Patent ID: 11908558
Assignee: CLOVER HEALTH
Field: Medical technology (Instruments)
Classification: CPC G | IPC G

Claim 13:
14. A method comprising:
generating a first machine learning model configured to predict whether medication fills will be missed;
generating a training dataset corresponding to health-related data associated with users and first user input data indicating prior interactions with a medication-related system that led to successful medication fills or refills;
training the first machine learning model utilizing at least the training dataset such that a first trained machine learning model is generated by identifying relationships between the health-related data associated with users, the first user input data, and the reminders sent to the users led to successful medication fills;
receiving a refill schedule associated with a user and a medication;
accessing user data associated with the user;
determining, based at least in part on the user data, indicators associated with the user;
determining, based at least in part on the refill history, that a refill of the medication will occur within a threshold period of time;
generating input data representing the indicators associated with the user, the input data formatted for input to the first trained machine learning model;
generating, utilizing the first trained machine learning model and the input data, results data indicating a probability that the user will miss refilling the medication satisfies a probability threshold, the probability associated with a combination of indicators that the user will miss refilling the first medication;
generating a second machine learning model configured to determine a reminder type to send;
training the second machine learning model based at least in part on previous interaction data associated with various reminder types such that a second trained machine learning model is generated;
determining, utilizing the second trained machine learning model, the type of reminder associated with the combination using (1) the indicators associated with the user, (2) the refill schedule, (3) the refill history, (4) the second user input data, (5) previous interaction data of the user with reminder types, (6) computing devices associated with the user, and (7) software technology associated with the user; and
transmitting, based at least in part on the results data, a reminder to a device associated with the user, wherein the reminder includes an interactive link as at least a portion of the reminder, the interactive link configured to, when selected by the first user:
display a user interface with a list of selectable actions associated with the first reminder, the selectable actions including scheduling a refill, having the medication delivered to the user, arranging transportation of the user to a location associated with the medication, and preparing the medication for an in-person pickup; and
adaptively perform at least one of the selectable actions based at least in part on receiving third user input data indicating selection of the at least one of the selectable actions, the reminder causing an application associated with the device to initiate and cause the user interface to be displayed, the user interface configured to present a visual representation of the reminder in response to receiving the reminder at the device, the reminder formatted as the type of reminder associated with the combination.