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

1. A method of reducing impact of user-entered data errors in a data management system (DMS), the DMS executing a DMS application on a processor to request user-entered event data from a user for an event via a DMS application interface and store the user-entered event data received from the user into a primary DMS database, the method comprising:

obtaining secondary data from at least two sensors, wherein a first sensor detects non-glucose data;

storing the secondary data into a secondary tracking database;

cross-checking the user-entered event data against the secondary data to determine whether the user-entered event data is consistent with the secondary data via the processor;

assigning a state and a weight to the user-entered event data based on a result of cross-checking, wherein the state indicates a status of the user-entered event data, and wherein the weight indicates a confidence level in an accuracy of the user-entered event data;

displaying a request to the user to review and correct or confirm the user-entered event data based on the state,

wherein displaying the request includes 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;

updating the state and the weight of the user-entered event data in the primary DMS database to an updated state and an updated weight based on a user's response to the request; and

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.

2. The method of claim 1 , wherein storing the user-entered event data includes prompting the user for information regarding at least one of a user's meal markers, a user's exercise, a user's medication, and a user's sleep.

3. The method of claim 1 , wherein storing the secondary data includes storing data received from the DMS application generating the secondary data from the primary DMS database based on one or more rules related to the event.

4. The method of claim 1 , wherein the cross-checking comprises associating the user-entered event data with the secondary data by comparing respective time stamps for the event received for the secondary data and for the user-entered event data.

5. The method of claim 1 , wherein the state is at least one of “to be reviewed”, “suspect”, “unverified”, “verified”, “validated”, and “invalidated”.

6. The method of claim 1 , wherein the weight is a numerical value.

7. The method of claim 1 , wherein updating the diabetes management plan includes altering a medication dosage.

8. A data management system (DMS) comprising:

a primary DMS database accessible by a DMS application;

a secondary tracking database accessible by the DMS application;

at least one sensor assembly; and

a DMS device in communication with the at least one sensor assembly including a processor coupled to a memory, the memory operative to store instructions executable on the processor to execute the DMS application operable to:

request user-entered event data from a user regarding an event;

store the user-entered event data into the primary DMS database;

obtain secondary data from at least two sensors of the at least one sensor assembly,

wherein a first sensor detects non-glucose data;

store the secondary data into the secondary tracking database;

cross-check the user-entered event data against the secondary data to determine whether the user-entered event data is consistent with the secondary data;

assign a state and a weight to the user-entered event data based on a cross-check result,

wherein the state indicates a status of the user-entered event data, and

wherein the weight indicates a confidence level in an accuracy of the user-entered event data;

display a review request to the user to review and correct or confirm the user-entered event data based on the state,

wherein displaying the review request includes 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;

update the state and the weight of the user-entered event data in the primary DMS database to an updated state and an updated weight based on a user's response to the review request; and

determine a diabetes management recommendation 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.

9. The DMS of claim 8 , wherein the review request includes prompting the user for information regarding at least one of a user's meal markers, a user's exercise, a user's medication, and a user's sleep.

10. The DMS of claim 8 , wherein the secondary data further comprises results of one or more rulesets stored in the memory applied to the user-entered event data stored in the primary DMS database related to the event.

11. The DMS of claim 8 , wherein cross-checking includes associating the user-entered event data with the secondary data by comparing respective time stamps for the event received with the secondary data and with the user-entered event data.

12. The DMS of claim 8 , wherein the state is at least one of “to be reviewed”, “suspect”, “unverified”, “verified”, “validated”, and “invalidated”.

13. The DMS of claim 8 , wherein the weight is a numerical value and wherein the diabetes management recommendation includes altering a medication dosage.

14. A method of reducing impact of user-entered data errors in a data management system (DMS), the DMS executing a DMS application on a processor to request user-entered event data from a user for an event regarding at least one of a user's meal markers, a user's exercise, a user's medication, and a user's sleep by prompting the user to manually enter event data, and store the user-entered event data received from the user into a primary DMS database, the method comprising:

obtaining secondary data from at least two sensors, wherein a first sensor detects biometric or physiological parameters other than blood glucose levels;

storing the secondary data into a secondary tracking database;

cross-checking the user-entered event data against the secondary data to determine whether the user-entered event data is consistent with the secondary data via the processor;

assigning a state and a weight to the user-entered event data based on a cross-checking result,

wherein the state indicates a status of the user-entered event data, and

wherein the weight indicates a confidence level in an accuracy of the user-entered event data;

displaying a request to the user to review and correct or confirm the user-entered event data based on the state,

wherein the request includes 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;

updating the state and the weight of the user-entered event data in the primary DMS database to an updated state and an updated weight based on a user's response to the request;

performing 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;

updating the weight to an updated accuracy weight based on a balancing analysis result; and

updating a diabetes management plan in response to the updated accuracy weight to indicate a change in medication, testing, diet, or exercise.

15. The method of claim 14 , wherein the balancing analysis determines whether to increase, decrease, maintain, or ignore the user-entered event data.

16. The method of claim 14 , wherein the first sensor is an on-body sensor capable of detecting at least one of: analytes other than blood glucose, blood pressure, heart rate, pulse, wakefulness, breathing rate, respiration, body temperature, ambient temperature, pulse oximetry, humidity, electrocardiogram, movement, acceleration, proximity, direction, altitude, speed, applied force, pressure, perspiration, aging, sound, eating/drinking, snoring, bodyweight, height, and body composition.

17. The method of claim 14 , wherein the secondary data includes data generated by the primary DMS database based on one or more rules related to the event.

18. The method of claim 14 , wherein the state is any one of “to be reviewed”, “suspect”, “unverified”, “verified”, “validated”, and “invalidated”.

19. The method of claim 14 , wherein the weight is a numerical value, and wherein updating the diabetes management plan includes altering a medication dosage.