Method and system for self-management of a disease

• US 9,501,949 B2
• Filed: 10/06/2005
• Issued: 11/22/2016
• Est. Priority Date: 10/07/2004
• Status: Active Grant

• Current Assignee: Novo Nordisk A/S
• Original Assignee: Novo Nordisk A/S
• Inventors: Poulsen, Knud, Smedegaard, Jorgen Slot, Hansen, Jon Ulrich, Kristensen, Leif Engmann, Randlov, Jette, Poulsen, Radisch Ulrik Detlef, Poulsen, Jens Ulrik, Thodberg, Hans Henrik
• Primary Examiner(s): CANELLA, KAREN A
• Application Number:
  US11/664,561
• Publication Number:
  US 20090036828A1
• Time in Patent Office: 4,065 Days
• Field of Search: 600/365
• US Class Current: 1/1
• 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 diabetes, 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, and

storing the generated reminder data item in a device to be carried by the user said device is one of a blood glucose measuring device and an insulin administration device,

wherein detecting a user habit comprises determining a distribution of occurrences of said first type of user actions over a predetermined period of time and detecting a time interval during which said first type of user actions typically occurs.

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

3. 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.

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

5. A method according to claim 4, wherein said graphical representation includes at least one of a histogram, a line graph and a bar graph.

6. A method according to claim 1, 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.

7. 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.

8. A method according to claim 7, 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.

9. A method according to claim 7 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.

10. 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.

11. 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.

12. 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.

13. A method according to claim 12, wherein the predetermined distribution function is a Gaussian distribution function.

14. 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.