Patent ID: 12211626

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Ambient Cooperative Intelligence (In-Person Encounters)

System Overview

Referring toFIG.1, there is shown ambient cooperative intelligence process10. As will be discussed below in greater detail, ambient cooperative intelligence process10may be configured to automate the collection and processing of encounter information to generate/store/distribute reports.

Ambient cooperative intelligence process10may be implemented as a server-side process, a client-side process, or a hybrid server-side/client-side process. For example, ambient cooperative intelligence process10may be implemented as a purely server-side process via ambient cooperative intelligence process10s. Alternatively, ambient cooperative intelligence process10may be implemented as a purely client-side process via one or more of ambient cooperative intelligence process10c1, ambient cooperative intelligence process10c2, ambient cooperative intelligence process10c3, and ambient cooperative intelligence process10c4. Alternatively still, ambient cooperative intelligence process10may be implemented as a hybrid server-side/client-side process via ambient cooperative intelligence process10sin combination with one or more of ambient cooperative intelligence process10c1, ambient cooperative intelligence process10c2, ambient cooperative intelligence process10c3, and ambient cooperative intelligence process10c4.

Accordingly, ambient cooperative intelligence process10as used in this disclosure may include any combination of ambient cooperative intelligence process10s, ambient cooperative intelligence process10c1, ambient cooperative intelligence process10c2, ambient cooperative intelligence process10c3, and ambient cooperative intelligence process10c4.

Ambient cooperative intelligence process10smay be a server application and may reside on and may be executed by ambient cooperative intelligence (ACI) compute system12, which may be connected to network14(e.g., the Internet or a local area network). ACI compute system12may 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.

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 ACI compute system12may execute one or more operating systems, examples of which may include but are not limited to: Microsoft Windows Server™; Redhat Linux™, Unix, or a custom operating system, for example.

The instruction sets and subroutines of ambient cooperative intelligence process10s, which may be stored on storage device16coupled to ACI compute system12, may be executed by one or more processors (not shown) and one or more memory architectures (not shown) included within ACI compute system12. Examples of storage device16may 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.

Network14may be connected to one or more secondary networks (e.g., network18), examples of which may include but are not limited to: a local area network; a wide area network; or an intranet, for example.

Various IO requests (e.g., IO request20) may be sent from ambient cooperative intelligence process10s, ambient cooperative intelligence process10c1, ambient cooperative intelligence process10c2, ambient cooperative intelligence process10c3and/or ambient cooperative intelligence process10c4to ACI compute system12. Examples of IO request20may include but are not limited to data write requests (i.e., a request that content be written to ACI compute system12) and data read requests (i.e., a request that content be read from ACI compute system12).

The instruction sets and subroutines of ambient cooperative intelligence process10c1, ambient cooperative intelligence process10c2, ambient cooperative intelligence process10c3and/or ambient cooperative intelligence process10c4, which may be stored on storage devices20,22,24,26(respectively) coupled to ACI client electronic devices28,30,32,34(respectively), may be executed by one or more processors (not shown) and one or more memory architectures (not shown) incorporated into ACI client electronic devices28,30,32,34(respectively). Storage devices20,22,24,26may 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 ACI client electronic devices28,30,32,34may include, but are not limited to, personal computing device28(e.g., a smart phone, a personal digital assistant, a laptop computer, a notebook computer, and a desktop computer), audio input device30(e.g., a handheld microphone, a lapel microphone, an embedded microphone (such as those embedded within eyeglasses, smart phones, tablet computers and/or watches) and an audio recording device), display device32(e.g., a tablet computer, a computer monitor, and a smart television), machine vision input device34(e.g., an RGB imaging system, an infrared imaging system, an ultraviolet imaging system, a laser imaging system, a SONAR imaging system, a RADAR imaging system, and a thermal imaging system), a hybrid device (e.g., a single device that includes the functionality of one or more of the above-references devices; not shown), an audio rendering device (e.g., a speaker system, a headphone system, or an earbud system; not shown), various medical devices (e.g., medical imaging equipment, heart monitoring machines, body weight scales, body temperature thermometers, and blood pressure machines; not shown), and a dedicated network device (not shown).

Users36,38,40,42may access ACI compute system12directly through network14or through secondary network18. Further, ACI compute system12may be connected to network14through secondary network18, as illustrated with link line44.

The various ACI client electronic devices (e.g., ACI client electronic devices28,30,32,34) may be directly or indirectly coupled to network14(or network18). For example, personal computing device28is shown directly coupled to network14via a hardwired network connection. Further, machine vision input device34is shown directly coupled to network18via a hardwired network connection. Audio input device30is shown wirelessly coupled to network14via wireless communication channel46established between audio input device30and wireless access point (i.e., WAP)48, which is shown directly coupled to network14. WAP 48 may be, for example, an IEEE 802.11a, 802.11b, 802.11g, 802.11n, Wi-Fi, and/or Bluetooth device that is capable of establishing wireless communication channel46between audio input device30and WAP 48. Display device32is shown wirelessly coupled to network14via wireless communication channel50established between display device32and WAP 52, which is shown directly coupled to network14.

The various ACI client electronic devices (e.g., ACI client electronic devices28,30,32,34) may each execute an operating system, examples of which may include but are not limited to Microsoft Windows™, Apple Macintosh™, Redhat Linux™, or a custom operating system, wherein the combination of the various ACI client electronic devices (e.g., ACI client electronic devices28,30,32,34) and ACI compute system12may form ACI system54, an example of which is the Dragon Ambient eXperience (DAX) system offered by Nuance of Burlington, MA

The Ambient Cooperative Intelligence System

While ambient cooperative intelligence process10will be described below as being utilized to automate the collection and processing of clinical encounter information to generate/store/distribute medical records, 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.

Referring also toFIG.2, there is shown a simplified exemplary embodiment of ACI system54that is configured to automate cooperative intelligence. ACI system54may include: machine vision system100configured to obtain machine vision encounter information102concerning a patient encounter; audio recording system104configured to obtain audio encounter information106concerning the patient encounter; and a compute system (e.g., ACI compute system12) configured to receive machine vision encounter information102and audio encounter information106from machine vision system100and audio recording system104(respectively). ACI system54may also include: display rendering system108configured to render visual information110; and audio rendering system112configured to render audio information114, wherein ACI compute system12may be configured to provide visual information110and audio information114to display rendering system108and audio rendering system112(respectively).

Example of machine vision system100may include but are not limited to: one or more ACI client electronic devices (e.g., ACI client electronic device34, examples of which may include but are not limited to an RGB imaging system, an infrared imaging system, an ultraviolet imaging system, a laser imaging system, a SONAR imaging system, a RADAR imaging system, and a thermal imaging system). Examples of audio recording system104may include but are not limited to: one or more ACI client electronic devices (e.g., ACI client electronic device30, examples of which may include but are not limited to a handheld microphone (e.g., one example of a body worn microphone), a lapel microphone (e.g., another example of a body worn microphone), an embedded microphone, such as those embedded within eyeglasses, smart phones, tablet computers and/or watches (e.g., another example of a body worn microphone), and an audio recording device). Examples of display rendering system108may include but are not limited to: one or more ACI client electronic devices (e.g., ACI client electronic device32, examples of which may include but are not limited to a tablet computer, a computer monitor, and a smart television). Examples of audio rendering system112may include but are not limited to: one or more ACI client electronic devices (e.g., audio rendering device116, examples of which may include but are not limited to a speaker system, a headphone system, and an earbud system).

ACI compute system12may be configured to access one or more datasources118(e.g., plurality of individual datasources120,122,124,126,128), examples of which may include but are not limited to one or more of an electronic health record (EHR) datasource, a user profile datasource, a voice print datasource, a voice characteristics datasource (e.g., for adapting the ambient speech recognition models), a face print datasource, a humanoid shape datasource, an utterance identifier datasource, a wearable token identifier datasource, an interaction identifier datasource, a medical conditions symptoms datasource, a prescriptions compatibility datasource, a medical insurance coverage datasource, a physical events datasource, and a home healthcare datasource. While in this particular example, five different examples of datasources118are shown, 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.

As will be discussed below in greater detail, ACI system54may be configured to monitor a monitored space (e.g., monitored space130) in a clinical environment, wherein examples of this clinical environment may include but are not limited to: a doctor's office, a medical facility, a medical practice, a medical lab, an urgent care facility, a medical clinic, an emergency room, an operating room, a hospital, a long term care facility, a rehabilitation facility, a nursing home, and a hospice facility. Accordingly, an example of the above-referenced patient encounter may include but is not limited to a patient visiting one or more of the above-described clinical environments (e.g., a doctor's office, a medical facility, a medical practice, a medical lab, an urgent care facility, a medical clinic, an emergency room, an operating room, a hospital, a long-term care facility, a rehabilitation facility, a nursing home, and a hospice facility).

Machine vision system100may include a plurality of discrete machine vision systems when the above-described clinical environment is larger or a higher level of resolution is desired. As discussed above, examples of machine vision system100may include but are not limited to: one or more ACI client electronic devices (e.g., ACI client electronic device34, examples of which may include but are not limited to an RGB imaging system, an infrared imaging system, an ultraviolet imaging system, a laser imaging system, a SONAR imaging system, a RADAR imaging system, and a thermal imaging system). Accordingly, machine vision system100may include one or more of each of an RGB imaging system, an infrared imaging system, an ultraviolet imaging system, a laser imaging system, a SONAR imaging system, a RADAR imaging system, and a thermal imaging system.

Audio recording system104may include a plurality of discrete audio recording systems when the above-described clinical environment is larger or a higher level of resolution is desired. As discussed above, examples of audio recording system104may include but are not limited to: one or more ACI client electronic devices (e.g., ACI client electronic device30, examples of which may include but are not limited to a handheld microphone, a lapel microphone, an embedded microphone (such as those embedded within eyeglasses, smart phones, tablet computers and/or watches) and an audio recording device). Accordingly, audio recording system104may include one or more of each of a handheld microphone, a lapel microphone, an embedded microphone (such as those embedded within eyeglasses, smart phones, tablet computers and/or watches) and an audio recording device.

Display rendering system108may include a plurality of discrete display rendering systems when the above-described clinical environment is larger or a higher level of resolution is desired. As discussed above, examples of display rendering system108may include but are not limited to: one or more ACI client electronic devices (e.g., ACI client electronic device32, examples of which may include but are not limited to a tablet computer, a computer monitor, and a smart television). Accordingly, display rendering system108may include one or more of each of a tablet computer, a computer monitor, and a smart television.

Audio rendering system112may include a plurality of discrete audio rendering systems when the above-described clinical environment is larger or a higher level of resolution is desired. As discussed above, examples of audio rendering system112may include but are not limited to: one or more ACI client electronic devices (e.g., audio rendering device116, examples of which may include but are not limited to a speaker system, a headphone system, or an earbud system). Accordingly, audio rendering system112may include one or more of each of a speaker system, a headphone system, or an earbud system.

ACI compute system12may include a plurality of discrete compute systems. As discussed above, ACI compute system12may 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. Accordingly, ACI compute system12may include one or more of each of 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.

Microphone Array

Referring also toFIG.3, audio recording system104may include microphone array200having a plurality of discrete microphone assemblies. For example, audio recording system104may include a plurality of discrete audio acquisition devices (e.g., audio acquisition devices202,204,206,208,210,212,214,216,218) that may form microphone array200. As will be discussed below in greater detail, ACI system54may be configured to form one or more audio recording beams (e.g., audio recording beams220,222,224) via the discrete audio acquisition devices (e.g., audio acquisition devices202,204,206,208,210,212,214,216,218) included within audio recording system104.

For example, ACI system54may be further configured to steer the one or more audio recording beams (e.g., audio recording beams220,222,224) toward one or more encounter participants (e.g., encounter participants226,228,230) of the above-described patient encounter. Examples of the encounter participants (e.g., encounter participants226,228,230) may include but are not limited to: medical professionals (e.g., doctors, nurses, physician's assistants, lab technicians, physical therapists, scribes (e.g., a quality documentation specialist that performs editing and quality assurance operations) and/or staff members involved in the patient encounter), patients (e.g., people that are visiting the above-described clinical environments for the patient encounter), and third parties (e.g., friends of the patient, relatives of the patient and/or acquaintances of the patient that are involved in the patient encounter).

Accordingly, ACI system54and/or audio recording system104may be configured to utilize one or more of the discrete audio acquisition devices (e.g., audio acquisition devices202,204,206,208,210,212,214,216,218) to form an audio recording beam. For example, ACI system54and/or audio recording system104may be configured to utilize various audio acquisition devices to form audio recording beam220, thus enabling the capturing of audio (e.g., speech) produced by encounter participant226(as audio recording beam220is pointed to (i.e., directed toward) encounter participant226). Additionally, ACI system54and/or audio recording system104may be configured to utilize various audio acquisition devices to form audio recording beam222, thus enabling the capturing of audio (e.g., speech) produced by encounter participant228(as audio recording beam222is pointed to (i.e., directed toward) encounter participant228). Additionally, ACI system54and/or audio recording system104may be configured to utilize various audio acquisition devices to form audio recording beam224, thus enabling the capturing of audio (e.g., speech) produced by encounter participant230(as audio recording beam224is pointed to (i.e., directed toward) encounter participant230).

Further, ACI system54and/or audio recording system104may be configured to utilize null-steering precoding to cancel interference between speakers and/or noise. As is known in the art, null-steering precoding is a method of spatial signal processing by which a multiple antenna transmitter may null multiuser interference signals in wireless communications, wherein null-steering precoding may mitigate the impact off background noise and unknown user interference. In particular, null-steering precoding may be a method of beamforming for narrowband signals that may compensate for delays of receiving signals from a specific source at different elements of an antenna array. In general and to improve performance of the antenna array, incoming signals may be summed and averaged, wherein certain signals may be weighted and compensation may be made for signal delays.

Machine vision system100and audio recording system104may be stand-alone devices (as shown inFIG.2). Additionally/alternatively, machine vision system100and audio recording system104may be combined into one package to form mixed-media ACI device232. For example, mixed-media ACI device232may be configured to be mounted to a structure (e.g., a wall, a ceiling, a beam, a column) within the above-described clinical environments (e.g., a doctor's office, a medical facility, a medical practice, a medical lab, an urgent care facility, a medical clinic, an emergency room, an operating room, a hospital, a long term care facility, a rehabilitation facility, a nursing home, and a hospice facility), thus allowing for easy installation of the same. Further, ACI system54may be configured to include a plurality of mixed-media ACI devices (e.g., mixed-media ACI device232) when the above-described clinical environment is larger or a higher level of resolution is desired.

ACI system54may be further configured to steer the one or more audio recording beams (e.g., audio recording beams220,222,224) toward one or more encounter participants (e.g., encounter participants226,228,230) of the patient encounter based, at least in part, upon machine vision encounter information102. As discussed above, mixed-media ACI device232(and machine vision system100/audio recording system104included therein) may be configured to monitor one or more encounter participants (e.g., encounter participants226,228,230) of a patient encounter.

Specifically and as will be discussed below in greater detail, machine vision system100(either as a stand-alone system or as a component of mixed-media ACI device232) may be configured to detect humanoid shapes within the above-described clinical environments (e.g., a doctor's office, a medical facility, a medical practice, a medical lab, an urgent care facility, a medical clinic, an emergency room, an operating room, a hospital, a long term care facility, a rehabilitation facility, a nursing home, and a hospice facility). And when these humanoid shapes are detected by machine vision system100, ACI system54and/or audio recording system104may be configured to utilize one or more of the discrete audio acquisition devices (e.g., audio acquisition devices202,204,206,208,210,212,214,216,218) to form an audio recording beam (e.g., audio recording beams220,222,224) that is directed toward each of the detected humanoid shapes (e.g., encounter participants226,228,230).

As discussed above, ACI compute system12may be configured to receive machine vision encounter information102and audio encounter information106from machine vision system100and audio recording system104(respectively); and may be configured to provide visual information110and audio information114to display rendering system108and audio rendering system112(respectively). Depending upon the manner in which ACI system54(and/or mixed-media ACI device232) is configured, ACI compute system12may be included within mixed-media ACI device232or external to mixed-media ACI device232.

The Ambient Cooperative Intelligence Process

As discussed above, ACI compute system12may execute all or a portion of ambient cooperative intelligence process10, wherein the instruction sets and subroutines of ambient cooperative intelligence process10(which may be stored on one or more of e.g., storage devices16,20,22,24,26) may be executed by ACI compute system12and/or one or more of ACI client electronic devices28,30,32,34.

As discussed above, ambient cooperative intelligence process10may be configured to automate the collection and processing of clinical encounter information to generate/store/distribute medical records. Accordingly and referring also toFIG.4, ambient cooperative intelligence process10may be configured to obtain300encounter information (e.g., machine vision encounter information102and/or audio encounter information106) of a patient encounter (e.g., a visit to a doctor's office). Ambient cooperative intelligence process10may further be configured to process302the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) to generate an encounter transcript (e.g., encounter transcript234), wherein ambient cooperative intelligence process10may then process304at least a portion of the encounter transcript (e.g., encounter transcript234) to populate at least a portion of a medical record (e.g., medical record236) associated with the patient encounter (e.g., the visit to the doctor's office). Encounter transcript234and/or medical record236may be reviewed by a medical professional involved with the patient encounter (e.g., a visit to a doctor's office) to determine the accuracy of the same and/or make corrections to the same.

For example, a scribe (i.e., a quality documentation specialist that performs editing and quality assurance operations) involved with (or assigned to) the patient encounter (e.g., a visit to a doctor's office) may review encounter transcript234, a draft of a medical report, and/or medical record236to confirm that the same was accurate and/or make corrections to the same. In the event that corrections are made to encounter transcript234and/or medical record236, ambient cooperative intelligence process10may utilize these corrections for training/tuning purposes (e.g., to adjust the various profiles associated the participants of the patient encounter) to enhance the future accuracy/efficiency/performance of ambient cooperative intelligence process10.

Alternatively/additionally, a doctor involved with the patient encounter (e.g., a visit to a doctor's office) may review encounter transcript234and/or medical record236to confirm that the same was accurate and/or make corrections to the same. In the event that corrections are made to encounter transcript234and/or medical record236, ambient cooperative intelligence process10may utilize these corrections for training/tuning purposes (e.g., to adjust the various profiles associated the participants of the patient encounter) to enhance the future accuracy/efficiency/performance of ambient cooperative intelligence process10.

For example, assume that a patient (e.g., encounter participant228) visits a clinical environment (e.g., a doctor's office) because they do not feel well. They have a headache, fever, chills, a cough, and some difficulty breathing. In this particular example, a monitored space (e.g., monitored space130) within the clinical environment (e.g., the doctor's office) may be outfitted with machine vision system100configured to obtain machine vision encounter information102concerning the patient encounter (e.g., encounter participant228visiting the doctor's office) and audio recording system104configured to obtain audio encounter information106concerning the patient encounter (e.g., encounter participant228visiting the doctor's office) via one or more audio sensors (e.g., audio acquisition devices202,204,206,208,210,212,214,216,218).

As discussed above, machine vision system100may include a plurality of discrete machine vision systems if the monitored space (e.g., monitored space130) within the clinical environment (e.g., the doctor's office) is larger or a higher level of resolution is desired, wherein examples of machine vision system100may include but are not limited to: an RGB imaging system, an infrared imaging system, an ultraviolet imaging system, a laser imaging system, a SONAR imaging system, a RADAR imaging system, and a thermal imaging system. Accordingly and in certain instances/embodiments, machine vision system100may include one or more of each of an RGB imaging system, an infrared imaging system, an ultraviolet imaging system, a laser imaging system, a SONAR imaging system, a RADAR imaging system, and a thermal imaging system positioned throughout monitored space130, wherein each of these systems may be configured to provide data (e.g., machine vision encounter information102) to ACI compute system12and/or ACI system54.

As also discussed above, audio recording system104may include a plurality of discrete audio recording systems if the monitored space (e.g., monitored space130) within the clinical environment (e.g., the doctor's office) is larger or a higher level of resolution is desired, wherein examples of audio recording system104may include but are not limited to: a handheld microphone, a lapel microphone, an embedded microphone (such as those embedded within eyeglasses, smart phones, tablet computers and/or watches) and an audio recording device. Accordingly and in certain instances/embodiments, audio recording system104may include one or more of each of a handheld microphone, a lapel microphone, an embedded microphone (such as those embedded within eyeglasses, smart phones, tablet computers and/or watches) and an audio recording device positioned throughout monitored space130, wherein each of these microphones/devices may be configured to provide data (e.g., audio encounter information106) to ACI compute system12and/or ACI system54.

Since machine vision system100and audio recording system104may be positioned throughout monitored space130, all of the interactions between medical professionals (e.g., encounter participant226), patients (e.g., encounter participant228) and third parties (e.g., encounter participant230) that occur during the patient encounter (e.g., encounter participant228visiting the doctor's office) within the monitored space (e.g., monitored space130) of the clinical environment (e.g., the doctor's office) may be monitored/recorded/processed. Accordingly, a patient “check-in” area within monitored space130may be monitored to obtain encounter information (e.g., machine vision encounter information102and/or audio encounter information106) during this pre-visit portion of the patient encounter (e.g., encounter participant228visiting the doctor's office). Further, various rooms within monitored space130may be monitored to obtain encounter information (e.g., machine vision encounter information102and/or audio encounter information106) during these various portions of the patient encounter (e.g., while meeting with the doctor, while vital signs and statistics are obtained, and while imaging is performed). Further, a patient “check-out” area within monitored space130may be monitored to obtain encounter information (e.g., machine vision encounter information102and/or audio encounter information106) during this post-visit portion of the patient encounter (e.g., encounter participant228visiting the doctor's office). Additionally and via machine vision encounter information102, visual speech recognition (via visual lip-reading functionality) may be utilized by ambient cooperative intelligence process10to further effectuate the gathering of audio encounter information106.

Accordingly and when obtaining300encounter information (e.g., machine vision encounter information102and/or audio encounter information106), ambient cooperative intelligence process10may: obtain306encounter information (e.g., machine vision encounter information102and/or audio encounter information106) from a medical professional (e.g., encounter participant226); obtain308encounter information (e.g., machine vision encounter information102and/or audio encounter information106) from a patient (e.g., encounter participant228); and/or obtain310encounter information (e.g., machine vision encounter information102and/or audio encounter information106) from a third party (e.g., encounter participant230). Further and when obtaining300encounter information (e.g., machine vision encounter information102and/or audio encounter information106), ambient cooperative intelligence process10may obtain300the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) from previous (related or unrelated) patient encounters. For example, if the current patient encounter is actually the third visit that the patient is making concerning e.g., shortness of breath, the encounter information from the previous two visits (i.e., the previous two patient encounters) may be highly-related and may be obtained300by ambient cooperative intelligence process10.

When ambient cooperative intelligence process10obtains300the encounter information, ambient cooperative intelligence process10may utilize312a medical virtual assistant (e.g., medical virtual assistant238) to prompt the patient (e.g., encounter participant228) to provide at least a portion of the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) during a pre-visit portion (e.g., a patient intake portion) of the patient encounter (e.g., encounter participant228visiting the doctor's office). Generally speaking, a pre-visit portion (e.g., a patient intake portion) of the patient encounter (e.g., encounter participant228visiting the doctor's office) is the portion of the patient encounter that occurs before the consultation portion (i.e., the portion of the patient encounter in which the patient (e.g., encounter participant228) meets with the medical professional (e.g., encounter participant226).

Further and when ambient cooperative intelligence process10obtains300encounter information, ambient cooperative intelligence process10may utilize314a medical virtual assistant (e.g., medical virtual assistant238) to prompt the patient (e.g., encounter participant228) to provide at least a portion of the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) during a post-visit portion (e.g., a patient follow-up portion) of the patient encounter (e.g., encounter participant228visiting the doctor's office). Generally speaking, a post-visit portion (e.g., a patient follow-up portion) of the patient encounter (e.g., encounter participant228visiting the doctor's office) is the portion of the patient encounter that occurs after the consultation portion (i.e., the portion of the patient encounter in which the patient (e.g., encounter participant228) meets with the medical professional (e.g., encounter participant226).

Automated Transcript Generation

Ambient cooperative intelligence process10may be configured to process the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) to generate encounter transcript234that may be automatically formatted and punctuated.

Accordingly and referring also toFIG.5, ambient cooperative intelligence process10may be configured to obtain300encounter information (e.g., machine vision encounter information102and/or audio encounter information106) of a patient encounter (e.g., a visit to a doctor's office).

Ambient cooperative intelligence process10may process350the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) to: associate a first portion of the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) with a first encounter participant, and associate at least a second portion of the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) with at least a second encounter participant.

As discussed above, ACI system54may be configured to form one or more audio recording beams (e.g., audio recording beams220,222,224) via the discrete audio acquisition devices (e.g., discrete audio acquisition devices202,204,206,208,210,212,214,216,218) included within audio recording system104, wherein ACI system54may be further configured to steer the one or more audio recording beams (e.g., audio recording beams220,222,224) toward one or more encounter participants (e.g., encounter participants226,228,230) of the above-described patient encounter.

Accordingly and continuing with the above-stated example, ACI system54may steer audio recording beam220toward encounter participant226, may steer audio recording beam222toward encounter participant228, and may steer audio recording beam224toward encounter participant230. Accordingly and due to the directionality of audio recording beams220,222,224, audio encounter information106may include three components, namely audio encounter information106A (which is obtained via audio recording beam220), audio encounter information106B (which is obtained via audio recording beam222) and audio encounter information106C (which is obtained via audio recording beam220).

Further and as discussed above, ACI compute system12may be configured to access one or more datasources118(e.g., plurality of individual datasources120,122,124,126,128), examples of which may include but are not limited to one or more of a user profile datasource, a voice print datasource, a voice characteristics datasource (e.g., for adapting the automated speech recognition models), a face print datasource, a humanoid shape datasource, an utterance identifier datasource, a wearable token identifier datasource, an interaction identifier datasource, a medical conditions symptoms datasource, a prescriptions compatibility datasource, a medical insurance coverage datasource, a physical events datasource, and a home healthcare datasource.

Accordingly, ambient cooperative intelligence process10may process350the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) to: associate a first portion (e.g., encounter information106A) of the encounter information (e.g., audio encounter information106) with a first encounter participant (e.g., encounter participant226), and associate at least a second portion (e.g., encounter information106B,106C) of the encounter information (e.g., audio encounter information106) with at least a second encounter participant (e.g., encounter participants228,230; respectively).

Further and when processing350the encounter information (e.g., audio encounter information106A,106B,106C), ambient cooperative intelligence process10may compare each of audio encounter information106A,106B,106C to the voice prints defined within the above-referenced voice print datasource so that the identity of encounter participants226,228,230(respectively) may be determined. Accordingly, if the voice print datasource includes a voice print that corresponds to one or more of the voice of encounter participant226(as heard within audio encounter information106A), the voice of encounter participant228(as heard within audio encounter information106B) or the voice of encounter participant230(as heard within audio encounter information106C), the identity of one or more of encounter participants226,228,230may be defined. And in the event that a voice heard within one or more of audio encounter information106A, audio encounter information106B or audio encounter information106C is unidentifiable, that one or more particular encounter participant may be defined as “Unknown Participant”.

Once the voices of encounter participants226,228,230are processed350, ambient cooperative intelligence process10may generate302an encounter transcript (e.g., encounter transcript234) based, at least in part, upon the first portion of the encounter information (e.g., audio encounter information106A) and the at least a second portion of the encounter information (e.g., audio encounter information106B.106C).

Automated Role Assignment

Ambient cooperative intelligence process10may be configured to automatically define roles for the encounter participants (e.g., encounter participants226,228,230) in the patient encounter (e.g., a visit to a doctor's office).

Accordingly and referring also toFIG.6, ambient cooperative intelligence process10may be configured to obtain300encounter information (e.g., machine vision encounter information102and/or audio encounter information106) of a patient encounter (e.g., a visit to a doctor's office).

Ambient cooperative intelligence process10may then process400the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) to associate a first portion of the encounter information with a first encounter participant (e.g., encounter participant226) and assign402a first role to the first encounter participant (e.g., encounter participant226).

When processing400the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) to associate the first portion of the encounter information with the first encounter participant (e.g., encounter participant226), ambient cooperative intelligence process10may process404the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) to associate a first portion of the audio encounter information (e.g., audio encounter information106A) with the first encounter participant (e.g., encounter participant226).

Specifically and when processing404the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) to associate the first portion of the audio encounter information (e.g., audio encounter information106A) with the first encounter participant (e.g., encounter participant226), ambient cooperative intelligence process10may compare406one or more voice prints (defined within voice print datasource) to one or more voices defined within the first portion of the audio encounter information (e.g., audio encounter information106A); and may compare408one or more utterance identifiers (defined within utterance datasource) to one or more utterances defined within the first portion of the audio encounter information (e.g., audio encounter information106A); wherein comparisons406,408may allow ambient cooperative intelligence process10to assign402a first role to the first encounter participant (e.g., encounter participant226). For example, if the identity of encounter participant226can be defined via voice prints, a role for encounter participant226may be assigned402if that identity defined is associated with a role (e.g., the identity defined for encounter participant226is Doctor Susan Jones). Further, if an utterance made by encounter participant226is “I am Doctor Susan Jones”, this utterance may allow a role for encounter participant226to be assigned402.

When processing400the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) to associate the first portion of the encounter information with the first encounter participant (e.g., encounter participant226), ambient cooperative intelligence process10may process410the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) to associate a first portion of the machine vision encounter information (e.g., machine vision encounter information102A) with the first encounter participant (e.g., encounter participant226).

Specifically and when processing410the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) to associate the first portion of the machine vision encounter information (e.g., machine vision encounter information102A) with the first encounter participant (e.g., encounter participant226), ambient cooperative intelligence process10may compare412one or more face prints (defined within face print datasource) to one or more faces defined within the first portion of the machine vision encounter information (e.g., machine vision encounter information102A); compare414one or more wearable token identifiers (defined within wearable token identifier datasource) to one or more wearable tokens defined within the first portion of the machine vision encounter information (e.g., machine vision encounter information102A); and compare416one or more interaction identifiers (defined within interaction identifier datasource) to one or more humanoid interactions defined within the first portion of the machine vision encounter information (e.g., machine vision encounter information102A); wherein comparisons412,414,416may allow ambient cooperative intelligence process10to assign402a first role to the first encounter participant (e.g., encounter participant226). For example, if the identity of encounter participant226can be defined via face prints, a role for encounter participant226may be assigned402if that identity defined is associated with a role (e.g., the identity defined for encounter participant226is Doctor Susan Jones). Further, if a wearable token worn by encounter participant226can be identified as a wearable token assigned to Doctor Susan Jones, a role for encounter participant226may be assigned402. Additionally, if an interaction made by encounter participant226corresponds to the type of interaction that is made by a doctor, the existence of this interaction may allow a role for encounter participant226to be assigned402.

Examples of such wearable tokens may include but are not limited to wearable devices that may be worn by the medical professionals when they are within monitored space130(or after they leave monitored space130). For example, these wearable tokens may be worn by medical professionals when e.g., they are moving between monitored rooms within monitored space130, travelling to and/or from monitored space130, and/or outside of monitored space130(e.g., at home).

Additionally, ambient cooperative intelligence process10may process418the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) to associate at least a second portion of the encounter information with at least a second encounter participant; and may assign420at least a second role to the at least a second encounter participant.

Specifically, ambient cooperative intelligence process10may process418the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) to associate at least a second portion of the encounter information with at least a second encounter participant. For example, ambient cooperative intelligence process10may process418the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) to associate audio encounter information106B and machine vision encounter information102B with encounter participant228and may associate audio encounter information106C and machine vision encounter information102C with encounter participant230.

Further, ambient cooperative intelligence process10may assign420at least a second role to the at least a second encounter participant. For example, ambient cooperative intelligence process10may assign420a role to encounter participants228,230.

Automated Movement Tracking

Ambient cooperative intelligence process10may be configured to track the movement and/or interaction of humanoid shapes within the monitored space (e.g., monitored space130) during the patient encounter (e.g., a visit to a doctor's office) so that e.g., the ambient cooperative intelligence process10knows when encounter participants (e.g., one or more of encounter participants226,228,230) enter, exit r cross paths within monitored space130.

Accordingly and referring also toFIG.7, ambient cooperative intelligence process10may process450the machine vision encounter information (e.g., machine vision encounter information102) to identify one or more humanoid shapes. As discussed above, examples of machine vision system100generally (and ACI client electronic device34specifically) may include but are not limited to one or more of an RGB imaging system, an infrared imaging system, an ultraviolet imaging system, a laser imaging system, a SONAR imaging system, a RADAR imaging system, and a thermal imaging system).

When ACI client electronic device34includes a visible light imaging system (e.g., an RGB imaging system), ACI client electronic device34may be configured to monitor various objects within monitored space130by recording motion video in the visible light spectrum of these various objects. When ACI client electronic device34includes an invisible light imaging system (e.g., a laser imaging system, an infrared imaging system and/or an ultraviolet imaging system), ACI client electronic device34may be configured to monitor various objects within monitored space130by recording motion video in the invisible light spectrum of these various objects. When ACI client electronic device34includes an X-ray imaging system, ACI client electronic device34may be configured to monitor various objects within monitored space130by recording energy in the X-ray spectrum of these various objects. When ACI client electronic device34includes a SONAR imaging system, ACI client electronic device34may be configured to monitor various objects within monitored space130by transmitting soundwaves that may be reflected off of these various objects. When ACI client electronic device34includes a RADAR imaging system, ACI client electronic device34may be configured to monitor various objects within monitored space130by transmitting radio waves that may be reflected off of these various objects. When ACI client electronic device34includes a thermal imaging system, ACI client electronic device34may be configured to monitor various objects within monitored space130by tracking the thermal energy of these various objects.

As discussed above, ACI compute system12may be configured to access one or more datasources118(e.g., plurality of individual datasources120,122,124,126,128), wherein examples of which may include but are not limited to one or more of a user profile datasource, a voice print datasource, a voice characteristics datasource (e.g., for adapting the automated speech recognition models), a face print datasource, a humanoid shape datasource, an utterance identifier datasource, a wearable token identifier datasource, an interaction identifier datasource, a medical conditions symptoms datasource, a prescriptions compatibility datasource, a medical insurance coverage datasource, a physical events datasource, and a home healthcare datasource.

Accordingly and when processing450the machine vision encounter information (e.g., machine vision encounter information102) to identify one or more humanoid shapes, ambient cooperative intelligence process10may be configured to compare the humanoid shapes defined within one or more datasources118to potential humanoid shapes within the machine vision encounter information (e.g., machine vision encounter information102).

When processing450the machine vision encounter information (e.g., machine vision encounter information102) to identify one or more humanoid shapes, ambient cooperative intelligence process10may track452the movement of the one or more humanoid shapes within the monitored space (e.g., monitored space130). For example and when tracking452the movement of the one or more humanoid shapes within monitored space130, ambient cooperative intelligence process10may add454a new humanoid shape to the one or more humanoid shapes when the new humanoid shape enters the monitored space (e.g., monitored space130) and/or may remove456an existing humanoid shape from the one or more humanoid shapes when the existing humanoid shape leaves the monitored space (e.g., monitored space130).

For example, assume that a lab technician (e.g., encounter participant242) temporarily enters monitored space130to chat with encounter participant230. Accordingly, ambient cooperative intelligence process10may add454encounter participant242to the one or more humanoid shapes being tracked452when the new humanoid shape (i.e., encounter participant242) enters monitored space130. Further, assume that the lab technician (e.g., encounter participant242) leaves monitored space130after chatting with encounter participant230. Therefore, ambient cooperative intelligence process10may remove456encounter participant242from the one or more humanoid shapes being tracked452when the humanoid shape (i.e., encounter participant242) leaves monitored space130.

Also and when tracking452the movement of the one or more humanoid shapes within monitored space130, ambient cooperative intelligence process10may monitor the trajectories of the various humanoid shapes within monitored space130. Accordingly, assume that when leaving monitored space130, encounter participant242walks in front of (or behind) encounter participant226. As ambient cooperative intelligence process10is monitoring the trajectories of (in this example) encounter participant242(who is e.g., moving from left to right) and encounter participant226(who is e.g., stationary), when encounter participant242passes in front of (or behind) encounter participant226, the identities of these two humanoid shapes may not be confused by ambient cooperative intelligence process10.

Ambient cooperative intelligence process10may be configured to obtain300the encounter information of the patient encounter (e.g., a visit to a doctor's office), which may include machine vision encounter information102(in the manner described above) and/or audio encounter information106.

Ambient cooperative intelligence process10may steer458one or more audio recording beams (e.g., audio recording beams220,222,224) toward the one or more humanoid shapes (e.g., encounter participants226,228,230) to capture audio encounter information (e.g., audio encounter information106), wherein audio encounter information106may be included within the encounter information (e.g., machine vision encounter information102and/or audio encounter information106).

Specifically and as discussed above, ambient cooperative intelligence process10(via ACI system54and/or audio recording system104) may utilize one or more of the discrete audio acquisition devices (e.g., audio acquisition devices202,204,206,208,210,212,214,216,218) to form an audio recording beam. For example, ACI system54and/or audio recording system104may be configured to utilize various audio acquisition devices to form audio recording beam220, thus enabling the capturing of audio (e.g., speech) produced by encounter participant226(as audio recording beam220is pointed to (i.e., directed toward) encounter participant226). Additionally, ACI system54and/or audio recording system104may be configured to utilize various audio acquisition devices to form audio recording beam222, thus enabling the capturing of audio (e.g., speech) produced by encounter participant228(as audio recording beam222is pointed to (i.e., directed toward) encounter participant228). Additionally, ACI system54and/or audio recording system104may be configured to utilize various audio acquisition devices to form audio recording beam224, thus enabling the capturing of audio (e.g., speech) produced by encounter participant230(as audio recording beam224is pointed to (i.e., directed toward) encounter participant230).

Once obtained, ambient cooperative intelligence process10may process302the encounter information (e.g., machine vision encounter information102and/or audio encounter information106) to generate encounter transcript234and may process304at least a portion of encounter transcript234to populate at least a portion of a medical record (e.g., medical record236) associated with the patient encounter (e.g., a visit to a doctor's office).

Telehealth (Remote Encounters)

System Overview

Regular access to medical professionals is of paramount importance for people maintaining their health. Accordingly, it has been shown that annual physicals are instrumental to maintaining a patient's health. Further and in the event of an illness, it is important that a medical professional is engaged in a timely fashion. Unfortunately, such medical professionals are often not timely engaged. For example, it is often difficult for people to travel to see a doctor. Further and especially when a specialist is needed, a significant amount of travel may be required in order to visit with such a medical professional. Accordingly, telehealth visits may solve some of these issues by allowing a patient to visit with a doctor without having to actually travel to the doctor's office.

Referring toFIG.8, there is shown telehealth process510. As will be discussed below in greater detail, telehealth process510may be configured to effectuate a telehealth visit between a medical professional and a patient.

Telehealth process510may be implemented as a server-side process, a client-side process, or a hybrid server-side/client-side process. For example, telehealth process510may be implemented as a purely server-side process via telehealth process510s. Alternatively, telehealth process510may be implemented as a purely client-side process via one or more of telehealth process510c1, telehealth process510c2, telehealth process510c3, and telehealth process510c4. Alternatively still, telehealth process510may be implemented as a hybrid server-side/client-side process via telehealth process510sin combination with one or more of telehealth process510c1, telehealth process510c2, telehealth process510c3, and telehealth process510c4.

Accordingly, telehealth process510as used in this disclosure may include any combination of telehealth process510s, telehealth process510c1, telehealth process510c2, telehealth process510c3, and telehealth process510c4.

Telehealth process510smay be a server application and may reside on and may be executed by telehealth system512, which may be connected to network514(e.g., the Internet or a local area network). Telehealth system512may 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, one or more software applications, one or more software platforms, a cloud-based computational system, and a cloud-based storage platform.

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 telehealth system512may execute one or more operating systems, examples of which may include but are not limited to: Microsoft Windows Server™, Redhat Linux™, Unix, or a custom operating system, for example.

The instruction sets and subroutines of telehealth process510s, which may be stored on storage device516coupled to telehealth system512, may be executed by one or more processors (not shown) and one or more memory architectures (not shown) included within telehealth system512. Examples of storage device516may 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.

Network514may be connected to one or more secondary networks (e.g., network518), examples of which may include but are not limited to: a local area network; a wide area network; or an intranet, for example.

Various IO requests (e.g., IO request520) may be sent from telehealth process510s, telehealth process510c1, telehealth process510c2, telehealth process510c3and/or telehealth process510c4to telehealth system512. Examples of IO request520may include but are not limited to data write requests (i.e., a request that content be written to data acquisition system512) and data read requests (i.e., a request that content be read from data acquisition system512).

The instruction sets and subroutines of telehealth process510c1, telehealth process510c2, telehealth process510c3and/or telehealth process510c4, which may be stored on storage devices520,522,524,526(respectively) coupled to client electronic devices528,530,532,534(respectively), may be executed by one or more processors (not shown) and one or more memory architectures (not shown) incorporated into client electronic devices528,530,532,534(respectively). Storage devices520,522,524,526may 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 client electronic devices528,530,532,534may include, but are not limited to, data-enabled, cellular telephone528, laptop computer530, tablet computer532, laptop computer534, a notebook computer (not shown), a server computer (not shown), a gaming console (not shown), a smart television (not shown), and a dedicated network device (not shown). Client electronic devices528,530,532,534may each execute an operating system, examples of which may include but are not limited to Microsoft Windows™, Android™, WebOS™, iOS™, Redhat Linux™, or a custom operating system.

Users536,538,540,542may access telehealth process510directly through network514or through secondary network518. Further, telehealth process510may be connected to network514through secondary network518, as illustrated with link line544.

The various client electronic devices (e.g., client electronic devices528,530,532,534) may be directly or indirectly coupled to network514(or network518). For example, data-enabled, cellular telephone528and laptop computer530are shown wirelessly coupled to network514via wireless communication channels546,548(respectively) established between data-enabled, cellular telephone528, laptop computer530(respectively) and cellular network/bridge550, which is shown directly coupled to network514. Further, tablet computer532is shown wirelessly coupled to network514via wireless communication channel552established between tablet computer532and wireless access point (i.e., WAP)554, which is shown directly coupled to network514. WAP 554 may be, for example, an IEEE 802.11a, 802.11b, 802.11g, 802.11n, Wi-Fi, and/or Bluetooth device that is capable of establishing wireless communication channel552between tablet computer532and WAP 554. Additionally, laptop computer534is shown directly coupled to network518via a hardwired network connection.

The Telehealth System

Referring also toFIG.9and as discussed above, telehealth process510in combination with telehealth system512may be configured to enable telehealth medical encounters between a medical professional and a patient. While the following illustrative example concerns a telehealth medical encounter between a single doctor and a single patient, 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, telehealth process510in combination with telehealth system512may establish a telehealth medical encounter between a team of medical professionals, a patient and one or more interested parties (e.g., patients, relatives, guardians, etc.).

As is known in the art, telehealth is the distribution of health-related services and information via electronic information and telecommunication technologies. Telehealth medical encounters may allow long-distance patient and clinician contact, care, advice, reminders, education, intervention, monitoring, and remote admissions. Telemedicine may sometimes be used as a synonym, or may be used in a more limited sense to describe remote clinical services, such as diagnosis and monitoring. When rural settings, lack of transport, a lack of mobility, decreased funding, or a lack of staff restrict access to care; telehealth may bridge the gap, as well as provide: distance-learning, meetings, supervision, and presentations between practitioners; online information and health data management; and healthcare system integration. Telehealth may include two clinicians discussing a case over video conference; a robotic surgery occurring through remote access; physical therapy performed via digital monitoring instruments, live feed and application combinations; tests being forwarded between facilities for interpretation by a higher specialist; home monitoring through continuous sending of patient health data; client to practitioner online conference; or even videophone interpretation during a consult.

For example, assume that a patient (e.g., user538) wishes to meet with a doctor (e.g., user542). However and for various reasons (e.g., a pandemic, a geographic distance, lack of geographically-proximate practitioners, etc.), the patient (e.g., user538) cannot physically meet with the doctor (e.g., user542). Therefore, telehealth process510in combination with telehealth system512may enable the patient (e.g., user538) to virtually meet with the doctor (e.g., user542) via a telehealth medical encounter.

Specifically, the patient (e.g., user538) may utilize their client electronic device (e.g., laptop computer530) and telehealth process510c2to participate in a telehealth medical encounter with the doctor (e.g., user542), who will utilize their client electronic device (e.g., laptop computer534) and telehealth process510c4.

The client electronic device (e.g., laptop computer530) of the patient (e.g., user538) may include video camera600and microphone602to generate audio/video stream (e.g., AV stream604) that may be provided via telehealth system512to the client electronic device (e.g., laptop computer534) of the doctor (e.g., user542). Additionally, the client electronic device (e.g., laptop computer534) of the doctor (e.g., user542) may include video camera606and microphone608to generate audio/video stream (e.g., AV stream610) that may be provided via telehealth system512to the client electronic device (e.g., laptop computer530) of the patient (e.g., user538).

Telehealth process510(generally) and telehealth process510c2(specifically) may render user interface612on the client electronic device (e.g., laptop computer530) of the patient (e.g., user538). User interface612may render a smaller-size video feed of the patient (e.g., user538), which is obtained from video camera600and allows the patient (e.g., user538) to monitor the way that they appear within the telehealth medical encounter. Further, user interface612may render a larger-size video feed of the doctor (e.g., user542) as well as an audio signal from the doctor (e.g., user542) on speaker assembly614, both of which are obtained from AV stream610and allow the patient (e.g., user538) to see, hear and interact with the doctor (e.g., user542).

Telehealth process510(generally) and telehealth process510c4(specifically) may render user interface616on the client electronic device (e.g., laptop computer534) of the doctor (e.g., user542). User interface616may render a smaller-size video feed of the doctor (e.g., user542), which is obtained from video camera606and allows the doctor (e.g., user542) to monitor the way that they appear within the telehealth medical encounter. Further, user interface616may render a larger-size video feed of the patient (e.g., user538) as well as an audio signal from the patient (e.g., user538) on speaker assembly618, both of which are obtained from AV stream604and allow the doctor (e.g., user542) to see, hear and interact with the patient (e.g., user538).

Telehealth system512may be coupled to one or more collaborating systems (e.g., collaborating system620), 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.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.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.

Accordingly and through the use of such a PAX system and an EHR system, the doctor (e.g., user42) may access and review medical images and electronic health records associated with the patient (e.g., user38).

Telehealth system512may also be coupled to an ambient cooperative intelligence system (e.g., ACI system54described above). ACI system54may be configured to automate the gathering and processing of clinical encounter information (e.g., gathered encounter information624) associated with a patient encounter (e.g., the telehealth medical encounter between the patient (e.g., user538) and the doctor (e.g., user542)).

As discussed above, ACI system54may be configured to process the encounter information (e.g., gathered encounter information624) to generate an encounter transcript (e.g., encounter transcript626), wherein ACI system54may then process at least a portion of the encounter transcript (e.g., encounter transcript626) to populate at least a portion of a medical record (e.g., medical record628) associated with the patient encounter (e.g., the telehealth medical encounter between the patient (e.g., user538) and the doctor (e.g., user542)). Accordingly, ACI system54may gather clinical encounter information (e.g., gathered encounter information624) associated with the telehealth medical encounter between the patient (e.g., user538) and the doctor (e.g., user542) to generate/store/distribute medical records (e.g., medical records628) for the patient (e.g., user538).

As also discussed above, ACI system54may be configured to process the encounter information (e.g., gathered encounter information624) to assign roles to the participants of the meeting. For example, ACI system54may listen for specific phases stated by the participants, such as “Hello, I am Dr. Jones . . . what brings you to the office today?” (which would indicate that the person speaking is a doctor) or “Hello Doctor, I am having a hard time breathing for the past couple of weeks” (which would indicate that the person speaking is a patient). Additionally/alternatively, ACI system54may monitor the network connection from which the participants are accessing telehealth system512. For example, the client electronic device (e.g., laptop computer534) of the doctor (e.g., user542) may access telehealth system512from a local IP address (e.g., 192.xxx.yyy.zzz), while the client electronic device (e.g., laptop computer530) of the patient (e.g., user538) may access telehealth system512from a remote IP address (e.g., 113.xxx.yyy.zzz). Accordingly, ACI system54may process gathered encounter information624to assign a role of “doctor” to user542and assign the role of “patient” to user538.

ACI system54may utilize natural language processing and artificial intelligence to process data included within the encounter transcript (e.g., encounter transcript626) and/or data included within AV streams604,610. For example and as will be discussed below, ACI system54may monitor the meeting between the patient (e.g., user538) and the doctor (e.g., user542) during the above-described telehealth medical encounter.

As is known in the art, natural language processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data. The goal is a computer capable of “understanding” the contents of documents, including the contextual nuances of the language within them. The technology may then accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves.

As is known in the art, artificial intelligence (AI) and/or machine learning (ML) is the study of computer algorithms that improve automatically through experience and by the use of data. Artificial intelligence and machine learning algorithms may build a model based on sample data (known as “training data”) in order to make predictions or decisions without being explicitly programmed to do so. Artificial intelligence and machine learning algorithms may be used in a wide variety of applications, such as in medicine, email filtering, speech recognition, and computer vision, wherein it may be difficult or unfeasible to develop conventional algorithms to perform the needed tasks. Artificial intelligence and machine learning may involve computers discovering how they can perform tasks without being explicitly programmed to do so (e.g., where computers learn from sample data (known as “training data”) how to carry out certain tasks.

As is known in the art, a machine learning system or model may generally include an algorithm (or combination of algorithms) that has been trained to recognize certain types of patterns. For example, machine learning approaches may be generally divided into three categories, depending on the nature of the signal available: supervised learning, unsupervised learning, and reinforcement learning. As is known in the art, supervised learning may include presenting a computing device with example inputs and their desired outputs, given by a “teacher”, where the goal is to learn a general rule that maps inputs to outputs. With unsupervised learning, no labels are given to the learning algorithm, leaving it on its own to find structure in its input. Unsupervised learning can be a goal in itself (discovering hidden patterns in data) or a means towards an end (feature learning). As is known in the art, reinforcement learning may generally include a computing device interacting in a dynamic environment in which it must perform a certain goal (such as driving a vehicle or playing a game against an opponent). As it navigates its problem space, the program is provided feedback that's analogous to rewards, which it tries to maximize. While three examples of machine learning approaches have been provided, it will be appreciated that other machine learning approaches are possible within the scope of the present disclosure.

The Telehealth Process

Referring also toFIG.10, telehealth process510(alone or in conjunction with ACI system54) may monitor700a meeting (e.g., the above-described telehealth medical encounter) between a patient (e.g., user538) and a medical entity. Examples of this medical entity may include but are not limited to: a medical professional (e.g., user542) and a medical virtual assistant (e.g., medical virtual assistant630). As is known in the art, a virtual assistant (e.g., medical virtual assistant630) is a software agent that may perform tasks or services for an individual based upon commands or questions. The term “chatbot” is sometimes used to refer to virtual assistants generally or specifically to those accessed via online chat. Some virtual assistants may interpret human speech and respond via synthesized voices. Users may ask their virtual assistant questions, control home automation devices and media playback via voice, and manage other basic tasks such as email, to-do lists, and calendars with verbal commands.

When monitoring700the meeting (e.g., the above-described telehealth medical encounter) between (in this example) the patient (e.g., user538) and the medical entity, natural language processing and artificial intelligence may be utilized to process data included within the encounter transcript (e.g., encounter transcript626) and/or data included within AV streams604,610.

The meeting (e.g., the above-described telehealth medical encounter) may include one or more of: a consultation portion; an intake portion; and a follow-up portion.Consultation portion: An example of such a consultation portion may include but is not limited to a telehealth session in which the patient (e.g., user538) is discussing a medical situation with the medical professional (e.g., user542) and/or medical virtual assistant630.Intake Portion: An example of such an intake portion may include but is not limited to an intake session in which the patient (e.g., user538) is initiating a telehealth medical encounter and providing information to the medical professional (e.g., user542) and/or medical virtual assistant630concerning e.g., symptoms and/or issues to be discussed during the consultation portion.Follow-Up Portion: An example of such a follow-up portion may include but is not limited to a follow-up session in which the patient (e.g., user38) is providing follow-up information to the medical professional (e.g., user542) and/or medical virtual assistant630in response to e.g., a wellness check-in call.
Participant Identification

As will be discussed below, telehealth process510(alone or in conjunction with ACI system54) may identify702a portion of the meeting (e.g., the above-described telehealth medical encounter) associated with the patient (e.g., user538), thus identifying a patient meeting portion (e.g., patient meeting portion556).

Telehealth process510(alone or in conjunction with ACI system54) may process704the meeting (e.g., the above-described telehealth medical encounter) to clarify the portion of the meeting (e.g., patient meeting portion556) associated with the patient (e.g., user538). For example, telehealth process510(alone or in conjunction with ACI system54) may apply various noise-cancellation algorithms/processes/filters to the patient meeting portion (e.g., patient meeting portion556) to e.g., remove background noise, eliminate crosstalk and/or reduce distortion.

When identifying702a portion of the meeting (e.g., the above-described telehealth medical encounter) associated with the patient (e.g., user538), thus identifying a patient meeting portion, telehealth process510(alone or in conjunction with ACI system54) may utilize706a voiceprint (e.g., voiceprint558) to identify the portion of the meeting (e.g., the above-described telehealth medical encounter) associated with the patient (e.g., user538).

As is known in the art, a voiceprint (e.g., voiceprint558) is a digital model of the unique vocal characteristics of an individual. Voiceprints (e.g., voiceprint558) may be created by specialized computer programs that process speech samples, wherein the creation of a voiceprint may be referred to as “enrollment” in a biometric system. A voiceprint may be created by performing “feature extraction” on one or more speech samples, wherein this feature extraction process may essentially create personalized calculations or vectors related to specific attributes that make the user's speech unique. Accordingly and if a voiceprint (e.g., voiceprint558) had been previously created for e.g., the patient (e.g., user538), this previously-created voiceprint (e.g., voiceprint558) may be utilized to identify patient meeting portion556(i.e., the portion of the meeting associated with user538).

Additionally/alternatively and when identifying702a portion of the meeting (e.g., the above-described telehealth medical encounter) associated with the patient (e.g., user538), thus identifying a patient meeting portion, telehealth process510(alone or in conjunction with ACI system54) may monitor708words/phrases included in the meeting (e.g., the above-described telehealth medical encounter) to identify the portion of the meeting (e.g., the above-described telehealth medical encounter) associated with the patient (e.g., user538). Accordingly and as discussed above, telehealth process510(alone or in conjunction with ACI system54) may listen for specific phases stated by the participants, such as “Hello, I am Dr. Jones . . . what brings you to the office today?” (which would indicate that the person speaking is a doctor (e.g., user542)) or “Hello Doctor, I am having a hard time breathing for the past couple of weeks” (which would indicate that the person speaking is a patient (e.g., user538)).

Additionally/alternatively and when identifying702a portion of the meeting (e.g., the above-described telehealth medical encounter) associated with the patient (e.g., user538), thus identifying a patient meeting portion, telehealth process510(alone or in conjunction with ACI system54) may monitor710network connections to identify the portion of the meeting (e.g., the above-described telehealth medical encounter) associated with the patient (e.g., user538). Accordingly and as discussed above, the client electronic device (e.g., laptop computer534) of the doctor (e.g., user542) may access telehealth system512from a local IP address (e.g., 192.xxx.yyy.zzz), while the client electronic device (e.g., laptop computer530) of the patient (e.g., user538) may access telehealth system512from a remote IP address (e.g., 113.xxx.yyy.zzz).

As will be discussed below, telehealth process510(alone or in conjunction with ACI system54) may identify712a portion of the meeting (e.g., the above-described telehealth medical encounter) associated with the medical professional (e.g., user542), thus identifying a medical professional meeting portion (e.g., medial professional meeting portion560).

Telehealth process510(alone or in conjunction with ACI system54) may process714the meeting (e.g., the above-described telehealth medical encounter) to clarify the portion of the meeting (e.g., medical professional meeting portion560) associated with the medical professional (e.g., user542). For example, telehealth process510(alone or in conjunction with ACI system54) may apply various noise-cancellation algorithms/processes/filters to the medical professional meeting portion (e.g., medical professional meeting portion560) to e.g., remove background noise, eliminate crosstalk and/or reduce distortion.

When identifying712a portion of the meeting (e.g., the above-described telehealth medical encounter) associated with the medical professional (e.g., user542), thus identifying a medical professional meeting portion, telehealth process510(alone or in conjunction with ACI system54) may utilize716a voiceprint (e.g., voiceprint562) to identify the portion of the meeting (e.g., the above-described telehealth medical encounter) associated with the medical professional (e.g., user542). Accordingly and if a voiceprint (e.g., voiceprint562) had been previously created for e.g., the medical professional (e.g., user542), this previously-created voiceprint (e.g., voiceprint562) may be utilized to identify medical professional meeting portion560(i.e., the portion of the meeting associated with user542).

Additionally/alternatively and when identifying712a portion of the meeting (e.g., the above-described telehealth medical encounter) associated with the medical professional (e.g., user542), thus identifying a medical professional meeting portion, telehealth process510(alone or in conjunction with ACI system54) may monitor718words/phrases included in the meeting (e.g., the above-described telehealth medical encounter) to identify the portion of the meeting (e.g., the above-described telehealth medical encounter) associated with the medical professional (e.g., user542). Accordingly and as discussed above, telehealth process510(alone or in conjunction with ACI system54) may listen for specific phases stated by the participants, such as “Hello, I am Dr. Jones . . . what brings you to the office today?” (which would indicate that the person speaking is a doctor (e.g., user542)) or “Hello Doctor, I am having a hard time breathing for the past couple of weeks” (which would indicate that the person speaking is a patient (e.g., user538)).

Additionally/alternatively and when identifying712a portion of the meeting (e.g., the above-described telehealth medical encounter) associated with the medical professional (e.g., user542), thus identifying a medical professional meeting portion, telehealth process510(alone or in conjunction with ACI system54) may monitor720network connections to identify the portion of the meeting (e.g., the above-described telehealth medical encounter) associated with the medical professional (e.g., user542). Accordingly and as discussed above, the client electronic device (e.g., laptop computer534) of the doctor (e.g., user542) may access telehealth system512from a local IP address (e.g., 192.xxx.yyy.zzz), while the client electronic device (e.g., laptop computer530) of the patient (e.g., user538) may access telehealth system512from a remote IP address (e.g., 113.xxx.yyy.zzz).

Medical Intelligence (Generally)

System Overview

As discussed above, meetings may occur between a patient (e.g., user228or user538) and a medical entity, examples of which may include but are not limited to a medical professional (e.g., user226or user542) and/or a medical virtual assistant (e.g., medical virtual assistant238or medical virtual assistant630). As also discussed above, these meetings may occur as in-person medical encounters (e.g., via ambient cooperative intelligence process10and ACI system54) or as telehealth medical encounters (e.g., via telehealth process510and telehealth system512), wherein these meetings may include one or more of: an intake portion (which may occur prior to the consultation portion); a consultation portion (wherein the patient meets with e.g., a doctor); and/or a follow-up portion (which may occur directly or shortly after the consultation portion).

Medical intelligence process56may be configured to be utilized during in-person medical encounters (e.g., via ambient cooperative intelligence process10and ACI system54) and/or telehealth medical encounters (e.g., via telehealth process510and telehealth system512). Accordingly and while the following illustrative example concerns medical intelligence process56being utilized during a telehealth medical encounter (e.g., via telehealth process510and telehealth system512), it is understood that (as discussed above) medical intelligence process56may be utilized during in-person medical encounters and/or telehealth medical encounters.

Informational Overlay Process:

As will be discussed below in greater detailed, medical intelligence process56may be configured to provide information to participants of meetings between a patient (e.g., user228or user538) and a medical entity, examples of which may include but are not limited to a medical professional (e.g., user226or user542), wherein this information may be provided in an unintrusive manner that does not interfere with the effectuation of the meeting.

Concept 1

As will be discussed below in greater detail, medical intelligence process56may be configured to render an informational window for review by a medical professional (e.g., user542) and/or a patient (e.g., user538) during a telehealth medical encounter (e.g., via telehealth process510and telehealth system512).

Referring also toFIG.11, medical intelligence process56may monitor750a meeting between a patient (e.g., user538) and a medical entity (e.g., user542and/or medical virtual assistant630) during a telehealth medical encounter (e.g., via telehealth process510and telehealth system512). As discussed above, these meetings may include one or more of: an intake portion (which may occur prior to the consultation portion); a consultation portion (wherein the patient meets with e.g., a doctor); and/or a follow-up portion (which may occur directly or shortly after the consultation portion).

Accordingly and during the intake portion of the meeting, a virtual assistant (e.g., medical virtual assistant630) may be utilized to gather intake information from the patient (e.g., user538). Example of such intake information may include but are not limited to: name, address, phone number, emergency contact information, date of birth, height, weight, vital signs, allergies, current medications, insurance information, etc.). Further and during the consultation portion of the meeting, a medical professional (e.g., user542) and the patient (e.g., user538) may discuss the reason for the meeting. Additionally and during the follow-up portion of the meeting, the virtual assistant (e.g., medical virtual assistant630) may be utilized to gather follow-up information from the patient (e.g., user538). Example of such follow-up information may include but are not limited to: scheduling a future meeting, discussing medications and instructions, wellness check information, etc.

Medical intelligence process56may gather752information during the telehealth medical encounter, thus generating gathered encounter information (e.g., gathered encounter information624).

Medical intelligence process56may render754an informational window (e.g., informational window632,634) concerning the telehealth medical encounter for review by the patient (e.g., user538) and/or the medical entity (e.g., user542), wherein the informational window (e.g., informational window632,634) may be configured to provide supplemental information (e.g., supplemental information636,638respectively) based, at least in part, upon the gathered encounter information (e.g., gathered encounter information624).

The informational window (e.g., informational window632,634) may be a transparent overlay informational window. For example, informational window (e.g., informational window632,634) may be configured to function in a similar fashion to a head-up display (i.e., positionable on top of other pieces of information without obscuring them), thus allowing the patient (e.g., user538) and/or the medical entity (e.g., user542) to review the supplemental information (e.g., supplemental information636,638respectively) while fully participating in the telehealth medical encounter.

As is known in the art, a head-up display, also known as a HUD, is any transparent display that presents data without requiring users to look away from their usual viewpoints. The origin of the name stems from a pilot being able to view information with the head positioned “up” and looking forward, instead of angled down looking at lower instruments. A HUD also has the advantage that the pilot's eyes do not need to refocus to view the outside after looking at the optically nearer instruments.

The supplemental information (e.g., supplemental information636,638) provided within the informational window (e.g., informational window632,634) may include one of more of: patient status information; EHR-provided information; patient-provided information; patient allergy information; patient medication information; medication interaction information; and AI-generated information.Patient Status Information: The supplemental information (e.g., supplemental information636,638) provided within the informational window (e.g., informational window632,634) may include patient status information, examples of which may include but are not limited to patient name, address, phone number, emergency contact information, date of birth, height, weight, vital signs, allergies, current medications, and insurance information. This patient status information may include current patient status information (e.g., patient status information at the time of the telehealth medical encounter) and historic patient status information (e.g., patient status information at some point prior to the telehealth medical encounter).EHR-Provided Information: The supplemental information (e.g., supplemental information636,638) provided within the informational window (e.g., informational window632,634) may include EHR-provided information, examples of which may include but are not limited to any information that may be included within the electronic health record (EHR) of a patient (e.g., treatment history, illness history, etc.).Patient-Provided Information: The supplemental information (e.g., supplemental information636,638) provided within the informational window (e.g., informational window632,634) may include patient-provided information, examples of which may include but are not limited to current aches, current pains, issues, and current concerns, as well as information included within the patient's health wallet (e.g., an electronic repository for the patient's health information that is controlled by the patient).Patient Allergy Information: The supplemental information (e.g., supplemental information636,638) provided within the informational window (e.g., informational window632,634) may include patient allergy information (e.g., allergy information known by the patient that may not be included within the EHR of the patient).Patient Medication Information: The supplemental information (e.g., supplemental information636,638) provided within the informational window (e.g., informational window632,634) may include patient medication information (e.g., medication information known by the patient that may not be included within the EHR of the patient).Medication Interaction Information: The supplemental information (e.g., supplemental information636,638) provided within the informational window (e.g., informational window632,634) may include medication interaction information, examples of which may include but are not limited to known side effects/interactions of medication currently being taken by the patient and known side effects/interactions of medication being considered for the patient.AI-Generated Information: The supplemental information (e.g., supplemental information636,638) provided within the informational window (e.g., informational window632,634) may include AI-generated information.

A will be discussed below in greater detail, this AI-Generated Information may include one or more of: AI-generated best practices information; AI-generated medical encounter workflow information; AI-generated recommendations; AI-generated suggested inquiry information; and AI-generated observational information (each of which will be discussed below in greater detail).AI-Generated Best Practices Information: The AI-Generated Best Practices Information may include information intended to define or provide guidance concerning one or more proposed best practices concerning e.g., the telehealth medical encounter.AI-Generated Medical Encounter Workflow Information: The AI-Generated Medical Encounter Workflow Information may include information intended to define or provide guidance concerning one or more proposed workflows concerning e.g., the telehealth medical encounter.AI-Generated Recommendations: The AI-Generated Recommendations may include information intended to define or provide guidance concerning one or more proposed recommendations concerning e.g., the telehealth medical encounter.AI-Generated Suggested Inquiry Information: The AI-Generated Suggested Inquiry Information may include information intended to define or provide guidance concerning one or more proposed inquiries concerning e.g., the telehealth medical encounter.AI-Generated Observational Information: The AI-Generated Observational Information may include information intended to provide observations concerning e.g., the telehealth medical encounter. As will be discussed below in greater detail, this AI-Generated Observational Information may include one or more of: AI-generated audible observational information (e.g., observational information defined within audio-based content associated with e.g., the telehealth medical encounter), and AI-generated visual observational information (e.g., observational information defined within image-based content and/or video-based content associated with e.g., the telehealth medical encounter).

Medical intelligence process56may enable756the patient (e.g., user538) and/or the medical entity (e.g., user542) to adjust one or more of: the size of the informational window (e.g., informational window632,634); the position of the informational window (e.g., informational window632,634); the transparency of the informational window (e.g., informational window632,634); and the content of the informational window (e.g., informational window632,634).

Further, medical intelligence process56may store758one or more user-defined visual preferences (e.g., user preferences640) for the informational window (e.g., informational window632,634) for use during subsequent sessions of the informational window (e.g., informational window632,634).

Intelligent Monitoring and Guidance (Generally):

As will be discussed below in greater detailed, medical intelligence process56may be configured to monitor meetings between a patient (e.g., user228or user538) and a medical entity, examples of which may include but are not limited to a medical professional (e.g., user226or user542) and/or a medical virtual assistant (e.g., medical virtual assistant238or medical virtual assistant630). These meetings may occur as in-person medical encounters (e.g., via ambient cooperative intelligence process10and ACI system54) or as telehealth medical encounters (e.g., via telehealth process510and telehealth system512). As will be discussed below in greater detail, medical intelligence process56may then provide guidance (e.g., in the form of supplemental information) to the medical professional (e.g., user226or user542) with respect to the same.

Concept 2

As will be discussed below in greater detail, medical intelligence process56may be configured to provide medical encounter workflow information for review by a medical professional (e.g., user226or user542) during in-person medical encounters (e.g., via ambient cooperative intelligence process10and ACI system54) and/or telehealth medical encounters (e.g., via telehealth process510and telehealth system512). While the following illustrative example concerns medical intelligence process56being utilized during a telehealth medical encounter (e.g., via telehealth process510and telehealth system512), it is understood that (as discussed above) medical intelligence process56may be utilized during in-person medical encounters and/or telehealth medical encounters.

Referring also toFIG.12, medical intelligence process56may monitor800a meeting between a patient (e.g., user538) and a medical entity (e.g., user542and/or medical virtual assistant630) during a medical encounter (e.g., a telehealth medical encounter).

Medical intelligence process56may gather802information during the medical encounter (e.g., a telehealth medical encounter), thus generating gathered encounter information (e.g., gathered encounter information624).

Medical intelligence process56may generate804medical encounter workflow information (e.g., medical encounter workflow information642) via artificial intelligence, wherein the medical encounter workflow information (e.g., medical encounter workflow information642) may be based at least in part upon the gathered encounter information (e.g., gathered encounter information624) and may be configured to provide guidance to the medical entity (e.g., user542) concerning a desired workflow for the medical encounter (e.g., a telehealth medical encounter), wherein such a desired workflow may quantify a preferred manner in which the medical encounter (e.g., a telehealth medical encounter) should proceed.

The medical encounter workflow information (e.g., medical encounter workflow information642) may be based upon one or more best practices (e.g., best practices644), wherein these one or more best practices (e.g., best practices644) may be definable by one or more medical organizations/institutions (e.g., organizations/institutions646). Examples of such medical organizations/institutions (e.g., organizations/institutions646) may include but are not limited to the hospital network for which user542works, the insurance company through which user538is insured, local/state/regional licensing boards, etc.

When generating804medical encounter workflow information (e.g., medical encounter workflow information642) via artificial intelligence, medical intelligence process56may:generate806initial medical encounter workflow information (e.g., an initial version of medical encounter workflow information642) in response to initial information gathered during the medical encounter (e.g., a telehealth medical encounter); andgenerate808supplemental medical encounter workflow information (e.g., a supplemental version of medical encounter workflow information642) in response to supplemental information gathered during the medical encounter (e.g., a telehealth medical encounter).

Specifically, when medical intelligence process56has more knowledge as to what the medical encounter (e.g., a telehealth medical encounter) is about, the workflow may be more defined. However, up until that point, the workflow may be more fluid/wandering. For example, if the patient (e.g., user538) is initially explaining to the medical entity (e.g., user542) that they are having difficulty breathing, medical intelligence process56may initiate a first workflow to investigate whether the patient (e.g., user538) has COVID, notifying the medical entity (e.g., user542) that “This Patient may have COVID” and prompting them to make inquiries about sense of taste and smell. In the event that it seems that the patient (e.g., user538) does not have COVID, medical intelligence process56may initiate a second workflow to investigate whether the patient (e.g., user538) has pneumonia.

Medical intelligence process56may provide810the medical encounter workflow information (e.g., medical encounter workflow information642) to the medical entity (e.g., user542). When providing810the medical encounter workflow information (e.g., medical encounter workflow information642) to the medical entity (e.g., user542), medical intelligence process56may provide812the medical encounter workflow information (e.g., medical encounter workflow information642) to the medical entity (e.g., user542) via an informational window (e.g., informational window634).

The informational window (e.g., informational window634) may be a transparent overlay informational window. As discussed above, the informational window (e.g., informational window634) may be configured to function in a similar fashion to a head-up display (i.e., positionable on top of other pieces of information without obscuring them), thus allowing the medical entity (e.g., user542) to review the medical encounter workflow information (e.g., medical encounter workflow information642) while fully participating in the telehealth medical encounter.

Generally speaking, medical intelligence process56may observe the progression of the medical encounter (e.g., a telehealth medical encounter) and may direct the medical encounter (e.g., a telehealth medical encounter) via prompts (e.g., within informational window634) along a desired workflow that may be based upon one or more best practices (e.g., best practices644), wherein these best practices (e.g., best practices644) may be definable by organizations/institutions646. For example, when proscribing medication, medical intelligence process56may confirm that the medical entity (e.g., user542) inquiries about medicine allergies, and prior allergic reactions. In the event that the medical entity (e.g., user542) does not make such inquiries, medical intelligence process56may prompt (e.g., within informational window634) the medical entity (e.g., user542) to do so. Further, medical intelligence process56may confirm that standard closing questions are used prior to ending the medical encounter (e.g., a telehealth medical encounter). For example, if the medical entity (e.g., user542) does not inquire if the patient (e.g., user538) has any questions before ending the medical encounter (e.g., a telehealth medical encounter), medical intelligence process56may prompt (e.g., within informational window634) the medical entity (e.g., user542) to do so.

Medical intelligence process56may receive814feedback concerning the medical encounter workflow information (e.g., medical encounter workflow information642) from the medical entity (e.g., user542). This feedback may be active, wherein medical intelligence process56may inquire as to whether the medical encounter workflow information was helpful. Additionally/alternatively, this feedback may be passive, wherein medical intelligence process56may gauge the quality of the medical encounter workflow information by monitoring whether the medical entity (e.g., user542) follows the prompts of medical intelligence process56.

Concept 3

As will be discussed below in greater detail, medical intelligence process56may be configured to process image-based content and provide guidance for review by a medical professional (e.g., user226or user542) during in-person medical encounters (e.g., via ambient cooperative intelligence process10and ACI system54) and/or telehealth medical encounters (e.g., via telehealth process510and telehealth system512). While the following illustrative example concerns medical intelligence process56being utilized during a telehealth medical encounter (e.g., via telehealth process510and telehealth system512), it is understood that (as discussed above) medical intelligence process56may be utilized during in-person medical encounters and/or telehealth medical encounters.

Referring also toFIG.13, medical intelligence process56may monitor850a meeting between a patient (e.g., user538) and a medical entity (e.g., user542and/or medical virtual assistant630) during a medical encounter (e.g., a telehealth medical encounter).

Medical intelligence process56may gather852information during the medical encounter (e.g., a telehealth medical encounter), thus generating gathered encounter information (e.g., gathered encounter information624). This gathered encounter information (e.g., gathered encounter information624) may include image-based content (e.g., image-based content648) of the patient (e.g., user538). An example of image-based content648may include but is not limited to a still image/photograph/screen capture of e.g., a wound, a bruise or a mole on the patient (e.g., user538).

Medical intelligence process56may generate854image-based content information (e.g., image-based content information650) via artificial intelligence, wherein the image-based content information (e.g., image-based content information650) may be based at least in part upon the image-based content (e.g., image-based content648) and/or the gathered encounter information (e.g., gathered encounter information624) and may be configured to provide guidance to the medical entity (e.g., user542) concerning the image-based content (e.g., image-based content648). For example, medical intelligence process56may capture image-based content648(e.g., the still image, the photograph, the screen capture) of e.g., the wound/bruise/mole on the patient (e.g., user538).

When generating854image-based content information (e.g., image-based content information650) via artificial intelligence, medical intelligence process56may reactively generate856image-based content information (e.g., image-based content information650) via artificial intelligence in response to a request by the medical entity (e.g., user542). For example, assume that the patient (e.g., user538) has a mole on their forehead that is visible by medical entity (e.g., user542) during the medical encounter (e.g., a telehealth medical encounter). Accordingly, the medical entity (e.g., user542) may reactively generate856the image-based content information (e.g., image-based content information650) by manually initiating the capture of image-based content648(e.g., the still image, the photograph, the screen capture) of the mole on the patient (e.g., user538).

Additionally/alternatively and when generating854image-based content information (e.g., image-based content information650) via artificial intelligence, medical intelligence process56may proactively generate858image-based content information (e.g., image-based content information850) via artificial intelligence without requiring human intervention. For example and continuing with the example in which the patient (e.g., user538) has a mole on their forehead that is visible during the medical encounter (e.g., a telehealth medical encounter), medical intelligence process56may proactively generate858image-based content information (e.g., image-based content information850) via artificial intelligence without requiring human intervention (e.g., without requiring initiation by the medical entity (e.g., user542).

Additionally/alternatively and when generating854image-based content information (e.g., image-based content information650) via artificial intelligence, medical intelligence process56may compare860a current version of the image-based content (e.g., image-based content648) to a previous version of the image-based content (e.g., image-based content648) to determine if the image-based content (e.g., image-based content648) has changed. Continuing with the example in which the patient (e.g., user538) has a mole on their forehead that is visible during the medical encounter (e.g., a telehealth medical encounter), medical intelligence process56may repeatedly capture image-based content648(e.g., the still image, the photograph, the screen capture) of the mole on the patient (e.g., user538) during every medical encounter (e.g., once every six months during scheduled telehealth medical encounters), thus creating a temporally spaced sequence of image-based content648. Medical intelligence process56may compare860a current version (e.g., the latest version) of the image-based content (e.g., image-based content648) to a previous version of the image-based content (e.g., image-based content648) to determine if the image-based content (e.g., image-based content648) has changed (which may be indicative of a cancerous condition).

Additionally/alternatively and when generating854image-based content information (e.g., image-based content information650) via artificial intelligence, medical intelligence process56may compare862the image-based content (e.g., image-based content648) to image-based information (e.g., image-based information652) associated with one or more ailments/conditions to identify one or more potential ailments/conditions. For example and continuing with the example in which the patient (e.g., user538) has a mole on their forehead that is visible during the medical encounter (e.g., a telehealth medical encounter), medical intelligence process56may capture image-based content648(e.g., the still image, the photograph, the screen capture) of the mole on the patient (e.g., user538) and may compare862the image-based content (e.g., image-based content648) to image-based information (e.g., image-based information652) associated with one or more ailments/conditions (e.g., pictures of cancerous moles) to identify one or more potential ailments/conditions (e.g., one or more skin cancers).

Generally speaking, medical intelligence process56may enable the capturing of close proximity/high resolution images (e.g., image-based content648) that may be incorporated into a medical record, wherein these close proximity/high resolution images (e.g., image-based content648) may be processed by medical intelligence process56to assess any visual concerns (e.g., to gauge wound healing, paleness, bruising, jaundice, etc.).

Medical intelligence process56may provide864the image-based content information (e.g., image-based content information650) to the medical entity (e.g., user542). When providing864the image-based content information (e.g., image-based content information650) to the medical entity (e.g., user542), medical intelligence process56may provide866the image-based content information (e.g., image-based content information650) to the medical entity (e.g., user542) via an informational window (e.g., informational window634). Accordingly and continuing with the above-stated example, informational window634may display image-based content information650that says “This Patient shows signs of skin cancer”

The informational window (e.g., informational window634) may be a transparent overlay informational window. As discussed above, the informational window (e.g., informational window634) may be configured to function in a similar fashion to a head-up display (i.e., positionable on top of other pieces of information without obscuring them), thus allowing the medical entity (e.g., user542) to review the image-based content information (e.g., image-based content information650) while fully participating in the telehealth medical encounter.

Medical intelligence process56may seek approval from the patient (e.g., user538) before image-based content648(e.g., the still image, the photograph, the screen capture) is captured and/or added to the medical record (e.g., medical record628) of the patient (e.g., user538)

Concept 4

As will be discussed below in greater detail, medical intelligence process56may be configured to process audio-based content and provide guidance for review by a medical professional (e.g., user226or user542) during in-person medical encounters (e.g., via ambient cooperative intelligence process10and ACI system54) and/or telehealth medical encounters (e.g., via telehealth process510and telehealth system512). While the following illustrative example concerns medical intelligence process56being utilized during a telehealth medical encounter (e.g., via telehealth process510and telehealth system512), it is understood that (as discussed above) medical intelligence process56may be utilized during in-person medical encounters and/or telehealth medical encounters.

Referring also toFIG.14, medical intelligence process56may monitor900a meeting between a patient (e.g., user538) and a medical entity (e.g., user542and/or medical virtual assistant630) during a medical encounter (e.g., a telehealth medical encounter).

Medical intelligence process56may gather902information during the medical encounter (e.g., a telehealth medical encounter), thus generating gathered encounter information (e.g., gathered encounter information624). This gathered encounter information (e.g., gathered encounter information624) may include audio-based content (e.g., audio-based content654) of the patient (e.g., user538). An example of audio-based content654may include but is not limited to an audio recording of the voice of the patient (e.g., user538).

Medical intelligence process56may generate904audio-based content information (e.g., audio-based content information656) via artificial intelligence, wherein the audio-based content information (e.g., audio-based content information656) may be based at least in part upon the audio-based content (e.g., audio-based content654) and/or the gathered encounter information (e.g., gathered encounter information624) and may be configured to provide guidance to the medical entity (e.g., user542) concerning the audio-based content (e.g., audio-based content654). For example, medical intelligence process56may capture audio-based content654(e.g., an audio recording of a conversation between the patient (e.g., user538) and the medical entity (e.g., user542).

When generating904audio-based content information (e.g., audio-based content information656) via artificial intelligence, medical intelligence process56may reactively generate906audio-based content information (e.g., audio-based content information656) via artificial intelligence in response to a request by the medical entity (e.g., user542). For example, assume that the patient (e.g., user538) is slurring their speech during the medical encounter (e.g., a telehealth medical encounter). Accordingly, the medical entity (e.g., user542) may reactively generate906the audio-based content information (e.g., audio-based content information656) by manually initiating the recording of audio-based content654(e.g., the audio recording of the speech) of the patient (e.g., user538).

Additionally/alternatively and when generating904audio-based content information (e.g., audio-based content information656) via artificial intelligence, medical intelligence process56may proactively generate908audio-based content information (e.g., audio-based content information656) via artificial intelligence without requiring human intervention. Continuing with the example in which the patient (e.g., user538) is slurring their speech during the medical encounter (e.g., a telehealth medical encounter), medical intelligence process56may proactively generate908audio-based content information (e.g., audio-based content information656) via artificial intelligence without requiring human intervention (e.g., without requiring initiation by the medical entity (e.g., user542).

Additionally/alternatively and when generating904audio-based content information (e.g., audio-based content information656) via artificial intelligence, medical intelligence process56may compare910a current version of the audio-based content (e.g., audio-based content654) to a previous version of the audio-based content (e.g., audio-based content654) to determine if the audio-based content (e.g., audio-based content654) has changed. Continuing with the example in which the patient (e.g., user538) is slurring their speech during the medical encounter (e.g., a telehealth medical encounter), medical intelligence process56may repeatedly capture audio-based content654(e.g., the audio recording of the speech) of the patient (e.g., user538) during every medical encounter (e.g., once every six months during scheduled telehealth medical encounters), thus creating a temporally spaced sequence of audio-based content654. Medical intelligence process56may compare910a current version (e.g., the latest version) of the audio-based content (e.g., audio-based content654) to a previous version of the audio-based content (e.g., audio-based content654) to determine if the audio-based content (e.g., audio-based content654) has changed (which may be indicative of a degenerating neurological condition).

Additionally/alternatively and when generating904audio-based content information (e.g., audio-based content information656) via artificial intelligence, medical intelligence process56may compare912the audio-based content (e.g., audio-based content654) to audio-based information (e.g., audio-based information658) associated with one or more ailments/conditions to identify one or more potential ailments/conditions. Continuing with the example in which the patient (e.g., user538) is slurring their speech during the medical encounter (e.g., a telehealth medical encounter), medical intelligence process56may capture audio-based content654(e.g., the audio recording of the speech) of the patient (e.g., user538) and may compare912the audio-based content (e.g., audio-based content654) to audio-based information (e.g., audio-based information658) associated with one or more ailments/conditions (e.g., audio recordings of people who had strokes) to identify one or more potential ailments/conditions (e.g., strokes, brain bleeds, etc.).

Generally speaking, medical intelligence process56may process the audio of the medical encounter (e.g., a telehealth medical encounter) to determine if the patient (e.g., user538) is afflicted with a disease (e.g., depression, dementia, vocal cord problems, respiratory ailments).

Medical intelligence process56may provide914the audio-based content information (e.g., audio-based content information656) to the medical entity (e.g., user542). When providing914the audio-based content information (e.g., audio-based content information656) to the medical entity (e.g., user542), medical intelligence process56may provide916the audio-based content information (e.g., audio-based content information656) to the medical entity (e.g., user542) via an informational window (e.g., informational window634). Accordingly and continuing with the above-stated example, informational window634may display audio-based content information656that says “This Patient shows signs of a stroke/brain bleed”.

The informational window (e.g., informational window634) may be a transparent overlay informational window. As discussed above, the informational window (e.g., informational window634) may be configured to function in a similar fashion to a head-up display (i.e., positionable on top of other pieces of information without obscuring them), thus allowing the medical entity (e.g., user542) to review the audio-based content information (e.g., audio-based content information656) while fully participating in the telehealth medical encounter.

Medical intelligence process56may seek approval from the patient (e.g., user538) before audio-based content (e.g., audio-based content654) is recorded and/or added to the medical record (e.g., medical record628) of the patient (e.g., user538).

Concept 5

As will be discussed below in greater detail, medical intelligence process56may be configured to process video-based content and provide guidance for review by a medical professional (e.g., user226or user542) during in-person medical encounters (e.g., via ambient cooperative intelligence process10and ACI system54) and/or telehealth medical encounters (e.g., via telehealth process510and telehealth system512). While the following illustrative example concerns medical intelligence process56being utilized during a telehealth medical encounter (e.g., via telehealth process510and telehealth system512), it is understood that (as discussed above) medical intelligence process56may be utilized during in-person medical encounters and/or telehealth medical encounters.

Referring also toFIG.15, medical intelligence process56may monitor950a meeting between a patient (e.g., user538) and a medical entity (e.g., user542and/or medical virtual assistant630) during a medical encounter (e.g., a telehealth medical encounter).

Medical intelligence process56may gather952information during the medical encounter (e.g., a telehealth medical encounter), thus generating gathered encounter information (e.g., gathered encounter information624). This gathered encounter information (e.g., gathered encounter information624) may include video-based content (e.g., video-based content660) of the patient (e.g., user538). An example of video-based content660may include but is not limited to a video recording of the patient (e.g., user538).

Medical intelligence process56may generate954video-based content information (e.g., video-based content information662) via artificial intelligence, wherein the video-based content information (e.g., video-based content information662) may be based at least in part upon the video-based content (e.g., video-based content660) and/or the gathered encounter information (e.g., gathered encounter information624) and may be configured to provide guidance to the medical entity (e.g., user542) concerning the video-based content (e.g., video-based content662). For example, medical intelligence process56may capture video-based content660(e.g., a video recording of a meeting between the patient (e.g., user538) and the medical entity (e.g., user542).

When generating954video-based content information (e.g., video-based content information662) via artificial intelligence, medical intelligence process56may reactively generate956video-based content information (e.g., video-based content information662) via artificial intelligence in response to a request by the medical entity (e.g., user542). For example, assume that the patient (e.g., user538) is experiencing hand tremors during the medical encounter (e.g., a telehealth medical encounter). Accordingly, the medical entity (e.g., user542) may reactively generate956the video-based content information (e.g., video-based content information662) by manually initiating the recording of video-based content660(e.g., the video recording of the hand tremors) of the patient (e.g., user538).

When generating954video-based content information (e.g., video-based content information662) via artificial intelligence, medical intelligence process56may proactively generate958video-based content information (e.g., video-based content information662) via artificial intelligence without requiring human intervention. Continuing with the example in which the patient (e.g., user538) is experiencing hand tremors during the medical encounter (e.g., a telehealth medical encounter), medical intelligence process56may proactively generate958video-based content information (e.g., video-based content information662) via artificial intelligence without requiring human intervention (e.g., without requiring initiation by the medical entity (e.g., user542).

When generating954video-based content information (e.g., video-based content information662) via artificial intelligence, medical intelligence process56may compare960a current version of the video-based content (e.g., video-based content660) to a previous version of the video-based content (e.g., video-based content660) to determine if the video-based content (e.g., video-based content660) has changed. Continuing with the example in which the patient (e.g., user538) is experiencing hand tremors during the medical encounter (e.g., a telehealth medical encounter), medical intelligence process56may repeatedly capture video-based content660(e.g., the video recording of the hand tremors) of the patient (e.g., user538) during every medical encounter (e.g., once every six months during scheduled telehealth medical encounters), thus creating a temporally spaced sequence of video-based content660. Medical intelligence process56may compare960a current version (e.g., the latest version) of the video-based content (e.g., video-based content660) to a previous version of the video-based content (e.g., video-based content660) to determine if the video-based content (e.g., video-based content660) has changed (which may be indicative of e.g., advancing Parkinson's disease).

When generating954video-based content information (e.g., video-based content information662) via artificial intelligence, medical intelligence process56may compare962the video-based content (e.g., video-based content660) to video-based information (e.g., video-based information664) associated with one or more ailments/conditions to identify one or more potential ailments/conditions. Continuing with the example in which the patient (e.g., user538) is experiencing hand tremors during the medical encounter (e.g., a telehealth medical encounter), medical intelligence process56may capture video-based content660(e.g., the video recording of the hand tremors) of the patient (e.g., user538) and may compare962the video-based content (e.g., video-based content660) to video-based information (e.g., video-based information664) associated with one or more ailments/conditions (e.g., video recordings of people who had Parkinson's disease) to identify one or more potential ailments/conditions (e.g., Parkinson's disease).

Generally speaking, medical intelligence process56may process the video of the medical encounter (e.g., a telehealth medical encounter) to determine if the patient (e.g., user538) is afflicted with a disease (e.g., depression, dementia, Alzheimer's, Parkinson's, hypertension (via skin pulsations), elevated heart rate (via skin pulsations), respiratory ailments, mobility problems, signs of spousal abuse, signs of child abuse, etc.

Medical intelligence process56may provide964the video-based content information (e.g., video-based content information662) to the medical entity (e.g., user542). When providing964the video-based content information (e.g., video-based content information662) to the medical entity (e.g., user542), medical intelligence process56may provide966the video-based content information (e.g., video-based content information662) to the medical entity (e.g., user542) via an informational window (e.g., informational window634). Accordingly and continuing with the above-stated example, informational window634may display video-based content information662that says “This Patient shows signs of Parkinson's Disease”.

The informational window (e.g., informational window634) may be a transparent overlay informational window. As discussed above, the informational window (e.g., informational window634) may be configured to function in a similar fashion to a head-up display (i.e., positionable on top of other pieces of information without obscuring them), thus allowing the medical entity (e.g., user542) to review the video-based content information (e.g., audio-based content information662) while fully participating in the telehealth medical encounter.

Medical intelligence process56may seek approval from the patient (e.g., user538) before video-based content (e.g., video-based content660) is recorded and/or added to the medical record (e.g., medical record628) of the patient (e.g., user538).

Concept 6

As will be discussed below in greater detail, medical intelligence process56may be configured to provide guidance concerning third-party encounters for review by a medical professional (e.g., user226or user542) during in-person medical encounters (e.g., via ambient cooperative intelligence process10and ACI system54) and/or telehealth medical encounters (e.g., via telehealth process510and telehealth system512). While the following illustrative example concerns medical intelligence process56being utilized during a telehealth medical encounter (e.g., via telehealth process510and telehealth system512), it is understood that (as discussed above) medical intelligence process56may be utilized during in-person medical encounters and/or telehealth medical encounters.

Referring also toFIG.16, medical intelligence process56may monitor1000a meeting between a patient (e.g., user538) and a medical entity (e.g., user542and/or medical virtual assistant630) during a medical encounter (e.g., a telehealth medical encounter).

Medical intelligence process56may gather1002information during the medical encounter (e.g., a telehealth medical encounter), thus generating gathered encounter information (e.g., gathered encounter information624).

Medical intelligence process56may process1004the gathered encounter information (e.g., gathered encounter information624) via artificial intelligence to determine whether a third-party encounter should be initiated. If it is determined that the third-party encounter should be initiated, medical intelligence process56may provide1006a recommendation (e.g., recommendation666) to the medical entity (e.g., user542) for the third-party encounter. Additionally, one or more third-party providers available for the third-party encounter may be identified. Further, the medical entity may be enabled to specify a particular third-party provider.

When providing1006a recommendation (e.g., recommendation666) to the medical entity (e.g., user542) for the third-party encounter if it is determined that the third-party encounter should be initiated, medical intelligence process56may provide1008a recommendation (e.g., recommendation666) to the medical entity (e.g., user542) for the third-party encounter via an informational window (e.g., informational window634) if it is determined that the third-party encounter should be initiated.

The informational window (e.g., informational window634) may be a transparent overlay informational window. As discussed above, the informational window (e.g., informational window634) may be configured to function in a similar fashion to a head-up display (i.e., positionable on top of other pieces of information without obscuring them), thus allowing the medical entity (e.g., user542) to review the recommendation (e.g., recommendation666) while fully participating in the telehealth medical encounter

Continuing with the example in which the patient (e.g., user538) has a mole on their forehead that is visible during the medical encounter (e.g., a telehealth medical encounter), medical intelligence process56may process1004the gathered encounter information (e.g., gathered encounter information624) via artificial intelligence to determine whether a third-party encounter should be initiated. Assume that medical intelligence process56determines that it is probable that the patient (e.g., user538) has skin cancer. Accordingly, medical intelligence process56may provide1006a recommendation (e.g., recommendation666) to the medical entity (e.g., user542) for a third-party encounter with e.g., a dermatologist and/or an oncologist.

Medical intelligence process56may enable1010the medical entity (e.g., user542) to manually initiate the third-party encounter in response to the provided recommendation (e.g., recommendation666). For example and assuming that the medical entity (e.g., user542) agrees with the recommendation (e.g., recommendation666) provided, the medical entity (e.g., user542) may manually initiate the third-party encounter with third-party entity668(e.g., a dermatologist and/or an oncologist) in response to the recommendation (e.g., recommendation666). Additionally/alternatively, medical intelligence process56may identify one or more third-party providers that are available for the third-party encounter. For example, medical intelligence process56may present the medical entity (e.g., user542) with a list (not shown) of available third-party entities (e.g., dermatologists and/or an oncologists) from which the medical entity (e.g., user542) may make a selection. Additionally,/alternatively, the medical entity (e.g., user542) may be enabled to specify a particular third-party provider (e.g., from the list of available third-party entities (not shown))

Additionally/alternatively, medical intelligence process56may automatically initiate1012the third-party encounter if it is determined that the third-party encounter should be initiated. As discussed above, medical intelligence process56may process1004the gathered encounter information (e.g., gathered encounter information624) via artificial intelligence to determine whether a third-party encounter should be initiated. Accordingly, if medical intelligence process56determines that the third-party encounter with third-party entity668(e.g., a dermatologist and/or an oncologist) should be initiated, medical intelligence process56may automatically initiate1012the third-party encounter with third-party entity668(e.g., a dermatologist and/or an oncologist). Various factors may influence the above-described process. For example, medical intelligence process56may take into consideration various elements, examples of which may include but are not limited to: the particular area of specialization of the third-party encounter; whether the patient (e.g., user538) is known by a particular third-party provider; if a particular third-party provider is in-network (for insurance purposes); and the general costs associated with a particular third-party provider.

When automatically initiating1012the third-party encounter if it is determined that the third-party encounter should be initiated, medical intelligence process56may determine1014whether third-party entity668(e.g., a dermatologist and/or an oncologist) is available to timely participate in the third-party encounter. Accordingly, medical intelligence process56may determine1014whether third-party entity668(e.g., a dermatologist and/or an oncologist) is available to join the medical encounter (e.g., the telehealth medical encounter) immediately (or within a reasonable amount of time).

Concept 7

As will be discussed below in greater detail, medical intelligence process56may be configured to provide supplement information for review by a medical professional (e.g., user226or user542) during in-person medical encounters (e.g., via ambient cooperative intelligence process10and ACI system54) and/or telehealth medical encounters (e.g., via telehealth process510and telehealth system512). While the following illustrative example concerns medical intelligence process56being utilized during a telehealth medical encounter (e.g., via telehealth process510and telehealth system512), it is understood that (as discussed above) medical intelligence process56may be utilized during in-person medical encounters and/or telehealth medical encounters.

Referring also toFIG.17, medical intelligence process56may monitor1050a meeting between a patient (e.g., user538) and a medical entity (e.g., user542and/or medical virtual assistant630) during a medical encounter (e.g., a telehealth medical encounter).

Medical intelligence process56may gather1052information during the medical encounter (e.g., a telehealth medical encounter), thus generating gathered encounter information (e.g., gathered encounter information624). Medical intelligence process56may provide1054supplemental information (e.g., supplemental information638) to the medical entity (e.g., user542) based, at least in part, upon the gathered encounter information (e.g., gathered encounter information624).

As discussed above, supplemental information (e.g., supplemental information638) may include one of more of: patient status information; EHR-provided information; patient-provided information; patient allergy information; patient medication information; medication interaction information; and AI-generated information.Patient Status Information: The supplemental information (e.g., supplemental information638) provided within the informational window (e.g., informational window634) may include patient status information, examples of which may include but are not limited to patient name, address, phone number, emergency contact information, date of birth, height, weight, vital signs, allergies, current medications, insurance information. This patient status information may include current patient status information (e.g., patient status information at the time of the telehealth medical encounter) and historic patient status information (e.g., patient status information at some point prior to the telehealth medical encounter).EHR-Provided Information: The supplemental information (e.g., supplemental information638) provided within the informational window (e.g., informational window634) may include EHR-provided information, examples of which may include but are not limited to any information that may be included within the electronic health record (EHR) of a patient (e.g., treatment history, illness history, etc.).Patient-Provided Information: The supplemental information (e.g., supplemental information638) provided within the informational window (e.g., informational window634) may include patient-provided information, examples of which may include but are not limited to current aches, current pains, issues, and current concerns, as well as information included within the patient's health wallet (e.g., an electronic repository for the patient's health information that is controlled by the patient).Patient Allergy Information: The supplemental information (e.g., supplemental information638) provided within the informational window (e.g., informational window634) may include patient allergy information (e.g., allergy information known by the patient that may not be included within the EHR of the patient).Patient Medication Information: The supplemental information (e.g., supplemental information638) provided within the informational window (e.g., informational window634) may include patient medication information (e.g., medication information known by the patient that may not be included within the EHR of the patient).Medication Interaction Information: The supplemental information (e.g., supplemental information638) provided within the informational window (e.g., informational window634) may include medication interaction information, examples of which may include but are not limited to known side effects/interactions of medication currently being taken by the patient and known side effects/interactions of medication being considered for the patient.AI-Generated Information: The supplemental information (e.g., supplemental information638) provided within the informational window (e.g., informational window634) may include AI-generated information.

This AI-Generated Information may include one or more of: AI-generated best practices information; AI-generated medical encounter workflow information; AI-generated recommendations; AI-generated suggested inquiry information; and AI-generated observational information (each of which will be discussed below in greater detail).AI-Generated Best Practices Information: The AI-Generated Best Practices Information may include information intended to define or provide guidance concerning one or more proposed best practices concerning e.g., the telehealth medical encounter.AI-Generated Medical Encounter Workflow Information: The AI-Generated Medical Encounter Workflow Information may include information intended to define or provide guidance concerning one or more proposed workflows concerning e.g., the telehealth medical encounter.AI-Generated Recommendations: The AI-Generated Recommendations may include information intended to define or provide guidance concerning one or more proposed recommendations concerning e.g., the telehealth medical encounter.AI-Generated Suggested Inquiry Information: The AI-Generated Suggested Inquiry Information may include information intended to define or provide guidance concerning one or more proposed inquiries concerning e.g., the telehealth medical encounter.AI-Generated Observational Information: The AI-Generated Observational Information may include information intended to provide observations concerning e.g., the telehealth medical encounter. This AI-Generated Observational Information may include one or more of: AI-generated audible observational information (e.g., observational information defined within audio-based content associated with e.g., the telehealth medical encounter), and AI-generated visual observational information (e.g., observational information defined within image-based content and/or video-based content associated with e.g., the telehealth medical encounter).

Generally speaking, medical intelligence process56may provide notifications and guidance to the medical entity (e.g., user542) in a manner that gains the attention of the medical entity (e.g., user542) without interfering with their ability to effectuate the medical encounter (e.g., an in-person medical encounter and/or a telehealth medical encounter). Medical intelligence process56may tag some or all of the supplemental information (e.g., supplemental information638) provided to the medical entity (e.g., user542) based upon severity. For example, low importance supplemental information may be provided to the medical entity (e.g., user542) in a solid white font; medium importance supplemental information may be provided to the medical entity (e.g., user542) in a solid red font; while high importance supplemental information may be provided to the medical entity (e.g., user542) in a flashing red font. These visual notifications may automatically fade aware after a defined period of time; or may stay illuminated until the medical entity (e.g., user542) “clicks” on the visual notification; or may stay illuminated until medical intelligence process56detects that the medical entity (e.g., user542) addressed the visual notification during the medical encounter (e.g., an in-person medical encounter and/or a telehealth medical encounter). Additionally, these visual notifications may be supplemented with audible notifications (via a speaker assembly or an ear bud worn by user542). As discussed above, medical intelligence process56may monitor1050the meeting between a patient (e.g., user538) and a medical entity (e.g., user542and/or medical virtual assistant630) during a medical encounter (e.g., an in-person medical encounter and/or a telehealth medical encounter). Accordingly, in the event that certain defined best practices appear to be missed by the medical entity (e.g., user542), the supplemental information (e.g., supplemental information638) provided by medical intelligence process56may remind the medical entity (e.g., user542) to e.g., ask about current medications, discuss medication allergies, ask if there is anything else that needs to be discussed, etc.

When providing1054supplemental information (e.g., supplemental information638) to the medical entity (e.g., user542) based, at least in part, upon the gathered encounter information (e.g., gathered encounter information624), medical intelligence process56may provide1056supplemental information (e.g., supplemental information638) to the medical entity (e.g., user542) based, at least in part, upon the gathered encounter information (e.g., gathered encounter information624) via an informational window (e.g., informational window634).

The informational window (e.g., informational window634) may be a transparent overlay informational window. As discussed above, the informational window (e.g., informational window634) may be configured to function in a similar fashion to a head-up display (i.e., positionable on top of other pieces of information without obscuring them), thus allowing the medical entity (e.g., user542) to review the supplemental information (e.g., supplemental information638) while fully participating in the telehealth medical encounter.

Medical intelligence process56may receive feedback concerning the supplemental information (e.g., supplemental information638) from the medical entity (e.g., user542). This feedback may be active, wherein medical intelligence process56may inquire as to whether the supplemental information was helpful. Additionally/alternatively, this feedback may be passive, wherein medical intelligence process56may gauge the quality of the supplemental information by monitoring whether the medical entity (e.g., user542) follows the prompts of medical intelligence process56.

Concept 8

As will be discussed below in greater detail, medical intelligence process56may be configured to provide medical encounter topical information for review by a medical professional (e.g., user226or user542) during in-person medical encounters (e.g., via ambient cooperative intelligence process10and ACI system54) and/or telehealth medical encounters (e.g., via telehealth process510and telehealth system512). While the following illustrative example concerns medical intelligence process56being utilized during a telehealth medical encounter (e.g., via telehealth process510and telehealth system512), it is understood that (as discussed above) medical intelligence process56may be utilized during in-person medical encounters and/or telehealth medical encounters.

Referring also toFIG.18, medical intelligence process56may monitor1100a meeting between a patient (e.g., user538) and a medical entity (e.g., user542and/or medical virtual assistant630) during a medical encounter (e.g., a telehealth medical encounter).

Medical intelligence process56may gather1102information during the medical encounter (e.g., a telehealth medical encounter), thus generating gathered encounter information (e.g., gathered encounter information624).

Medical intelligence process56may generate1104medical encounter topical information (e.g., medical encounter topical information670) via artificial intelligence, wherein the medical encounter topical information (e.g., medical encounter topical information670) may be based at least in part upon the gathered encounter information (e.g., gathered encounter information624) and is configured to provide guidance to the medical entity (e.g., user542) concerning one or more topics to be discussed during the medical encounter (e.g., an in-person medical encounter and/or a telehealth medical encounter). This medical encounter topical information (e.g., medical encounter topical information670) may be based upon one or more best practices (e.g., best practices644), wherein these one or more best practices (e.g., best practices644) may be definable by one or more medical organizations/institutions (e.g., organizations/institutions646).

When generating1104medical encounter topical information (e.g., medical encounter topical information670) via artificial intelligence, medical intelligence process56may:generate1106initial medical encounter topical information (e.g., medical encounter topical information670) in response to initial information gathered during the medical encounter (e.g., a telehealth medical encounter); andgenerate1108supplemental medical encounter topical information (e.g., medical encounter topical information670) in response to supplemental information gathered during the medical encounter (e.g., a telehealth medical encounter).

Specifically, when medical intelligence process56has more knowledge as to what the medical encounter (e.g., a telehealth medical encounter) is about, the topics and progression thereof may be more defined. However, up until that point, the topics may be more fluid/wandering. For example, if the patient (e.g., user538) is initially explaining to the medical entity (e.g., user542) that they are having difficulty breathing, medical intelligence process56may initiate a first topic to investigate whether the patient (e.g., user538) has COVID, notifying the medical entity (e.g., user542) that “This Patient may have COVID” and prompting them to make inquiries about sense of taste and smell. In the event that it seems that the patient (e.g., user538) does not have COVID, medical intelligence process56may initiate a second topic to investigate whether the patient (e.g., user538) has pneumonia.

Generally speaking, medical intelligence process56may process data from previous visits with the medical entity (e.g., user542), or in a particular hospital or in a group of hospitals to determine the manner in which a medical encounter (e.g., an in-person medical encounter and/or a telehealth medical encounter) should flow (e.g., the progression of the medical encounter, such as Topic ATopic BTopic CTopic DTopic E). The medical entity (e.g., user542) may then be provided with prompts concerning proposed discussion topics. The sequencing of such topics may be definable by one or more medical organizations/institutions (e.g., organizations/institutions646).

Medical intelligence process56may provide1110the medical encounter topical information (e.g., medical encounter topical information670) to the medical entity (e.g., user542). When providing1110the medical encounter topical information (e.g., medical encounter topical information670) to the medical entity (e.g., user542), medical intelligence process56may provide1112the medical encounter topical information (e.g., medical encounter topical information670) to the medical entity (e.g., user542) via an informational window (e.g., informational window634).

The informational window (e.g., informational window634) may be a transparent overlay informational window. As discussed above, the informational window (e.g., informational window634) may be configured to function in a similar fashion to a head-up display (i.e., positionable on top of other pieces of information without obscuring them), thus allowing the medical entity (e.g., user542) to review the medical encounter topical information (e.g., medical encounter topical information670) while fully participating in the telehealth medical encounter

Medical intelligence process56may receive1114feedback concerning the medical encounter topical information (e.g., medical encounter topical information670) from the medical entity (e.g., user542). This feedback may be active, wherein medical intelligence process56may inquire as to whether the medical encounter topical information was helpful. Additionally/alternatively, this feedback may be passive, wherein medical intelligence process56may gauge the quality of the medical encounter topical information by monitoring whether the medical entity (e.g., user542) follows the prompts of medical intelligence process56.

General:

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.

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.

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., network14).

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.

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.

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.

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.

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.

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.

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.