Patent ID: 11901073
Assignee: RYKOV LLC
Field: Medical technology (Instruments)
Classification: CPC G | IPC G

Claim 0:
1. A system for management of healthcare to support a social health network comprising:
a patient user interface customized by a patient user of the social health network and accessible from a first device;
a plurality of patient controlled electronic health records (EHRs), each EHR having a patient record associated with a patient, the EHRs shared with a plurality of health provider systems and external databases;
a data analytics platform comprising: one or more processors and at least one memory programmed to implement a network learning model, the network learning model generated from a training network to update one or more data sets comprising patient inputs, patient data from the patient record, and health provider data, individually or in combination, wherein the patient user interface provides an artificial intelligence (AI) generated depiction of data extracted from the one or more data sets or the network learning model, and customized from data of the patient user and the health provider user to create knowledge graphs personalized to the user and trending data characterized by data selections specific to the patient inputs, a diagnosis or treatment specific to a patient, and selections of health provider data;
one or more servers to store the updated data sets in at least one database, and programmed to create at least one patient profile through the patient user interface and at least one health provider profile associated with the at least one patient profile and accessible via a second user interface, the one or more servers further programmed to:
receive a request from the patient user of the social health network at the patient user interface to authorize release of the information associated with the patient user at an external system where the patient record of the patient user is stored, wherein the information requested comprises information identifying the patient user and a health provider user associated with the patient user in the social health network;
access the database by way of the processor, wherein the processor predicts data models in personalized health diagnosis, outcomes, treatments, disease, healthcare operations, administration and cost, and alternative suggestions using deep learning algorithms that analyze the data sets;
determine if the external system is authorized to transmit the information requested;
in response to a determination that the external system is authorized to transmit the information requested, process the request and extract the patient record of the patient user from the external system to provide extracted data of the patient user;
transmit the extracted data directly to the social health network;
separate the extracted data into subsets, wherein a first subset comprises health information with the patient user identified and available to be shared with the social health network, and a second subset comprises health information of the patient user available to be shared with the social health network when the patient user is de-identified;
de-identify a portion of the second subset of the extracted data to provide de-identified data of the patient user;
in response to a query or selection by the patient or the health provider user, the processor is directed to extract, sort, and trend data, the de-identified data, or any subset thereof;
wherein the step to de-identify occurs prior to the step to perform data analytics, thereby protecting privacy of the patient user; and
transmit one or more predictive suggestions or outcomes to at least one of the patient user interface or the second user interface as a personalized depiction of data generated by the patient inputs or health provider inputs in combination with the generated AI.