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US 11,387,005 B2Granted
Secure patient messaging
AssigneeCVS Pharmacy, Inc.
InventorsBryan D. Tate, Christine C. Sawicki
Life of this patent
Estimating the term…
Abstract
The techniques described in this disclosure relate to methods and systems for generating a model profile to identify opportunities to, for example, initiate dialogue between a pharmacy and a patient. The techniques include a method comprising generating a model profile to identify at least one discrete opportunity to initiate dialogue with a patient; analyzing a patient profile associated with a patient to determine whether the patient profile fits the model profile; determining that the patient profile fits the model profile; and sending a message to the patient.
Claims18
A computer-implemented method comprising:
- capturing first patient data by a sensor of a patient computing device configured to monitor a state about a first patient;
- electronically transmitting, by the patient computing device, the first patient data to a centralized computing system;
- training, by the centralized computing system, a first instance of a machine learning model profile to identify at least one discrete opportunity to initiate dialogue with the first patient by applying at least one machine learning technique to at least the first patient data and based on the first patient being associated with a message type;
- analyzing, by the centralized computing system, a first patient profile associated with the first patient to determine whether the first patient profile fits the first instance of the machine learning model profile by identifying patterns within the first patient profile that match the machine learning model profile;
- in response to determining that the first patient profile fits the first instance of the machine learning model profile, automatically generating, by the centralized computing system, a message corresponding to the message type and based at least in part on the state about the first patient;
- generating, by the centralized computing system, a two-way secure communication with at least a pharmacy and the first patient;
- requesting, by the centralized computing system, health sensitive data associated with the first patient as part of the message over the two-way secure communication;
- automatically electronically transmitting, by the centralized computing system, the message over the two-way secure communication to a display of the patient computing device of the first patient;
- displaying the message on the display of the patient computing device of the first patient;
- electronically receiving, over the two-way secure communication, at the centralized computing system, a first patient response to the message based on a selection to the message on the display of the patient computing device by the first patient;
- retraining, by the centralized computing system, the first instance of the machine learning model profile based on the first patient response to the message on the display of the patient computing device, thereby generating a second instance of the machine learning model profile;
- and
- analyzing, by the centralized computing system, a second patient profile associated with a second patient to determine whether the second patient profile fits the second instance of the machine learning model profile by identifying patterns within the second patient profile that match the second instance of the machine learning model profile.
10 more elements
A system comprising:
- one or more processors;
- and
- one or more memories storing instructions that, when executed, cause the one or more processors to:
- capture first patient data by a sensor of a patient computing device configured to monitor a state about a first patient;
- electronically transmit the first patient data from the patient computing device;
- train a first instance of a machine learning model profile to identify at least one discrete opportunity to initiate dialogue with the first patient by applying at least one machine learning technique to at least the first patient data and based on the first patient being associated with a message type;
- analyze a first patient profile associated with the first patient to determine whether the first patient profile fits the first instance of the machine learning model profile by identifying patterns within the first patient profile that match the machine learning model profile;
- in response to determining that the first patient profile fits the first instance of the machine learning model profile, automatically generate a message corresponding to the message type and based at least in part on the state about the first patient;
- generate a two-way secure communication with at least a pharmacy and the first patient;
- request health sensitive data associated with the first patient as part of the message over the two-way secure communication;
- automatically electronically transmit the message over the two-way secure communication to a display of the patient computing device of the first patient;
- display the message on the display of the patient computing device of the first patient;
- electronically receive over the two-way secure communication a first patient response to the message based on a selection to the message on the display of the patient computing device by the first patient;
- retrain the first instance of the machine learning model profile based on the first patient response to the message on the display of the patient computing device, thereby generating a second instance of the machine learning model profile;
- and
- analyze a second patient profile associated with a second patient to determine whether the second patient profile fits the second instance of the machine learning model profile by identifying patterns within the second patient profile that match the second instance of the machine learning model profile.
13 more elements
Dependencies are inferred from the claim text.