Patent ID: 11862302
Assignee: TELADOC HEALTH, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 16:
17. A method for automatically generating, by one or more processors, a structured medical note during a remote medical consultation, the method comprising:
providing, by a provider tele-presence device, two-way audio communication between a medical provider in the vicinity of the provider tele-presence device and a patient in the vicinity of a patient tele-presence device;
displaying, by the provider tele-presence device, information from a medical record of the patient;
recording, by at least one of the provider tele-presence device and the patient tele-presence device, audio data from communication between the medical provider and the patient;
receiving, by a machine learning network implemented on the one or more processors from over a communication network, the patient's medical record and the recorded audio data from the provider tele-presence device;
distinguishing, by the machine learning network, between speech of the medical provider and speech of the patient and removing other voices to obtain patient audio data and medical provider audio data, respectively;
electronically transcribing, by the machine learning network, at least the speech of the medical provider from the medical provider audio data;
electronically derive patient audio meta-data from the patient audio data, the patient audio meta-data including one or more of slurring in patient speech and a pause duration between a medical provider question and a start of a patient answer;
automatically generating, by the machine learning network, the structured medical note including at least a portion of the medical record, at least a portion of the transcribed speech, and at least a portion of the patient audio meta-data, wherein the structured medical note is stored in a medical documentation server coupled to the communication network in association with an identity of the patient and includes at least a first field for subjective information, a second field for objective information, a third field for assessment information, and a forth field for treatment plan information;
receiving, by the machine learning network, feedback including medical provider corrections to the automatically generated structured medical note; and
training the machine learning network based on the medical provider corrections.