Database management and graphical user interfaces for measurements collected by analyzing blood

Inventors

McRAITH, Kevin • KESANI, Hari • Iyer, Anand • SUSAI, Gabriel • SHOMALI, Mansur • RAO, Prasad Matti

Assignees

WellDoc Inc

Abstract

Methods and devices include database management and graphical user interfaces for measurements collected by analyzing blood.

Core Innovation

The disclosed invention provides a computer-implemented method for managing blood glucose levels of a user using a continuous glucose monitoring device comprising a subcutaneous sensor to provide blood glucose values. The method electronically receives, at a server, data including types and dosages of medications consumed by the user and the blood glucose values, stores the received data in a database, and extracts health data including cohort data comprising blood glucose values of one or more other users.

The extracted metadata and cohort data are input into one or more machine learning algorithms to generate a treatment plan for improving the blood glucose values of the user at an end of a treatment period as compared to the blood glucose values at a beginning of the treatment period. The treatment plan includes instructions for tasks performed by the user, including prescribed blood glucose measurement pairs to be measured before and after meals, prescribed timing and dosage of medication, a prescribed amount of carbohydrates, or prescribed exercise.

During the first subset of the treatment period, the system electronically receives data relating to the treatment plan, including medications consumed, amount of exercise performed, and blood glucose levels of the user. Based on determined medication compliance, exercise compliance, and identified patterns, the treatment plan is revised for a subsequent subset, and the method determines, based on the identified patterns, a trigger event that occurs before an adverse effect and sends a notification to the user upon detecting an instance of the trigger event.

In certain implementations, the system additionally includes extracting metadata from stored medication and A1C data to generate a goal for reduction in the A1C value based on cohort data, determining a tendency of the user to follow at least one of a medication regimen, a diet regimen, and an exercise regimen, administering a questionnaire, and receiving GPS data to generate a route for the user to walk along, where a distance of the route corresponds to the prescribed exercise in the treatment plan.

Claims Coverage

The document provides three independent claims that share the core workflow of continuous glucose monitoring and server-side receipt of medication and glucose data, machine-learning generation of a goal and task-based treatment plan from cohort data, iterative plan revision based on compliance and identified patterns, and trigger-event detection with user notifications. Across the independent claims, the inventive features include subcutaneous continuous glucose monitoring with server-side data receipt, cohort-based machine learning treatment-plan generation, iterative plan revision, trigger-event detection and notifications, A1C reduction goal generation, tendency determination using questionnaire answers, and GPS-based route generation.

Across the independent claims, the invention centers on generating an end-of-treatment improvement plan using cohort-based machine learning driven by subcutaneous continuous glucose monitoring data and medication data, issuing task-based instructions, revising the plan based on compliance and identified patterns, and detecting trigger events that precede adverse effects with user notifications; additional independent-claim scope includes A1C reduction goal generation, tendency determination via questionnaire, and GPS-based route generation tied to prescribed exercise.

Stated Advantages

Documented Applications