METHODS AND APPARATUS TO REDUCE THE IMPACT OF USER-ENTERED DATA ERRORS IN DIABETES MANAGEMENT SYSTEMS

• US 20170091259A1
• Filed: 09/16/2016
• Published: 03/30/2017
• Est. Priority Date: 09/29/2015
• Status: Active Grant

• Current Assignee: Ascensia Diabetes Care Holdings AG (PHC Holdings Corporation)
• Original Assignee: Ascensia Diabetes Care Holdings AG (PHC Holdings Corporation)
• Inventors: Curran, Kevin
• Granted Patent: US 11,803,534 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 11/3006 where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems multiprogramming arrangements G06F9/46; allocation of resources G06F9/50
• CPC Class Codes: G06F 11/301 where the computing system is a virtual computing platform, e.g. logically partitioned systems virtual machines G06F9/45533; logical partitioning of resources G06F9/5077
• CPC Class Codes: G06F 11/3089 Monitoring arrangements determined by the means or processing involved in sensing the monitored data, e.g. interfaces, connectors, sensors, probes, agents software debugging using additional hardware using a specific debug interface G06F11/3656; performance evaluation by tracing or monitoring G06F11/3466
• CPC Class Codes: G06F 11/3466 Performance evaluation by tracing or monitoring
• CPC Class Codes: G06F 16/215 Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
• CPC Class Codes: G06F 16/22 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/2308 Concurrency control transaction processing G06F9/466
• CPC Class Codes: G06F 16/2315 Optimistic concurrency control
• CPC Class Codes: G06F 16/2322 using timestamps
• CPC Class Codes: G06F 16/2329 using versioning
• CPC Class Codes: G06F 16/2336 Pessimistic concurrency control approaches, e.g. locking or multiple versions without time stamps
• CPC Class Codes: G06F 16/2343 Locking methods, e.g. distributed locking or locking implementation details
• CPC Class Codes: G06F 16/2365 Ensuring data consistency and integrity
• CPC Class Codes: G06F 16/2379 Updates performed during online database operations; commit processing
• CPC Class Codes: G06F 2201/835 Timestamp
• CPC Class Codes: G06F 2201/86 Event-based monitoring
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

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.

Claims

1. A method of reducing impact of user-entered data errors in a data management system (DMS), the method comprising:

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 the user-entered data based on the cross-checking results;

presenting for review any user-entered data marked for review upon being evaluated;

treating the 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.

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

3. The method of claim 1, wherein storing secondary data includes receiving data from one or more sensor assemblies.

4. The method of claim 1, wherein storing secondary data includes receiving data from a DMS application generating secondary data from the primary DMS database based on one or more rules.

5. The method of claim 1, wherein associating the secondary data with one or more events described by the user-entered data includes identifying events and secondary events that occur proximate in time.

6. The method of claim 1, wherein cross-checking the user-entered data against the associated secondary data includes identifying user-entered data that appear to be incorrect or inconsistent with the associated secondary data.

7. The method of claim 1, wherein evaluating user-entered data includes assigning states to the user-entered data based on the cross-checking results.

8. The method of claim 7, wherein assigning states includes assigning a state of at least one of “

to be reviewed”

, “

suspect”

, “

unverified”

, “

verified”

, “

validated”

, and “

invalidated”

.

9. The method of claim 1, wherein presenting for review user-entered data marked for review includes prompting the user to indicate if the user-entered data or the associated secondary data is more accurate.

10. The method of claim 1, wherein treating user-entered data in the primary DMS database includes adjusting a weight of the user-entered data based on review results.

11. The method of claim 1, wherein determining a diabetes management plan based on the treated user-entered data includes factoring in weights assigned to the treated user-entered data when evaluating the user-entered data.

12. A data management system (DMS) comprising:

a DMS device adapted to execute a DMS application;

at least one sensor assembly in communication with the DMS device;

a primary DMS database accessible by the DMS application; and

a secondary tracking database accessible by the DMS application,

wherein the DMS device includes a processor coupled to a memory, and the memory is operative to store instructions executable on the processor to;

store user-entered data received from a user into the primary DMS database;

store secondary data received from the at least one sensor assembly into the secondary tracking database;

associate the secondary data with one or more events described by the user-entered data;

cross-check the user-entered data against the associated secondary data;

evaluate user-entered data for review based on the cross-checking results;

present the evaluated user-entered data for review;

treat the user-entered data in the primary DMS database based on review results; and

determine a diabetes management recommendation based on the treated user-entered data.

13. The system of claim 12, wherein the instruction to store user-entered data includes instructions to prompt the user for information regarding at least one of meal markers, exercise, medication, and sleep.

14. The system of claim 12, wherein the instruction to store secondary data includes instructions to receive data from a plurality of sensor assemblies.

15. The system of claim 12, wherein the instruction to store secondary data includes instructions to receive data from a DMS application generating secondary data from the primary DMS database based on one or more rules.

16. The system of claim 12, wherein the instruction to associate the secondary data with one or more events described by the user-entered data includes instructions to identify events and secondary events that occur proximate in time.

17. The system of claim 12, wherein the instruction to cross-check the user-entered data against the associated secondary data includes instructions to identify user-entered data that appear to be incorrect or inconsistent with the associated secondary data.

18. The system of claim 12, wherein the instruction to evaluate user-entered data includes instructions to assign states to the user-entered data based on the cross-checking results.

19. The system of claim 18, wherein the instruction to assign states includes instructions to assign a state of at least one of “

to be reviewed”

, “

suspect”

, “

unverified”

, “

verified”

, “

validated”

, and “

invalidated”

.

20. The system of claim 12, wherein the instruction to present evaluated user-entered data for review includes instructions to prompt the user to indicate if the user-entered data or the associated secondary data are more accurate.

21. The system of claim 12, wherein the instruction to treat user-entered data in the primary DMS database includes instructions to adjust a weight of the user-entered data based on review results.

22. The system of claim 12, wherein the instruction to determine a diabetes management recommendation based on the treated user-entered data includes instructions to factor in weights assigned to the updated user-entered data when evaluating the user-entered data.

23. A system for reducing impact of user-entered data errors in a data management system (DMS), the system comprising:

a DMS database storing user-entered data;

a source of non-user-entered data in communication with the DMS; and

an evaluation system to evaluate user-entered data relative to non-user-entered data,

wherein the source may include at least one of an internal database, one or more sensor assemblies, and one or more external data sources,

wherein the one or more sensor assemblies can include one or more sensors adapted to be worn on a user'"'"'s body, the sensor assemblies including a transceiver operable to transmit measured secondary data to a DMS device executing a DMS application wherein the DMS application is operative to store the secondary data in a secondary data tracking database, associate the stored secondary data with user-entered data in a primary DMS database, and cross-check the user-entered data against the secondary data to identify incorrect or inconsistent user-entered data for review.