of disparate platforms (e.g., medical image platform 46)
to process information (e.g., data 20) concerning a specific
topic.
[0046] As discussed above, communication process 10 may be
configured to allow clinician 38 (e.g., a radiologist, a
cardiologist or a pathologist) to utilize workstation computing
system 36 to review medical information (e.g., data 20) concerning
various patients and populate various medical reports (e.g.,
medical report 40). Accordingly and when enabling 102 a first of
the plurality of disparate platforms (e.g., medical image platform
46) to process information (e.g., data 20) concerning a specific
topic (e.g., a specific patient), communication process 10 may
enable 104 a user (e.g., clinician 38) of the first of the
plurality of disparate platforms (e.g., medical image platform 46)
to review medical information (e.g., data 20) concerning a specific
patient.
[0047] For this example, assume that collaborating system 30 is
executing medical image platform 46 (e.g., PACS), wherein medical
image platform portion 156 is executed on workstation computing
system 36. Accordingly, medical image platform 46 (e.g., PACS)
being executed on collaborating system 30 may provide chest x-ray
image 160 (e.g., data 20) of a patient (e.g., patient John Smith),
wherein clinician 38 may review chest x-ray image 160 using medical
image platform portion 156 being executed on workstation computing
system 36.
[0048] Communication process 10 may generate 106 observational data
(e.g., data 58) for the information (e.g., data 20) concerning the
specific topic (e.g., a specific patient). For example and when
generating 106 observational data (e.g., data 58) for the
information (e.g., data 20) concerning the specific topic (e.g., a
specific patient), communication process 10 may enable 108 the user
(e.g., clinician 38) of the first of the plurality of disparate
platforms (e.g., medical image platform 46) to generate structured
data concerning the specific patient.
[0049] Specifically and with respect to structured data, structured
data may relate to a structured observation that is made by (in
this example) clinician 38, wherein a structured observation may be
codified (have one or more medical codes assigned). For example, a
lung may have an assigned medical code . . . and a growth may have
an assigned medical code . . . and over 5.0 centimeters may have an
assigned medical code.
[0050] Accordingly, communication process 10 may enable 104
clinician 38 to review chest x-ray image 160 (via medical image
platform portion 156 executed on workstation computing system 36)
to generate 106 observational data (e.g., data 58) for chest x-ray
image 160 of patient John Smith. Examples of such observational
data (e.g., data 58) may include but are not limited to structured
data that concerns e.g., measurements of objects within an image
(e.g., x-ray image 160), the location of objects within an image
(e.g., x-ray image 160), and the type of image (e.g., x-ray image
160).
[0051] Accordingly and via medical image platform portion 156
executed on workstation computing system 36, clinician 38 may
review chest x-ray image 160. Upon reviewing chest x-ray image 160,
clinician 38 may notice a growth (e.g., growth 162) within x-ray
image 160. Accordingly and through medical image platform portion
156 executed on workstation computing system 36, communication
process 10 may enable 108 clinician 38 to measure growth 162
(measured to be 5.1 centimeters), thus generating 106 observational
data (e.g., data 58).
[0052] Communication process 10 may provide 110 the observational
data (e.g., data 58) for the information (e.g., data 20) concerning
the specific topic (e.g., a specific patient) to at least a second
of the plurality of disparate platforms (e.g., medical report
platform 48) via the communication computing system (e.g.,
communication computing system 12). For this example, assume that
the observational data (e.g., data 58) identifies the location of
growth 162 (e.g., lower quadrant of left lung) and the size of
growth 162 (e.g., 5.1 centimeters).
[0053] When providing 110 the observational data (e.g., data 58)
for the information (e.g., data 20) concerning the specific topic
(e.g., a specific patient) to at least a second of the plurality of
disparate platforms (e.g., medical report platform 48) via the
communication computing system (e.g., communication computing
system 12), communication process 10 may: [0054] receive 112 the
observational data (e.g., data 58) on the communication computing
system (e.g., communication computing system 12); and [0055]
broadcast 114 the observational data (e.g., data 58) to the at
least a second of the plurality of disparate platforms (e.g.,
medical report platform 48).
[0056] For example and as discussed above, through medical image
platform portion 156 executed on workstation computing system 36,
communication process 10 may enable 108 clinician 38 to measure
growth 162 (measured to be 5.1 centimeters), thus generating 106
observational data (e.g., data 58). This observational data (e.g.,
data 58) may then be provided to communication computing system 12.
For example, medical image platform portion 156 that is executed on
workstation computing system 36 may provide observational data
(e.g., data 58) to communication computing system 12.
Additionally/alternatively, medical image platform 46 (e.g., PACS)
that is executed on collaborating system 30 may provide
observational data (e.g., data 58) to communication computing
system 12.
[0057] Once the observational data (e.g., data 58) is received 112
on the communication computing system (e.g., communication
computing system 12), the communication computing system (e.g.,
communication computing system 12) may broadcast 114 the
observational data (e.g., data 58) to the at least a second of the
plurality of disparate platforms (e.g., medical report platform
48).
[0058] As discussed above, medical report platform 48 may be
configured to allow clinician 38 to populate a medical report
(e.g., medical report 40) concerning (in this example) patient John
Smith. Accordingly and as will be discussed below in greater
detail, once the observational data (e.g., data 58) is received
112, the communication computing system (e.g., communication
computing system 12) may broadcast 114 the observational data
(e.g., data 58) to medical report platform 48 so that the
observational data (e.g., data 58) may be utilized to populate a
medical report (e.g., medical report 40) for the patient (e.g.,
patient John Smith). Accordingly, the appropriate field (e.g.,
field 164) within medical report 40 of patient John Smith may be
populated by medical report platform 48 to state that chest x-ray
image 160 of patient John Smith shows a 5.1 centimeter growth
(e.g., growth 162) in the lower quadrant of the left lung.
B) Processing of Verbal Commands
[0059] Referring also to FIG. 4 and as discussed above,
communication process 10 may define 100 a communication computing
system (e.g., communication computing system 12) within a computing
network (e.g., network 14 and/or network 18). This computing
network (e.g., network 14 and/or network 18) may couple various
computing systems (e.g., computing systems 12, 30, 32, 34, 36)
configured to provide information (e.g., data 20) concerning
various topics. Disparate platforms (e.g., disparate platforms 46,
48, 50, 52, 54, 56) executed on these computing systems (e.g.,
computing systems 12, 30, 32, 34, 36) may generate and/or modify
information (e.g., data 20), which may be provided to other
computing systems within the computing network (e.g., network 14
and/or network 18).
[0060] Communication process 10 may enable 200 a user (e.g.,
clinician 38) to issue a verbal command (e.g., verbal
information/command 44) concerning one or more of the plurality of
disparate platforms (e.g., disparate platforms 46, 48, 50, 52, 54,
56).
[0061] As discussed above, communication process 10 may be
configured to allow clinician 38 to utilize audio input device 42
to provide verbal information/command 44 based upon information
ascertained from the medical information (e.g., data 20). Examples
of audio input device 42 may include but are not limited to a lapel
microphone, a desktop microphone, a wall-mounted microphone, or a
device-embedded microphone (e.g., a microphone embedded into a
laptop computer). Accordingly, since communication process 10
enables 200 clinician 38 to issue verbal commands (e.g., verbal
information/command 44) concerning the disparate platforms (e.g.,
disparate platforms 46, 48, 50, 52, 54, 56), communication process
10 may provide clinician 38 with virtual assistant
functionality.
[0062] Communication process 10 may process 202 the verbal command
(e.g., verbal information/command 44) to generate a
platform-useable command (e.g., platform-useable command 60) based,
at least in part, upon the verbal command (e.g., verbal
information/command 44). As discussed above, the plurality of
disparate platforms (e.g., disparate platforms 46, 48, 50, 52, 54,
56) may include medical imaging platform 46; medical report
platform 48; medical record platform 50; conversational AI platform
52; illumination platform 54 and/or medical analysis platform
56.
[0063] When processing 202 the verbal command (e.g., verbal
information/command 44) to generate a platform-useable command
(e.g., platform-useable command 60) based, at least in part, upon
the verbal command (e.g., verbal information/command 44),
communication process 10 may process 204 the verbal command (e.g.,
verbal information/command 44) via a conversational AI platform
(e.g., conversational AI platform 52) to generate the
platform-useable command (e.g., platform-useable command 60) based,
at least in part, upon the verbal command (e.g., verbal
information/command 44).
[0064] While conversational AI platform 52 is shown to be executed
on report computing system 34, this is for illustrative purposes
only and is not intended to be a limitation of this disclosure, as
other configurations are possible and are considered to be within
the scope of this disclosure. For example, conversational AI
platform 52 may be executed on any other computing system (e.g.,
computing systems 12, 30, 32, 36),
[0065] As is known in the art, conversational AI is a technology
that enables speech-based interaction between humans and computing
systems. Accordingly, conversational AI platform 52 may process
human speech (e.g., verbal information/command 44) to decipher the
same so that e.g., a computing system may effectuate a
computer-based response and/or render a speech-based response.
[0066] Conversational AI platform 52 may utilize Natural language
Understanding (NLU). As is known in the art, NLU is a branch of
artificial intelligence (AI) that uses computer software to
understand verbal inputs provided by a user (e.g., clinician 38).
NLU may directly enable human-computer interaction (HCl), wherein
the understanding of natural human language may enable computers to
understand human-provided commands (without the formalized syntax
of computer languages) and further enable these computers to
respond to the human in their own language. The field of NLU is an
important and challenging subset of natural language processing
(NLP), as NLU is tasked with communicating with untrained
individuals and understanding their intent. Accordingly, NLU goes
beyond understanding words and actually interprets the meaning of
such words. NLU may use algorithms to reduce human speech into a
structured ontology, fleshing out such things as intent, timing,
locations and sentiments.
[0067] Once generated, communication process 10 may provide 206 the
platform-useable command (e.g., platform-useable command 60) to at
least a portion of the plurality of disparate platforms (e.g.,
disparate platforms 46, 48, 50, 52, 54, 56) via the communication
computing system (e.g., communication computing system 12).
[0068] For the following example, assume that monitor 150 is a
diagnostic healthcare display (e.g., such as a healthcare display
offered by Barco.TM.). Accordingly, monitor 150 may be controllable
by illumination platform 54, which may be executed on workstation
computing system 36. Through the use of illumination platform 54,
clinician 38 may control various aspects of monitor 150, such as
adjusting the brightness, adjusting the contrast, and enabling
resolution enhancing features. In order to enable such control of
monitor 150, monitor 150 may execute illumination application 166,
which may be configured to process commands received from
illumination platform 54.
[0069] For the following example, assume that verbal
information/command 44 provided by clinician 38 is "Hey Monitor . .
. Turn on Illuminate", which instructs monitor 150 to turn on a
resolution enhancing feature called "Illuminate". Accordingly,
communication process 10 (via conversation AI platform) may process
202 verbal information/command 44 (e.g., "Hey Monitor . . . Turn on
Illuminate") to generate a platform-useable command (e.g.,
platform-useable command 60), wherein an example of
platform-useable command 60 may include "Monitor: Illuminate
Status=1".
[0070] When providing 206 the platform-useable command (e.g.,
platform-useable command 60) to at least a portion of the plurality
of disparate platforms (e.g., disparate platforms 46, 48, 50, 52,
54, 56) via the communication computing system (e.g., communication
computing system 12), communication process 10 may: [0071] receive
208 the platform-useable command (e.g., platform-useable command
60) on the communication computing system (e.g., communication
computing system 12); and [0072] broadcast 210 the platform-useable
command (e.g., platform-useable command 60) to at least a portion
of the plurality of disparate platforms (e.g., disparate platforms
46, 48, 50, 52, 54, 56).
[0073] As discussed above, communication process 10 may enable 200
clinician 38 to issue verbal information/command 44 (e.g., "Hey
Monitor . . . Turn on Illuminate"), which may be processed 204 by
conversational AI platform 52 (which is executed on report
computing system 34) to generate platform-useable command 60 (e.g.,
Monitor: Illuminate Status=1). Conversational AI platform 52 may
then provide platform-useable command 60 to communication computing
system 12.
[0074] Once the platform-useable command (e.g., platform-useable
command 60) is received 208 on the communication computing system
(e.g., communication computing system 12), the communication
computing system (e.g., communication computing system 12) may
broadcast 210 the platform-useable command (e.g., platform-useable
command 60) to the a portion of the plurality of disparate
platforms (e.g., illumination platform 54).
[0075] Once broadcast 210, communication process 10 may receive 212
the platform-useable command (e.g., command 46) on at least one of
the plurality of disparate platforms (e.g., computing systems 12,
28, 30, 32, 34). For example, communication process 10 may receive
212 platform-useable command 60 on illumination platform 54 (which
is executed on workstation computing system 36). Communication
process 10 may then process 214 platform-useable command 60 on
illumination platform 54, wherein illumination platform 54 may
provide the necessary commands to illumination application 166
(which is executed on monitor 150) so that the Illuminate
functionality may be turned on.
[0076] In the event that the platform-useable command 60 has some
ambiguity, illumination application 166/illumination platform 54
(via communication computing system 12.fwdarw.conversational AI
platform 52) may make an inquiry (possibly verbally) to clarify the
ambiguity. For example, if Illuminate has three brightness levels,
illumination application 166/illumination platform 54 may verbally
ask clinician 38 "What level of brightness would you prefer?"
[0077] C) Information Broadcast
[0078] Referring also to FIG. 5 and as discussed above,
communication process 10 may define 100 a communication computing
system (e.g., communication computing system 12) within a computing
network (e.g., network 14 and/or network 18). This computing
network (e.g., network 14 and/or network 18) may couple various
computing systems (e.g., computing systems 12, 30, 32, 34, 36)
configured to provide information (e.g., data 20) concerning
various topics. Disparate platforms (e.g., disparate platforms 46,
48, 50, 52, 54, 56) executed on these computing systems (e.g.,
computing systems 12, 30, 32, 34, 36) may generate and/or modify
information (e.g., data 20), which may be provided to other
computing systems within the computing network (e.g., network 14
and/or network 18).
[0079] As discussed above, communication computing system 12 (in
combination with communication process 10) may be configured to
effectuate communication between computing systems 30, 32, 34, 36,
wherein communication computing system 12 may receive data from one
disparate platform and broadcast the data to another disparate
platform. As will be discussed below in greater detail, in order to
avoid communication computing system 12 broadcasting all data to
all disparate platforms, communication process 10 may be configured
to enable disparate platforms to register to receive only certain
pieces of data.
[0080] Communication process 10 may enable 250 one or more specific
disparate platforms (e.g., disparate platforms 46, 48, 50, 52, 54,
56), included within the plurality of disparate platforms (e.g.,
disparate platforms 46, 48, 50, 52, 54, 56), to register with the
communication computing system (e.g., communication computing
system 12) to receive information (e.g., data 20) concerning a
specific topic (e.g., a specific patient).
[0081] As discussed above, assume for this example that clinician
38 is using medical image platform 46 (executed on collaborating
computing system 30) to review chest x-ray image 160 of patient
John Smith, wherein clinician 38 is populating medical report 40
using medical report platform 48 (executed on report computing
system 34). Accordingly, medical report platform 48 may be
interested in receiving all information that concerns patient John
Smith (as clinician 38 has utilized medical report platform 48 to
populate the medical report (e.g., medical report 40) of patient
John Smith).
[0082] When one or more specific disparate platforms (e.g.,
disparate platforms 46, 48, 50, 52, 54, 56) registers with the
communication computing system (e.g., communication computing
system 12) to receive information (e.g., data 20) concerning a
specific topic (e.g., a specific patient), the one or more specific
disparate platforms (e.g., disparate platforms 46, 48, 50, 52, 54,
56) may subscribe 252 with the communication computing system
(e.g., communication computing system 12) to receive information
(e.g., data 20) concerning the specific topic (e.g., a specific
patient) that is broadcast by the communication computing system
(e.g., communication computing system 12).
[0083] Accordingly, medical report platform 48 may subscribe 252
with communication computing system 12 to receive information
(e.g., data 20) concerning the specific topic (e.g., patient John
Smith) that is broadcast by the communication computing system
(e.g., communication computing system 12). Once medical report
platform 48 is subscribed 252, any information that concerns the
specific topic for which medical report platform 48 has subscribed
(in this example, patient John Smith) will be broadcast to medical
report platform 48. Accordingly, any and all information that
concerns patient John Smith (such as chest x-ray image 160) will be
broadcast to/received by medical report platform 48. Conversely,
any and all information that concerns other patients (for which
medical report platform 48 has not subscribed) will not be
broadcast to/received by medical report platform 48.
[0084] For the following example, assume that medical report
platform 48 subscribed 252 to receive information concerning
patient John Smith. Further assume that medical image platform 46
provides another x-ray image (e.g., data 62) that concerns patent
John Smith. As discussed above, communication computing system 12
(in combination with communication process 10) may be configured to
effectuate communication between computing systems 30, 32, 34, 36,
wherein communication computing system 12 may receive data from one
disparate platform and broadcast the data to another disparate
platform. Accordingly, communication process 10 may receive 254, on
the communication computing system (e.g., communication computing
system 12), information (e.g., data 62) concerning the specific
topic (e.g., patient John Smith).
[0085] When receiving 254, on the communication computing system
(e.g., communication computing system 12), information (e.g., data
62) concerning the specific topic, communication process 10 may
receive 256 on communication computing system 12 information
concerning various topics. As could be imagined, since
communication computing system 12 effectuates communication between
computing systems 30, 32, 34, 36, communication computing system 12
would receive information concerning various topics (e.g., various
patients in this example).
[0086] Further and when receiving 254, on the communication
computing system (e.g., communication computing system 12),
information (e.g., data 62) concerning the specific topic (e.g., a
specific patient), communication process 10 may process 258 the
information concerning the various topics (e.g., various patients)
to determine if the information concerning the various topics
(e.g., various patients) includes information (e.g., data 62)
concerning the specific topic (e.g., patient John Smith).
[0087] Communication process 10 may provide 260 the information
(e.g., data 62) concerning the specific topic (e.g., patient John
Smith) to the one or more specific disparate platforms (e.g.,
medical report platform 48) that registered with the communication
computing system (e.g., communication computing system 12) to
receive information (e.g., data 62) concerning the specific topic
(e.g., patient John Smith).
[0088] When providing 260 the information (e.g., data 62)
concerning the specific topic (e.g., patient John Smith) to the one
or more specific disparate platforms (e.g., medical report platform
48) that registered with the communication computing system (e.g.,
communication computing system 12) to receive information (e.g.,
data 62) concerning the specific topic (e.g., patient John Smith),
communication process 10 may proactively broadcast 262 the
information (e.g., data 62) concerning the specific topic (e.g.,
patient John Smith) to the one or more specific disparate platforms
(e.g., medical report platform 48) that registered with the
communication computing system (e.g., communication computing
system 12) to receive information (e.g., data 62) concerning the
specific topic (e.g., patient John Smith).
[0089] Accordingly and in this example, medical report platform 48
receives all information that concerns patient John Smith and does
not receive information that concerns other patients for which they
did not register.
D) Exposing an Endpoint
[0090] Referring also to FIG. 6 and as discussed above,
communication process 10 may define 100 a communication computing
system (e.g., communication computing system 12) within a computing
network (e.g., network 14 and/or network 18). This computing
network (e.g., network 14 and/or network 18) may couple various
computing systems (e.g., computing systems 12, 30, 32, 34, 36)
configured to provide information (e.g., data 20) concerning
various topics. Disparate platforms (e.g., disparate platforms 46,
48, 50, 52, 54, 56) executed on these computing systems (e.g.,
computing systems 12, 30, 32, 34, 36) may generate and/or modify
information (e.g., data 20), which may be provided to other
computing systems within the computing network (e.g., network 14
and/or network 18).
[0091] Further and as discussed above, communication computing
system 12 (in combination with communication process 10) may be
configured to effectuate communication between computing systems
30, 32, 34, 36, wherein communication computing system 12 may
receive data from one disparate platform and broadcast the data to
another disparate platform.
[0092] Further and as discussed above, communication computing
system 12 may be a local computing system directly coupled to e.g.,
computing systems 30, 32, 34, 36 via a local area network (e.g.,
network 14) and/or a cloud-based computing system (e.g., a
cloud-based resource) indirectly coupled to e.g., computing systems
30, 32, 34, 36 via network 18 (e.g., the internet). Accordingly and
in order for such communication to occur, the location of
communication computing system 12 must be known to the disparate
platforms (e.g., disparate platforms 46, 48, 50, 52, 54, 56)
[0093] In order to effectuate such communication, communication
process 10 may expose 300 an endpoint (e.g., endpoint 64) within
the computing network (e.g., network 14 and/or network 18) that
provides directory assistance to enable one or more specific
disparate platforms, included within the plurality of disparate
platforms (e.g., disparate platforms 46, 48, 50, 52, 54, 56), to
communicate with the communication computing system (e.g.,
communication computing system 12).
[0094] As used in this disclosure and as will be discussed below in
greater detail, an endpoint (e.g., endpoint 64) may be any
feature/functionality that provides directory assistance to enable
the disparate platforms (e.g., disparate platforms 46, 48, 50, 52,
54, 56) to ascertain the location of communication computing system
12.
[0095] For example and when exposing 300 an endpoint (e.g.,
endpoint 64) within the computing network (e.g., network 14 and/or
network 18), communication process 10 may publish 302 a well-known
uniform resource identifier (e.g., URI 66) within the computing
network (e.g., network 14 and/or network 18) to enable one or more
specific disparate platforms, included within the plurality of
disparate platforms (e.g., disparate platforms 46, 48, 50, 52, 54,
56), to communicate with the communication computing system (e.g.,
communication computing system 12).
[0096] As is known in the art, a uniform resource identifier (e.g.,
URI 66) is a unique identifier used by web technologies. URIs may
be used to identify anything, including real-world objects (e.g.,
people and places, concepts, or information resources such web
pages and books). Some URIs provide a means of locating and
retrieving information resources on a network (e.g., either on the
Internet or on another private network, such as a computer
filesystem or an Intranet), wherein these are referred to as
Uniform Resource Locators (URLs). Other URIs may provide only a
unique name, without a means of locating or retrieving the resource
or information about it, wherein these are referred to as Uniform
Resource Names (URNs).
[0097] Further and when exposing 300 an endpoint (e.g., endpoint
62) within the computing network (e.g., network 14 and/or network
18), communication process 10 may execute 304 a connector
application (e.g., connector application 68) on a computing
platform (e.g., workstation computing system 68) coupled to the
computing network (e.g., network 14 and/or network 18), wherein the
connector application (e.g., connector application 68) publishes
the well-known uniform resource identifier (e.g., URI 66) within
the computing network (e.g., network 14 and/or network 18) to
enable one or more specific disparate platforms, included within
the plurality of disparate platforms (e.g., disparate platforms 46,
48, 50, 52, 54, 56), to communicate with the communication
computing system (e.g., communication computing system 12)
[0098] When exposing 300 an endpoint (e.g., endpoint 62) within the
computing network (e.g., network 14 and/or network 18),
communication process 10 may monitor 306 the computing network
(e.g., network 14 and/or network 18) for a communication request
(e.g., request 70) by a specific disparate platform included within
the plurality of disparate platforms (e.g., disparate platforms 46,
48, 50, 52, 54, 56).
[0099] Further and when exposing 300 an endpoint (e.g., endpoint
62) within the computing network (e.g., network 14 and/or network
18), communication process 10 may provide 308 directory assistance
(if a communication request (e.g., request 70) is received) to
enable the one or more specific disparate platforms, included
within the plurality of disparate platforms (e.g., computing
systems 12, 28, 30, 32, 34), to communicate with the communication
computing system (e.g., communication computing system 12).
[0100] For the following example, assume that communication
computing system 12 is a cloud-based resource and, therefore, is
not directly coupled to network 14 but is indirectly coupled to
network 14 through network 18 (e.g., the internet). Accordingly,
URI 66 may identify the internet-based location of cloud-based
communication computing system 12.
[0101] For example, upon workstation computing system 36 starting
up and/or initiating a session, communication process 10 may expose
300 endpoint 64 within the computing network (e.g., network 14
and/or network 18), wherein endpoint 64 may be configured to
provide directory assistance that enables one or more disparate
platforms (included within disparate platforms 46, 48, 50, 52, 54,
56) to communicate with communication computing system 12.
Specifically and when exposing 300 endpoint 62 within the computing
network (e.g., network 14 and/or network 18), communication process
10 may execute 304 connector application 68 on workstation
computing system 68, wherein connector application 68 publishes URI
66 so that any disparate platforms (included within disparate
platforms 46, 48, 50, 52, 54, 56) may communicate with
communication computing system 12.
[0102] For the various reason discussed above, medical report
platform 48 may be interested in receiving all information that
concerns patient John Smith (as clinician 38 has utilized medical
report platform 48 to populate the medical report (e.g., medical
report 40) of patient John Smith. Therefore, medical report
platform 48 may wish to subscribe to receive information (e.g.,
data 20) concerning patient John Smith from communication computing
system 12. Accordingly, medical report platform 48 may generate and
provide a communication request (e., request 70) for communication
with communication computing system 12.
[0103] As discussed above, communication process 10 may monitor 306
the computing network (e.g., network 14 and/or network 18) for a
communication request (e.g., request 70) by (in this example)
medical report platform 48. Upon receiving request 70,
communication process 10 may provide 308 directory assistance to
enable (in this example) medical report platform 48 to communicate
with communication computing system 12. Specifically, communication
process 10 may provide 308 directory assistance by e.g., having
connector application 68 publishes URI 66 so that medical report
platform 48 knows the location (i.e., address) of communication
computing system 12.
E) Populating Medical Reports
[0104] Referring also to FIG. 7, communication process 10 may
receive 350 observational medical data (e.g., data 58). When
receiving 350 this observational medical data (e.g., data 58),
communication process 10 may receive 352 observational medical data
(e.g., data 58) from one or more of: [0105] At Least One Disparate
Platform: For example, communication process 10 may be configured
to obtain observational medical data (e.g., data 58) from any of
the disparate platform (e.g., disparate platforms 46, 48, 50, 52,
54, 56) that are accessible to communication process 10. [0106] An
Existing Medical Record: For example, communication process 10 may
be configured to process existing medical records (e.g., medical
records 72) available via medical record platform 50 to extract
observational medical data (e.g., data 58). [0107] An Existing
Medical Report: For example, communication process 10 may be
configured to process existing medical reports (e.g., medical
reports 74) available via medical report platform 48 to extract
observational medical data (e.g., data 58). [0108] An Artificial
Intelligence Platform: For example, communication process 10 may be
configured to utilize an artificial intelligence platform (e.g.,
medical analysis platform 56) to process (for example) existing
medical records (e.g., medical records 72), existing medical
reports (e.g., medical reports 74), existing medical forms (e.g.,
handwritten note 76) and existing medical recordings (e.g., voice
recording 78) to extract observational medical data (e.g., data
58). [0109] Manually-Entered Data: For example, communication
process 10 may be configured to receive observational medical data
(e.g., data 58) manually entered by clinician 38 via e.g., audio
input device 42, a keyboard (not shown) and/or a pointing device
(not shown) coupled to workstation computing system 36.
[0110] Accordingly and when utilizing observational medical data
(e.g., data 58) to populate a medical report (e.g., medical report
40), this observational medical data (e.g., data 58) may be
obtained from basically any source. Further and as will be
discussed below in greater detail, this observational data (e.g.,
data 58) need not be provided by a human being (e.g., clinician 38)
and may be provided without human intervention via e.g., artificial
intelligence.
[0111] Once received 350, communication process 10 may process 354
the observational medical data (e.g., data 58) to populate at least
a portion of a medical report (e.g., medical report 40).
[0112] When processing 354 the observational medical data (e.g.,
data 58) to populate at least a portion of a medical report (e.g.,
medical report 40), communication process 10 may: [0113] process
356 the observational medical data (e.g., data 58) to generate
natural language prose 80 using e.g., conversational AI platform
52; and [0114] populate 358 at least a portion of the medical
report (e.g., medical report 40) using natural language prose
80.
[0115] Continuing with the above-stated example, the observational
data (e.g., data 58) for patient John Smith identifies the
following: [0116] PATIENT: John Smith; [0117] TYPE: Growth; [0118]
LOCATION: Lower Quadrant of Left Lung; and [0119] SIZE: 5.1
Centimeters.
[0120] Accordingly and upon receiving 350 observational medical
data 58 (e.g., John Smith, Growth, Lower Quadrant of Left Lung, 5.1
Centimeters), communication process 10 may process 356 the
observational medical data (e.g., data 58) to generate natural
language prose 80 using e.g., conversational AI platform 52
executed on report computing system 34. For example, communication
process 10 may process 356 observational medical data 58 (e.g.,
John Smith, Growth, Lower Quadrant of Left Lung, 5.1 Centimeters)
to generate natural language prose 80, an example of which may
include but is not limited to "Patient John Smith has a growth in
the lower quadrant of left lung that measures 5.1 centimeters".
Once natural language prose 80 is generated, communication process
10 may populate 358 at least a portion of the medical report (e.g.,
medical report 40) using natural language prose 80. For example,
communication process 10 may populate 358 field 164 within medical
report 40 to state that "Patient John Smith has a growth in the
lower quadrant of left lung that measures 5.1 centimeters"
[0121] Additionally/alternatively and when processing 354 the
observational medical data (e.g., data 58) to populate at least a
portion of a medical report (e.g., medical report 40),
communication process 10 may process 360 the observational medical
data (e.g., data 58) using a script (e.g., script 82) to populate
at least a portion of the medical report (e.g., medical report 40).
For example, script 82 may be defined by e.g., clinician 38 and may
generally function as an if/then statement that may be used when
mapping data into the appropriate fields within medical report 40.
For example, script 82 may define keywords and/or standardized
medical codes that are associable with specific fields within a
medical report. For example, the keyword: [0122] "renal" may be
associable with the "Kidneys" field within medical report 40;
[0123] "pneumonia" may be associable with the "Lungs" field within
medical report 40; and [0124] "aorta" may be associable with the
"Heart" field within medical report 40.
[0125] Additionally, script 82 may be utilized to quantify an
entity. For example, script 82 say that: [0126] if a growth 6.00 cm
or greater, it is a large growth; [0127] if a growth is 3.00-5.99
cm, it is a medium growth; and [0128] if a growth is less than 2.99
cm, it is a small growth.
[0129] Additionally/alternatively and when processing 354 the
observational medical data (e.g., data 58) to populate at least a
portion of a medical report (e.g., medical report 40),
communication process 10 may process 362 the observational medical
data (e.g., data 58) using a template (e.g., template 84) to
populate at least a portion of the medical report (e.g., medical
report 40). For example, template 84 may be manually-defined by
e.g., clinician 38 and may generally provide the structure for the
language that is used to populate medical report 40.
[0130] In the example discussed above, communication process 10 may
populate process medical report 40 with "Patient John Smith has a
growth in the lower quadrant of left lung that measures 5.1
centimeters". As discussed above, the observational data (e.g.,
data 58) included within this statement is "______ John Smith
______ growth ______ lower quadrant of left lung 5.1 centimeters".
Accordingly, an example of template 84 (which may define the
structure for this statement) may be "Patient ______ has a ______
in the ______ that measures ______".
[0131] While template 84 is described above as being defined by a
human being (e.g., clinician 38), other configurations are possible
and are considered to be within the scope of this disclosure. For
example and as will be discussed below in greater detail, template
84 may be generated via artificial intelligence.
[0132] Accordingly and when processing 354 the observational
medical data (e.g., data 58) to populate at least a portion of a
medical report (e.g., medical report 40), communication process 10
may process 364 the observational medical data (e.g., data 58)
using extracted patterns (e.g., extracted patterns 86) to populate
at least a portion of the medical report (e.g., medical report 40),
wherein these extracted patterns (e.g., extracted patterns 86) may
be used to generate one or more templates (e.g., template 84).
[0133] For example, these extracted patterns (e.g., extracted
patterns 86) may be generated using artificial intelligence (via
e.g., medical analysis platform 56) to process a plurality of
previously-generated medical reports (e.g., medical reports 74).
For example, communication process 10 may utilize medical analysis
platform 56 to analyze medical reports 74 to identify patterns
within these medical reports.
[0134] As is known in the art, pattern recognition is the process
of recognizing patterns using a machine learning algorithm. Pattern
recognition may be defined as the classification of data based on
knowledge already gained or on statistical information extracted
from patterns and/or their representation. Pattern recognition is
generally the ability to detect arrangements of characteristics or
data that yield information about a given system or data set. In a
technological context, a recognized patterns might be recurring
sequences of data over time that may be used to predict trends,
particular configurations of features in images that identify
objects, frequent combinations of words and phrases for natural
language processing (NLP), or particular clusters of behaviors on a
network that could indicate an attack.
[0135] Accordingly, communication process 10 may utilize medical
analysis platform 56 to analyze previously-generated medical
reports 74 to identify patterns (e.g., extracted patterns 86)
within these previously-generated medical reports 74, wherein these
extracted patterns (e.g., extracted patterns 86) may be used to
generate one or more templates (e.g., template 84). For example and
upon communication process 10 utilizing medical analysis platform
56 to analyze previously-generated medical reports 74, an extracted
pattern (e.g., extracted pattern 86) may be identified, wherein
entities are typically reported as follows: "Patient ______ has a
______ in the ______ that measures ______". Accordingly, this
extracted pattern may be utilized to generate one or more templates
(e.g., template 84).
[0136] As will be discussed below in greater detail, these
extracted patterns (e.g., extracted patterns 86) may be used by
communication process 10 to define options for clinician 38 (e.g.,
a radiologist, a cardiologist or a pathologist) as to e.g., which
field within medical report 40 a particular statement (e.g.,
"Patient John Smith has a growth in the lower quadrant of left lung
that measures 5.1 centimeters") should be placed.
F) Medical Report Field Association
[0137] Referring also to FIG. 8 and as discussed above,
communication process 10 may receive 400 medical information (e.g.,
data 20). As also discussed above, communication process 10 may
utilize this medical information (e.g., data 20) to populate
medical reports (e.g., medical report 40).
[0138] The medical information (e.g., data 20) may include one or
more of: [0139] medical information (e.g., data 20) dictated by
clinician 38 (e.g., a radiologist, a cardiologist or a
pathologist). For example, clinician 38 may dictate verbal
information via e.g., audio input device 42 coupled to workstation
computing system 36. This verbal information may be processed via
artificial intelligence platform (e.g., conversational AI platform
and/or medical analysis platform 56). [0140] medical information
(e.g., data 20) obtained from at least one disparate platform
(e.g., disparate platforms 46, 48, 50, 52, 54, 56). [0141] medical
information (e.g., data 20) obtained from an existing medical
record (e.g., medical records 72). [0142] medical information
(e.g., data 20) obtained from an artificial intelligence platform
(e.g., medical analysis platform 56). [0143] medical information
(e.g., data 20) obtained from a form (e.g., handwritten note 76).
[0144] medical information (e.g., data 20) that is manually entered
by clinician 38 via e.g., a keyboard (not shown) and/or a pointing
device (not shown) coupled to workstation computing system 36.
[0145] However, in order for communication process 10 to properly
utilize such medical information (e.g., data 20), communication
process 10 will need to know the appropriate field into which to
place medical information (e.g., data 20).
[0146] Accordingly, communication process 10 may determine 402 if
the medical information (e.g., data 20) is associable with a
specific field (e.g., field 164) within a medical report (e.g.,
medical report 40).
[0147] When determining 402 if the medical information (e.g., data
20) is associable with a specific field (e.g., field 164) within a
medical report (e.g., medical report 40), communication process 10
may: [0148] associate 404 one or more keywords and/or standardized
medical codes with the specific field (e.g., field 164) within the
medical report (e.g., medical report 40); [0149] monitor 406 the
medical information (e.g., data 20) for the occurrence of the one
or more keywords and/or standardized medical codes; and [0150]
associate 408 the medical information (e.g., data 20) with the
specific field if the medical information (e.g., data 20) includes
the one or more keywords and/or standardized medical codes.
[0151] As discussed above, script 82 may be defined by e.g.,
clinician 38 and may generally function as an if/then statement
that may be used when mapping data into the appropriate fields
within medical report 40. For example, script 82 may define
keywords and/or standardized medical codes that are associable with
specific fields within a medical report. For example, the keyword:
[0152] "renal" may be associable with the "Kidneys" field within
medical report 40; [0153] "pneumonia" may be associable with the
"Lungs" field within medical report 40; and [0154] "aorta" may be
associable with the "Heart" field within medical report 40.
[0155] Accordingly and when determining 402 if the medical
information (e.g., data 20) is associable with a specific field
(e.g., field 164) within a medical report (e.g., medical report
40), communication process 10 may monitor 406 the medical
information (e.g., data 20) for the occurrence of the one or more
keywords and/or standardized medical codes.
[0156] Therefore: [0157] if the medical information (e.g., data 20)
includes the keyword "renal", the medical information (e.g., data
20) may be associated 408 with the "Kidneys" field (e.g., field
168) within medical report 40; [0158] if the medical information
(e.g., data 20) includes the keyword "pneumonia", the medical
information (e.g., data 20) may be associated 408 with the "Lungs"
field (e.g., field 164) within medical report 40; and [0159] if the
medical information (e.g., data 20) includes the keyword "aorta",
the medical information (e.g., data 20) may be associated 408 with
the "Heart" field (e.g., field 170) within medical report 40.
[0160] If the medical information (e.g., data 20) is associable
with the specific field (e.g., one of fields 164, 168, 170) within
the medical report (e.g., medical report 40), communication process
10 may populate 410 the specific field (e.g., one of fields 164,
168, 170) within the medical report (e.g., medical report 40) with
at least a portion of the medical information (e.g., data 20).
[0161] When associating 404 one or more keywords and/or
standardized medical codes with the specific field (e.g., one of
fields 164, 168, 170) within the medical report (e.g., medical
report 40), communication process 10 may use 412 artificial
intelligence (e.g., medical analysis platform 56) to process a
plurality of previously-generated medical reports (e.g., medical
report 40) to associate the one or more keywords and/or
standardized medical codes with the specific field (e.g., one of
fields 164, 168, 170) within the medical report (e.g., medical
report 40).
[0162] As discussed above, pattern recognition is the process of
recognizing patterns using a machine learning algorithm.
Accordingly, communication process 10 may utilize medical analysis
platform 56 to analyze previously-generated medical reports 74 to
identify patterns (e.g., extracted patterns 86) within these
previously-generated medical reports 74. These extracted patterns
(e.g., extracted patterns 86) may be used to identify the
above-described keywords and/or standardized medical codes.
[0163] For example, communication process 10 may use 412 artificial
intelligence (e.g., medical analysis platform 56) to determine
that: [0164] 96.3% of the time that "renal" is mentioned, it is in
the "Kidneys" field (e.g., field 168) within medical report 40;
[0165] 98.9% of the time that "pneumonia" is mentioned, it is in
the "Lungs" field (e.g., field 164) within medical report 40; and
-97.4% of the time that "aorta" is mentioned, it is in the "Heart"
field (e.g., field 170) within medical report 40.
[0166] Accordingly, communication process 10 may associate 404:
[0167] "renal" with the "Kidneys" field (e.g., field 168) within
medical report 40; [0168] "pneumonia" with the "Lungs" field (e.g.,
field 164) within medical report 40; and [0169] "aorta" with the
"Heart" field (e.g., field 170) within medical report 40.
[0170] If the medical information (e.g., data 20) is not associable
with the specific field (e.g., one of fields 164, 168, 170) within
the medical report (e.g., medical report 40), communication process
10 may place 414 at least a portion of the medical information
(e.g., data 20) within a last-used field within the medical report
(e.g., medical report 40). For example, if clinician 38 was
dictating (via e.g., audio input device 42) medical information
(e.g., data 20) that included the keyword "renal", that medical
information (e.g., data 20) would be placed within field 168 (for
the reasons discussed above). If clinician 38 paused for a bit and
then dictated "So I recommend the appropriate treatment", this
medical information (e.g., data 20) does not include any keywords
and/or standardized medical codes. However, being it was dictated
following information that was associable with field 168,
communication process 10 may place 414 at least a portion of the
medical information (e.g., "So I recommend the appropriate
treatment") within a last-used field (e.g., field 168) within the
medical report (e.g., medical report 40).
[0171] Additionally/alternatively, if the medical information
(e.g., data 20) is not associable with the specific field (e.g.,
one of fields 164, 168, 170) within the medical report (e.g.,
medical report 40), communication process 10 may mark 416 at least
a portion of the medical information (e.g., data 20) as uncertain
concerning location. For example, communication process 10 may
insert a parenthetical (e.g., PLEASE CONFIRM LOCATION) prior to or
after the information in question to mark 416 the location of the
information as uncertain.
[0172] Further and if the medical information (e.g., data 20) is
not associable with the specific field (e.g., one of fields 164,
168, 170) within the medical report (e.g., medical report 40),
communication process 10 may ask 418 clinician 38 (e.g., a
radiologist, a cardiologist or a pathologist) where at least a
portion of the medical information (e.g., data 20) should be
located. For example, communication process 10 may render popup
window 172 that asks 418 clinician 38 to confirm the location of
the information in question.
G) Identifying Actionable Items
[0173] Referring also to FIG. 9 and as discussed above,
communication process 10 may receive 400 medical information (e.g.,
data 20). As also discussed above, communication process 10 may
utilize this medical information (e.g., data 20) to populate
medical reports (e.g., medical report 40)
[0174] As discussed above, this medical information (e.g., data 20)
may include one or more of: [0175] medical information (e.g., data
20) dictated by clinician 38 (e.g., a radiologist, a cardiologist
or a pathologist). For example, clinician 38 may dictate verbal
information via e.g., audio input device 42 coupled to workstation
computing system 36. This verbal information may be processed via
artificial intelligence platform (e.g., conversational AI platform
and/or medical analysis platform 56). [0176] medical information
(e.g., data 20) obtained from at least one disparate platform
(e.g., disparate platforms 46, 48, 50, 52, 54, 56). [0177] medical
information (e.g., data 20) obtained from an existing medical
record (e.g., medical records 72). [0178] medical information
(e.g., data 20) obtained from an artificial intelligence platform
(e.g., medical analysis platform 56). [0179] medical information
(e.g., data 20) obtained from a form (e.g., handwritten note 76).
[0180] medical information (e.g., data 20) that is manually entered
by clinician 38 via e.g., a keyboard (not shown) and/or a pointing
device (not shown) coupled to workstation computing system 36.
[0181] Communication process 10 may process 450 the medical
information (e.g., data 20) to determine if the medical information
(e.g., data 20) includes one or more actionable items. For the
following discussion, an actionable item may be something included
within medical information (e.g., data 20) that requires some form
of follow up/intervention. As could be imagined, these actionable
items (and the associated follow up) may vary in severity from low
severity to high severity. For example: [0182] If medical
information (e.g., data 20) includes a patient's weight, and the
weight of the patient has increased ten pounds since the last time
that the patient visited the doctor; this may be considered a
low-severity actionable item. [0183] If medical information (e.g.,
data 20) includes the patient's blood pressure, and the blood
pressure of the patient is 160 over 120; this may be considered a
mid-severity actionable item. [0184] If medical information (e.g.,
data 20) includes an MRI image of a patient's brain, and the MRI
image reveals a brain bleed situation; this may be considered a
high-severity actionable item.
[0185] The actionable items that may be included within the medical
information (e.g., data 20) may be defined in various mays. For
example, some actionable items may be easily definable via a script
(e.g., script 82).
[0186] For example and with respect to the blood pressure of a
patient, script 82 may define the following:
TABLE-US-00001 Systolic (mm Hg) Diastolic (mm Hg) Normal Below 120
Below 80 Elevated (hypertension) 120-129 Below 80 Stage 1
hypertension 130-139 80-90 Stage 2 hypertension 140 or above 90 or
above Hypertensive crisis Over 180 Over 120
[0187] Further and with respect to the weight of a patient, script
82 may define the following:
TABLE-US-00002 BMI 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34
35 Height (inches) Body Weight (pounds) 58 91 96 100 105 110 115
119 124 129 134 138 143 148 153 158 162 167 59 94 99 104 109 114
119 124 128 133 138 143 148 153 158 163 168 173 60 97 102 107 112
118 123 128 133 138 143 148 153 158 163 168 174 179 61 100 106 111
116 122 127 132 137 143 148 153 158 164 169 174 180 185 62 104 109
115 120 126 131 136 142 147 153 158 164 169 175 180 186 191 63 107
113 118 124 130 135 141 146 152 158 163 169 175 180 186 191 197 64
110 116 122 128 134 140 145 151 157 163 169 174 180 186 192 197 204
65 114 120 126 132 138 144 150 156 162 168 174 180 186 192 198 204
210 66 118 124 130 136 142 148 155 161 167 173 179 186 192 198 204
210 216 67 121 127 134 140 146 153 159 166 172 178 185 191 198 204
211 217 223 68 125 131 138 144 151 158 164 171 177 184 190 197 203
210 216 223 230 69 128 135 142 149 155 162 169 176 182 189 196 203
209 216 223 230 236 70 132 139 146 153 160 167 174 181 188 195 202
209 216 222 229 236 243 71 136 143 150 157 165 172 179 186 193 200
208 215 222 229 236 243 250 72 140 147 154 162 169 177 184 191 199
206 213 221 228 235 242 250 258 73 144 151 159 166 174 182 189 197
204 212 219 227 235 242 250 257 265 74 148 155 163 171 179 186 194
202 210 218 225 233 241 249 256 264 272 75 152 160 168 176 184 192
200 208 216 224 232 240 248 256 264 272 279 76 156 164 172 180 189
197 205 213 221 230 238 246 254 263 271 279 287
[0188] Accordingly and for such numerically-quantifiable actionable
items, script 82 may be configured to define such action items, as
well as associate a severity with the action item that depends upon
e.g., the actionable item's position within the above-referenced
tables.
[0189] However, some actionable items may not be based upon
numbers. For example, a brain bleed is not based upon numbers and
is based upon what appears within an image of a patient's brain.
Additionally, a growth in the lung of a patient is not based upon
numbers and is based upon what appears in an image of a patient's
chest.
[0190] As discussed above, pattern recognition is the process of
recognizing patterns using a machine learning algorithm.
Accordingly, communication process 10 may utilize medical analysis
platform 56 to analyze e.g., medical records 72,
previously-generated medical reports 74, and/or medical images
(e.g., chest x-ray image 160 available from medical image platform
46) to identify patterns (e.g., extracted patterns 86) within these
medical records 72, previously-generated medical reports 74, and/or
medical images (e.g., chest x-ray image 160 available from medical
image platform 46).
[0191] For example, medical images in combination with medical
reports/records may be analyzed to determine: [0192] what a typical
brain bleed looks like; [0193] what a typical aortic aneurysm looks
like, and [0194] what a typical lung tumor looks like.
[0195] These extracted patterns (e.g., extracted patterns 86) may
be used identify the above-described actionable items.
[0196] When processing 450 the medical information (e.g., data 20)
to determine if the medical information (e.g., data 20) includes
one or more actionable items, communication process 10 may
associate 452 one or more best practices with one or more
actionable items.
[0197] Some of these best practices may be easily definable via
e.g., script 82. For example, if you are ten pounds overweight, you
need to eat less and/or exercise more until you lose the ten
pounds. If your blood pressure is slightly elevated, you may need
to exercise more. While if your blood pressure is extremely
elevated, you may need to be put on high blood pressure
medication.
[0198] However, some best practices may be less numerically driven
and harder to discern. Accordingly and when associating 452 one or
more best practices with one or more actionable items,
communication process 10 may use 454 artificial intelligence (e.g.,
medical analysis platform 56) to process a plurality of
previously-generated medical reports (e.g., previously-generated
medical reports 74) to associate one or more best practices with
one or more actionable items.
[0199] Again, pattern recognition is the process of recognizing
patterns using a machine learning algorithm. Accordingly,
communication process 10 may utilize medical analysis platform 56
to analyze e.g., medical records 72, previously-generated medical
reports 74, and/or medical images (e.g., chest x-ray image 160
available from medical image platform 46) to identify patterns
(e.g., extracted patterns 86) within these medical records 72,
previously-generated medical reports 74, and/or medical images
(e.g., chest x-ray image 160 available from medical image platform
46).
[0200] For example, medical images in combination with medical
reports/records may be analyzed to determine: [0201] what a typical
response (a best practice) to a brain bleed is; [0202] what a
typical response (a best practice) to an aortic aneurysm is, and
[0203] what a typical response (a best practice) to a lung tumor
is.
[0204] These extracted patterns (e.g., extracted patterns 86) may
be used identify the above-described best practices.
[0205] If communication process 10 determines 450 that the medical
information (e.g., data 20) includes one or more actionable items,
communication process 10 may: [0206] determine 456 an appropriate
action item response; and [0207] execute 458 the action item
response.
[0208] When determining 456 an appropriate action item response,
communication process 10 may: [0209] determine 460 a severity for
the one or more actionable items; and [0210] identify 462 the
appropriate action item response based, at least in part, upon the
severity for the one or more actionable items.
[0211] Accordingly and as discussed above, if the blood pressure of
a patient is slightly elevated, the patient may need to exercise
more. However, if the blood pressure of a patient is extremely
elevated, the patient may need to be put on high blood pressure
medication.
[0212] When executing 458 the action item response, communication
process 10 may: [0213] identify 464 the one or more actionable
items to clinician 38 (e.g., a radiologist, a cardiologist or a
pathologist); [0214] suggest 466 to clinician 38 (e.g., a
radiologist, a cardiologist or a pathologist) one or more remedial
courses of action concerning the one or more actionable items;
and/or [0215] execute 468 one or more remedial courses of action
concerning the one or more actionable items.
[0216] For example, communication process 10 may identify 464 the
one or more actionable items to clinician 38 (e.g., a radiologist,
a cardiologist or a pathologist). Accordingly, clinician 38 may be
informed of all actionable items (regardless of severity).
Alternatively, clinician 38 may be informed of only mid-severity or
high-severity actionable items. When identifying 464 the one or
more actionable items to clinician 38, communication process 10 may
render a popup window (e.g., popup window 172) that identifies the
one or more actionable items to clinician 38.
[0217] Further, communication process 10 may suggest 466 to
clinician 38 (e.g., a radiologist, a cardiologist or a pathologist)
one or more remedial courses of action concerning the one or more
actionable items. As discussed above, clinician 38 may be informed
of some or all of the actionable items. Further, communication
process 10 may make suggestions to clinician 38 concerning how to
address these actionable items. When suggesting 466 one or more
remedial courses of action concerning the one or more actionable
items to clinician 38, communication process 10 may render a popup
window (e.g., popup window 172) that suggests that clinician 38
contact oncology concerning the growth shown in chest x-ray image
160.
[0218] Additionally, communication process 10 may execute 468 one
or more remedial courses of action concerning the one or more
actionable items. As discussed above, clinician 38 may be informed
of some or all of the actionable items and/or suggestions may be
made concerning how to address some or all of the actionable items
(as discussed above). Further and concerning high-severity
situations, communication process 10 may automatically execute a
remedial course of action. When executing 468 one or more remedial
courses of action concerning the one or more actionable items,
communications process 10 may e.g., automatically contact neurology
and automatically schedule a surgery suite when a patient is
determined to have a brain bleed.
H) Floating Window
[0219] Referring also to FIG. 10 and as discussed above,
communication process 10 may enable 500 clinician 38 (e.g., a
radiologist, a cardiologist or a pathologist) to review medical
information (e.g., data 20) received from one or more disparate
platforms (e.g., disparate platforms 46, 48, 50, 52, 54, 56). As
discussed above, these disparate platforms may include disparate
medical platforms (e.g., medical imaging platform 46; medical
report platform 48; medical record platform 50; conversational AI
platform 52; illumination platform 54 and/or medical analysis
platform 56.
[0220] Further and as discussed above, communication process 10 may
receive 502 observational medical data (e.g., data 58) from the
clinician 38 (e.g., a radiologist, a cardiologist or a pathologist)
concerning the medical information (e.g., data 20), wherein
communication process 10 may process 504 at least a portion of the
medical information (e.g., data 20) and/or the observational
medical data (e.g., data 58) to populate at least a portion of a
medical report (e.g., medical report 40).
[0221] Referring also to FIG. 11 and in order to enhance the user
experience of clinician 38, communication process 10 may render 506
a summary window (e.g., summary window 550) concerning the
population of the at least a portion of the medical report (e.g.,
medical report 40). Summary window 550 may be a transparent overlay
summary window, thus allowing clinician 38 to see the information
below summary window 550. Accordingly and regardless of where
summary window 550 is positioned within monitor 150, the content of
monitor 150 (in this example, chest x-ray image 160) will not be
obscured by summary window 550.
[0222] Communication process 10 may enable 508 clinician 38 (e.g.,
a radiologist, a cardiologist or a pathologist) to adjust one or
more of: [0223] Summary Window Size: In a fashion similar to that
of a window within a personal computer, communication process 10
may allow clinician 38 to adjust the size of summary window 550
(e.g., increased or decreased with respect to width or height).
[0224] Summary Window Position: In a fashion similar to that of a
window within a personal computer, the position of summary window
550 may be repositioned (e.g., dragged and dropped) within the
display area of monitor 150. Further and as shown in FIG. 3,
summary window 550 may be repositioned amongst the various monitors
(e.g., 150, 152, 154). Accordingly, communication process 10 may
allow clinician 38 to position summary window 550 within the
monitor on which they are currently working. So if clinician 38 is
utilizing monitor 150 to review chest x-ray image 160,
communication process 10 may allow clinician 38 to position summary
window 550 within monitor 150 so that clinician 38 can view summary
window 550 without needing to take their eyes off of (in this
example) chest x-ray image 160. [0225] Summary Window Transparency:
Communication process 10 may allow clinician 38 to adjust the
transparency of summary window 550, thus allowing clinician 38 to
adjust how visible the content of monitor 150 is through summary
window 550. For example, clinician 38 may adjust the transparency
of summary window 550 from very transparent (e.g., essentially
invisible) to not transparent at all (e.g., fully obscuring what is
underneath summary window 550) [0226] Summary Window Content:
Communication process 10 may allow clinician 38 to adjust what is
included within summary window 550. For example, communication
process 10 may allow clinician 38 to decide whether summary window
550 includes: [0227] a microphone status (e.g., microphone status
indicator 552) that informs clinician 38 as to whether the
microphone (e.g., audio input device 42) is currently turned on;
[0228] a current dictation mode (e.g., dictation status indicator
554) that informs clinician 38 as to whether or not they are
currently in dictation mode; [0229] an audio input level (e.g.,
audio input level indicator 556) that informs clinician 38 of the
audio level of their voice signal (as provided by audio input
device 42); [0230] a plurality of fields (e.g., plurality of fields
indicator 558) included within the medical report (e.g., medical
report 40); [0231] an active field (e.g., active field indicator
560) included within the medical report (e.g., medical report 40);
[0232] alerts (e.g., alert indicator 562) for one or more
actionable items; and [0233] an application waiting (e.g.,
application waiting indicator 564) for input in a dialog.
[0234] Communication process 10 may store 510 one or more
user-defined visual aspects (e.g., the above-described summary
window size, summary window position, summary window transparency
and summary windows content) of the summary window (e.g., summary
window 550) for use during subsequent sessions of summary window
550. Accordingly and once clinician 38 has configured summary
window 550 to their liking, these configurations may be saved so
that clinician 38 does to need to reconfigure summary window 550
the next time they use the system.
[0235] Continuing with the above-described example, assume that
clinician 38 is reviewing chest x-ray image 160 on monitor 150.
Accordingly, clinician 38 may position summary window 550 within
monitor 150 so that clinician 38 may view summary window 550
without needing to take their eyes off of chest x-ray image 160,
thus providing functionality similar to that of a head-up display
in a car, wherein the driver may view vital information (e.g.,
speed, navigation instructions, etc.) without needing to take their
eyes off of the road.
[0236] As shown in FIG. 3, medical report 40 is shown to include
five fields, namely patient name, patient address, lungs, heart,
and kidneys. Accordingly, plurality of fields indicator 558 within
summary window 550 may identify the fields included within medical
report 40. While medical report 40 is shown to include only five
fields, this is for illustrative purposes only and it is understood
that medical report 40 may include many additional fields.
Additionally, active field indicator 560 within summary window 550
may identify the field in which communication process 10 is
currently entering data. As discussed above, communication process
10 may enter the prose "Patient John Smith has a growth in the
lower quadrant of left lung that measures 5.1 centimeters".
Accordingly, active field indicator 560 may indicate the "lungs"
field (e.g., field 164) as the active field within medical report
40.
[0237] Further, audio input level indicator 556 within summary
window 550 may be a sweeping audio level indicator that generally
shows the volume/strength of the audio signal that clinician 38 is
providing to audio input device 42, thus allowing clinician 38 to
adjust the loudness of their voice and/or adjust the gain of audio
input device 42 if the volume/strength of the audio signal is too
strong or too weak.
[0238] As discussed above, communication process 10 may process 512
the medical information (e.g., data 20) and/or the observational
medical data (e.g., data 58) to determine if the medical
information (e.g., data 20) and/or the observational medical data
(e.g., data 58) includes one or more actionable items, which may
include associating 514 one or more best practices with one or more
actionable items. And when associating 514 the one or more best
practices with one or more actionable items, communication process
10 may use 516 artificial intelligence to process a plurality of
previously-generated medical report (e.g., medical report 40) to
associate one or more best practices with one or more actionable
items.
[0239] Assuming that communication process 10 associates the best
practice of contacting oncology when a patient has "a growth in the
lower quadrant of left lung that measures 5.1 centimeters", summary
window 550 may render the message "Call Oncology" within alert
indicator 562 of summary window 550.
[0240] Further and as discussed above, medical images in
combination with medical reports/records may be analyzed to
determine: what a typical brain bleed looks like; what a typical
aortic aneurysm looks like, and what a typical lung tumor looks
like. Accordingly, communication process 10 and/or medical imaging
platform 46 (e.g., PACS) may identify growth 162 by e.g., circling
growth 162. Accordingly and to direct the attention of clinician 38
to medical imaging platform 46 (e.g., PACS) and the circled growth
identified therein, communication process 10 may render the message
"PACS Requires Attention" within application waiting indicator
564.
General:
[0241] As will be appreciated by one skilled in the art, the
present disclosure may be embodied as a method, a system, or a
computer program product. Accordingly, the present disclosure may
take the form of an entirely hardware embodiment, an entirely
software embodiment (including firmware, resident software,
micro-code, etc.) or an embodiment combining software and hardware
aspects that may all generally be referred to herein as a
"circuit," "module" or "system." Furthermore, the present
disclosure may take the form of a computer program product on a
computer-usable storage medium having computer-usable program code
embodied in the medium.
[0242] Any suitable computer usable or computer readable medium may
be utilized. The computer-usable or computer-readable medium may
be, for example but not limited to, an electronic, magnetic,
optical, electromagnetic, infrared, or semiconductor system,
apparatus, device, or propagation medium. More specific examples (a
non-exhaustive list) of the computer-readable medium may include
the following: an electrical connection having one or more wires, a
portable computer diskette, a hard disk, a random access memory
(RAM), a read-only memory (ROM), an erasable programmable read-only
memory (EPROM or Flash memory), an optical fiber, a portable
compact disc read-only memory (CD-ROM), an optical storage device,
a transmission media such as those supporting the Internet or an
intranet, or a magnetic storage device. The computer-usable or
computer-readable medium may also be paper or another suitable
medium upon which the program is printed, as the program can be
electronically captured, via, for instance, optical scanning of the
paper or other medium, then compiled, interpreted, or otherwise
processed in a suitable manner, if necessary, and then stored in a
computer memory. In the context of this document, a computer-usable
or computer-readable medium may be any medium that can contain,
store, communicate, propagate, or transport the program for use by
or in connection with the instruction execution system, apparatus,
or device. The computer-usable medium may include a propagated data
signal with the computer-usable program code embodied therewith,
either in baseband or as part of a carrier wave. The computer
usable program code may be transmitted using any appropriate
medium, including but not limited to the Internet, wireline,
optical fiber cable, RF, etc.
[0243] Computer program code for carrying out operations of the
present disclosure may be written in an object oriented programming
language such as Java, Smalltalk, C++ or the like. However, the
computer program code for carrying out operations of the present
disclosure may also be written in conventional procedural
programming languages, such as the "C" programming language or
similar programming languages. The program code may execute
entirely on the user's computer, partly on the user's computer, as
a stand-alone software package, partly on the user's computer and
partly on a remote computer or entirely on the remote computer or
server. In the latter scenario, the remote computer may be
connected to the user's computer through a local area network/a
wide area network/the Internet (e.g., network 14).
[0244] The present disclosure is described with reference to
flowchart illustrations and/or block diagrams of methods, apparatus
(systems) and computer program products according to embodiments of
the disclosure. It will be understood that each block of the
flowchart illustrations and/or block diagrams, and combinations of
blocks in the flowchart illustrations and/or block diagrams, may be
implemented by computer program instructions. These computer
program instructions may be provided to a processor of a general
purpose computer/special purpose computer/other programmable data
processing apparatus, such that the instructions, which execute via
the processor of the computer or other programmable data processing
apparatus, create means for implementing the functions/acts
specified in the flowchart and/or block diagram block or
blocks.
[0245] These computer program instructions may also be stored in a
computer-readable memory that may direct a computer or other
programmable data processing apparatus to function in a particular
manner, such that the instructions stored in the computer-readable
memory produce an article of manufacture including instruction
means which implement the function/act specified in the flowchart
and/or block diagram block or blocks.
[0246] The computer program instructions may also be loaded onto a
computer or other programmable data processing apparatus to cause a
series of operational steps to be performed on the computer or
other programmable apparatus to produce a computer implemented
process such that the instructions which execute on the computer or
other programmable apparatus provide steps for implementing the
functions/acts specified in the flowchart and/or block diagram
block or blocks.
[0247] The flowcharts and block diagrams in the figures may
illustrate the architecture, functionality, and operation of
possible implementations of systems, methods and computer program
products according to various embodiments of the present
disclosure. In this regard, each block in the flowchart or block
diagrams may represent a module, segment, or portion of code, which
comprises one or more executable instructions for implementing the
specified logical function(s). It should also be noted that, in
some alternative implementations, the functions noted in the block
may occur out of the order noted in the figures. For example, two
blocks shown in succession may, in fact, be executed substantially
concurrently, or the blocks may sometimes be executed in the
reverse order, depending upon the functionality involved. It will
also be noted that each block of the block diagrams and/or
flowchart illustrations, and combinations of blocks in the block
diagrams and/or flowchart illustrations, may be implemented by
special purpose hardware-based systems that perform the specified
functions or acts, or combinations of special purpose hardware and
computer instructions.
[0248] The terminology used herein is for the purpose of describing
particular embodiments only and is not intended to be limiting of
the disclosure. As used herein, the singular forms "a", "an" and
"the" are intended to include the plural forms as well, unless the
context clearly indicates otherwise. It will be further understood
that the terms "comprises" and/or "comprising," when used in this
specification, specify the presence of stated features, integers,
steps, operations, elements, and/or components, but do not preclude
the presence or addition of one or more other features, integers,
steps, operations, elements, components, and/or groups thereof.
[0249] The corresponding structures, materials, acts, and
equivalents of all means or step plus function elements in the
claims below are intended to include any structure, material, or
act for performing the function in combination with other claimed
elements as specifically claimed. The description of the present
disclosure has been presented for purposes of illustration and
description, but is not intended to be exhaustive or limited to the
disclosure in the form disclosed. Many modifications and variations
will be apparent to those of ordinary skill in the art without
departing from the scope and spirit of the disclosure. The
embodiment was chosen and described in order to best explain the
principles of the disclosure and the practical application, and to
enable others of ordinary skill in the art to understand the
disclosure for various embodiments with various modifications as
are suited to the particular use contemplated.
[0250] A number of implementations have been described. Having thus
described the disclosure of the present application in detail and
by reference to embodiments thereof, it will be apparent that
modifications and variations are possible without departing from
the scope of the disclosure defined in the appended claims.
* * * * *