Methods and apparatus to reduce the impact of user-entered data errors in diabetes management systems

Inventors

Curran, Kevin

Assignees

Ascensia Diabetes Care Holdings AG

Abstract

Embodiments provide systems, methods, and apparatus for reducing the impact of user-entered data errors in a data management system (DMS) such as for diabetes. Embodiments include storing user-entered data received from a user into a primary DMS database; storing secondary data received from a source other than the user into a secondary tracking database; associating the secondary data with one or more events described by the user-entered data; cross-checking the user-entered data against the associated secondary data; evaluating user-entered data based on the cross-checking results; presenting for review evaluated user-entered data; treating user-entered data in the primary DMS database based on review results; and determining a diabetes management plan based on the treated user-entered data. Numerous other aspects are provided.

Core Innovation

The document describes reducing impact of user-entered data errors in a data management system (DMS) executing a DMS application on a processor to request user-entered event data from a user for an event and to store the user-entered event data into a primary DMS database. The method obtains secondary data from at least two sensors, including a first sensor detecting non-glucose data or biometric or physiological parameters other than blood glucose levels, stores the secondary data into a secondary tracking database, and cross-checks the user-entered event data against the secondary data to determine whether the user-entered event data is consistent with the secondary data.

Based on a result of cross-checking, the DMS assigns a state and a weight to the user-entered event data, where the state indicates a status of the user-entered event data and the weight indicates a confidence level in an accuracy of the user-entered event data. The DMS displays a request to the user to review and correct or confirm the user-entered event data based on the state, including prompting the user to indicate whether the user-entered event data are more accurate than the secondary data or whether the secondary data is more accurate than the user-entered event data, and updates the state and the weight in the primary DMS database based on a user's response.

The document further provides updating a diabetes management plan in response to the updated state and the updated weight assigned to the user-entered event data indicating a change in medication, testing, diet, or exercise. In the additional method variant, the DMS performs a balancing analysis to assess a credibility of the user-entered event data based on a pattern of gaps detected in the user-entered event data, and updates the weight to an updated accuracy weight based on a balancing analysis result.

Claims Coverage

The partial content includes three independent claims (clm-00001, clm-00008, clm-00014). Across these claims, the document centers on cross-checking user-entered event data against secondary sensor data, assigning a state and a confidence weight, prompting user review/correction/confirmation, updating stored status and weight, and updating a diabetes management plan based on the updated values; one independent claim further adds a balancing analysis based on gaps in user-entered event data.

Across the independent claims, the core coverage is a DMS that cross-checks user-entered event data against secondary data from at least two sensors, assigns a state and confidence weight, prompts user review, updates the primary database with the updated state and weight, and updates a diabetes management plan based on the updated values; one independent claim additionally performs a balancing analysis based on patterns of gaps to further assess credibility and adjust the weight.

Stated Advantages

Documented Applications