Systems and methods for intelligently routing a member of an organization to a single point-of-contact within an optimized, secure network to address all the member's healthcare needs are described. The disclosed intelligent routing configurations transform and process, in real-time, vast amounts of member data to generate aggregated diagnoses and a member score specific to each member's household. The scores, among other things, are used to determine an identification of special needs and an appropriate advocate within the organization to route the member, and its account file containing real-time member and household level data.

A system for telemedicine diagnostics through remote sensing includes a computing device configured to initiate a communication interface between the computing device and a client device operated by a human subject, wherein the secure communication interface includes an audiovisual streaming protocol, receive, from at least a remote sensor at the human subject, a plurality of current physiological data, generate a clinical measurement approximation as a function of the change of a first discrete and a second discrete set of current physiological data, wherein generating further comprises receiving approximation training data correlating physiological data with clinical measurement data, training a measurement approximation model as a function of the training data and a machine-learning process, and generating the clinical measurement approximation as a function of the current physiological data and the measurement approximation model, and presenting the clinical measurement approximation to a user of the computing device using the secure communication interface.

A system for telemedicine diagnostics through remote sensing includes a computing device configured to initiate a communication interface between the computing device and a client device operated by a human subject, wherein the secure communication interface includes an audiovisual streaming protocol, receive, from at least a remote sensor at the human subject, a plurality of current physiological data, generate a clinical measurement approximation as a function of the change of a first discrete and a second discrete set of current physiological data, wherein generating further comprises receiving approximation training data correlating physiological data with clinical measurement data, training a measurement approximation model as a function of the training data and a machine-learning process, and generating the clinical measurement approximation as a function of the current physiological data and the measurement approximation model, and presenting the clinical measurement approximation to a user of the computing device using the secure communication interface.

A patient care method through artificial intelligence-based monitoring in accordance with one example of the present disclosure comprises steps of: obtaining image information relating a user by a first collecting portion, obtaining speech information relating to the user by a second collecting portion and obtaining biometrics information relating to the user by a third collecting portion (Step 1); representing at least a part of a plurality of information obtained from the first collecting portion, the second collecting portion and the third collecting portion, through a display portion of a user table (Step 2); determining health condition of the user, based on a part of the plurality of information obtained from the first collecting portion, the second collecting portion and the third collecting portion by a server (Step 3); controlling the display portion of the user table to represent a first information automatically generated based on the determined heath condition by the server (Step 4), wherein the first information is converted in real time based on user's feedback on the first information and represents a change in the determined health condition on the display portion.

A virtual care system can include a location module configured to receive location information associated with a device from the device, and a graphical user interface (GUI) module configured to generate a medical provider user interface accessible via the device. The medical provider user interface can be contextually generated based on the location information and includes interface characteristics associated with the location information.

Embodiments of a risk assessment and intervention platform architecture are disclosed, where the risk assessment and intervention platform can predict and reduce negative medical outcomes. Embodiments of the risk assessment and intervention platform may include components with controls or interface elements to receive instructions from clinicians to set parameters for interventions and then to enroll, track, and monitor patient activity through the medical treatment plans. Embodiments of a scoring engine are configured based on a specific medical treatment plan and intervention protocols to initiate intervention as needed.

Embodiments of a risk assessment and intervention platform architecture are disclosed, where the risk assessment and intervention platform can predict and reduce negative medical outcomes. Embodiments of the risk assessment and intervention platform may include components with controls or interface elements to receive instructions from clinicians to set parameters for interventions and then to enroll, track, and monitor patient activity through the medical treatment plans. Embodiments of a scoring engine are configured based on a specific medical treatment plan and intervention protocols to initiate intervention as needed.

Systems, methods, and a computer program product are provided which establish application-based telemedicine methods and protocols for providing authorization to an unlicensed or licensed user to perform a cleaning operation on a patient's ear canal. Specifically, once the user determines that a cleaning operation is necessary, an application is provided which allows the user to consolidate relevant information regarding the patient, send the relevant patient information along with a permission request to a licensed medical professional, receive an approved permission request, and perform a cleaning operation on the patient.

A method includes generating an intervention model for a population of users based on contact data, demographic data, and engagement data indicating successfulness of prior interventions for each of the population of users. The method includes, obtaining first data related to a first user, including engagement data indicating successfulness of prior interventions with the first user. The method includes supplying the obtained data as input to the intervention model to determine an intervention expectation, which indicates a likelihood that the first user will take action in response to an intervention. The method includes determining a likelihood of a gap in care. The method includes, in response to the care gap likelihood exceeding a minimum threshold, selecting and scheduling execution of a first intervention. The first intervention is one of a real-time communication with the first user by a specialist and an automated transmission of a message to the first user.

A method includes generating an intervention model for a population of users based on contact data, demographic data, and engagement data indicating successfulness of prior interventions for each of the population of users. The method includes, obtaining first data related to a first user, including engagement data indicating successfulness of prior interventions with the first user. The method includes supplying the obtained data as input to the intervention model to determine an intervention expectation, which indicates a likelihood that the first user will take action in response to an intervention. The method includes determining a likelihood of a gap in care. The method includes, in response to the care gap likelihood exceeding a minimum threshold, selecting and scheduling execution of a first intervention. The first intervention is one of a real-time communication with the first user by a specialist and an automated transmission of a message to the first user.