Method and System for Self-Management of a Disease

• US 20090036828A1
• Filed: 10/06/2005
• Published: 02/05/2009
• Est. Priority Date: 10/07/2004
• Status: Active Grant

• Current Assignee: Novo Nordisk A/S
• Original Assignee: Novo Nordisk A/S
• Inventors: Thodberg, Hans Henrik, Hansen, Jon Ulrich, Poulsen, Radisch Ulrik Detlef, Kirstensen, Jorgen Smedegaard, Poulsen, Knud, Randlov, Jette, Kristensen, Leif Engmann, Poulsen, Jens Ulrik
• Granted Patent: US 9,501,949 B2
• Time in Patent Office: Days
• US Class Current: 604/66
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: G09B 19/00 Teaching not covered by other main groups of this subclass teaching or practice apparatus for gun-aiming or gun-laying F41G3/26
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 20/70 relating to mental therapies, e.g. psychological therapy or autogenous training
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

The present specification discloses a method, system and program product that can be used for self-management of any chronic disease. The invention involves the use of a device to enter patient'"'"'s disease related data. Based on this data patient'"'"'s habits are detected and presented in a graphical format. The user also has the option of setting up a reminder based on the detected habits.

Claims

1. A method of assisting a user in the self-management of a physiological condition, the method comprising

obtaining data about occurrences of at least a first type of user actions;

detecting a user habit from the obtained data; and

generating a reminder data item from the detected user habit.

2. A method according to claim 1, further comprising storing the generated reminder data item in a device to be carried by the user.

3. A method according to claim 2, wherein the device is one of a blood glucose measuring device and an insulin administration device.

4. A method according to claim 1, wherein the reminder data item comprises a time interval during which the user action is to be performed.

5. A method according to claim 1, wherein the user action comprises one of a blood glucose measurement, a meal intake, physical exercise, and a medication.

6. A method according to claim 1, wherein detecting the user habit includes graphically presenting a representation of the obtained data.

7. A method according to claim 6, wherein said graphical representation includes at least one of a histogram, a line graph and a bar graph.

8. A method according to claim 1, wherein detecting a user habit comprises determining a distribution of occurrences of the first type of user actions over a predetermined period of time.

9. A method according to claim 8, wherein detecting a user habit further comprises at least one of a sliding window operation, a Gaussian smearing, and an area integration of the determined distribution.

10. A method according to claim 1, wherein detecting the user habit includes detecting a time interval during which said first type of user actions typically occurs.

11. A method according to claim 1, wherein the first type of user action includes an intake of a medicament, and wherein detecting the user habit/habitual pattern includes detecting a typical dose interval of the medicament.

12. A method according to claim 11, wherein detecting the user habit comprises

determining a time of day and a dose of each medication intake;

determining respective numbers of medication intakes within a plurality of time intervals and with a dose within a predetermined dose interval to obtain a distribution of medication intakes as function of time of day and of dose; and

determining a combination of a time interval and a dose interval as a maximum of said distribution.

13. A method according to claim 11, wherein reminder data item comprises a time constraint and a dose constraint for a medication to be taken by a user;

and wherein the method further comprises

receiving an indication of a medication event, if any, said indication comprising time and dose information about a medication taken by the user;

issuing a reminder if no indication about at least one medication event complying with both the time constraint and the dose constraint of the reminder data item is received.

14. A method according claim 1, wherein generating a reminder data item comprises

presenting at least one suggested parameter of the reminder data item to the user;

and

providing editing means allowing the user to edit the suggested parameter.

15. A method according to claim 1, wherein detecting the user habit comprises

determining a time of day of each of the occurrences of the first type of user actions;

determining respective numbers of said occurrences within a plurality of time intervals; and

determining one of said time intervals as corresponding to a largest number of occurrences.

16. A method according to claim 1, wherein detecting the user habit comprises

determining a time of day of each of the occurrences of the first type of user actions;

generating a predetermined distribution function around each occurrence;

combining the generated distribution functions to obtain a combined distribution functions; and

determine a user habit as a maximum of the combined distribution function.

17. A method according to claim 16, wherein the predetermined distribution function is a Gaussian distribution function.

18. A method according to claim 1, wherein the reminder data item comprises a time interval of a modal day during which a user should take an action of the first type;

and wherein the method further comprises

receiving an indication when a user action of the first type has occurred;

issuing a reminder if no indication about an occurred user action has been received within said time interval.

19. A method according to claim 1, wherein the physiological condition is a chronicle disease.

20. A method according to claim 1, wherein the physiological condition is diabetes.

27. A computer program product comprising program code means adapted to cause, when loaded into a data processing device, the data processing device to perform the method according to claim 1.

21. A system for assisting a user in the self-management of a physiological condition, the system comprising input means for obtaining data about occurrences of at least a first type if user actions;

and processing means adapted to detect a user habit from the obtained data, and to generate a reminder data item from the detected user habit.

22. A system according to claim 21, comprising a user device including the input means and means for issuing a reminder based on the reminder data item.

23. A system according to claim 22, wherein the user device further comprises the processing means.

24. A system according to claim 22, wherein the user device is one of a blood glucose measuring device and an insulin administration device.

25. A system according to claim 22, wherein the user device is a suitably programmed general-purpose data processing device.

26. A system according to claim 22, further comprising a data processing device separate from the user device, the data processing device comprising the processing means and means for communicating the generated reminder data item to the user device.

28. Method of assisting a user in the self-management of a physiological condition, the method comprising

providing a medication reminder data item, the medication reminder data item comprising a time constraint and a dose constraint for a medication to be taken by a user;

receiving an indication of a medication event, if any, said indication comprising time and dose information about a medication taken by the user;

issuing a reminder if no indication about at least one medication event complying with both the time constraint and the dose constraint of the reminder data item is received.

29. A method according to claim 28, further comprising

obtaining data about occurrences of medication events by the user;

detecting a user habit from the obtained data; and

generating the medication reminder data item from the detected user habit.

30. A method according to claim 29, wherein detecting the user habit includes detecting a time interval during which said medication events typically occur and detecting a typical dose interval of the medicament for each medication event.

31. A method according to claim 30, wherein detecting the user habit comprises

determining a time of day and a dose of each medication intake;

determining respective numbers of medication intakes within a plurality of time intervals and with a dose within a predetermined dose interval to obtain a distribution of medication intakes as function of time of day and of dose; and

determining a combination of a time interval and a dose interval as a maximum of said distribution.

32. A method according to claim 29, wherein detecting the user habit comprises

determining a time of day of each of the medication events;

determining a number of said medication events within a plurality of time intervals; and

determining one of said time intervals as corresponding to a largest number of medication events.

33. A method according to claim 29, wherein detecting the user habit comprises

determining a time of day of each of the occurrences of the medication events;

generating a predetermined distribution function around each occurrence;

combining the generated distribution functions to obtain a combined distribution functions; and

determine a user habit as a maximum of the combined distribution function.

34. A method according to claim 33, wherein the predetermined distribution function is a Gaussian distribution function.

35. A method according to claim 28, further comprising storing the generated medication reminder data item in a device to be carried by the user.

36. A method according to claim 35, wherein the device is one of a blood glucose measuring device and an insulin administration device.

37. A method according to claim 28, wherein the medication reminder data item comprises a time interval during which the medication event is to be performed and a dose interval of a dose of a medicament to be applied during said medication event.

38. A method according to claim 28, wherein the medication event is an insulin medication.

39. A method according to claim 28, wherein providing a reminder data item comprises

presenting at least one suggested parameter of the reminder data item to the user;

and

providing editing means allowing the user to edit the suggested parameter.

40. A method according to claim 28, wherein the reminder data item comprises a time interval of a modal day during which a user should take medication;

and wherein the method further comprises

receiving an indication when a medication event has occurred;

issuing a reminder if no indication about an occurred medication event has been received within said time interval.

41. A method according to claim 28, wherein the physiological condition is a chronicle disease.

42. A method according to claim 28, wherein the physiological condition is diabetes.

46. A computer program product comprising program code means adapted to cause, when loaded into a data processing device, the data processing device to perform the method according to claim 28.

43. A user device for assisting a user in the self-management of a physiological condition, the system comprising

input means for receiving an indication of a medication event, if any, said indication comprising time and dose information about a medication taken by the user;

storage means for storing a medication reminder data item, the medication reminder data item comprising a time constraint and a dose constraint for a medication to be taken by a user; and

processing means adapted to issue a reminder if no indication about at least one medication event complying with both the time constraint and the dose constraint of the reminder data item is received.

44. A device according to claim 43, wherein the device is one of a blood glucose measuring device and an insulin administration device.

45. A device according to claim 43, wherein the device is a suitably programmed general-purpose data processing device.