SYSTEM FOR DETERMINING BASAL RATE PROFILES

• US 20090222247A1
• Filed: 02/28/2008
• Published: 09/03/2009
• Est. Priority Date: 02/28/2008
• Status: Abandoned Application

• Current Assignee: Roche Diabetes Care Inc. (Roche Holding AG)
• Original Assignee: Roche Diabetes Care Inc. (Roche Holding AG)
• Inventors: Van der Helm, Wim, Weinert, Stefan, Hellwig, Robert
• Application Number:
  US12/039,366
• Publication Number:
  US 20090222247A1
• Time in Patent Office: Days
• US Class Current: 703/11
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients

Abstract

A system and method are provided for generating a plurality of basal rate models that together model delivery of a corresponding plurality of basal rates of a diabetes treatment drug to a patient over a period of time. Information may be collected from a plurality of patients that have a diabetic condition and to which the diabetes treatment drug has been delivered. The collected information may include a glycemic control indicator for each of the plurality of patients that is indicative of an efficacy of the diabetes treatment drug in treating the patient'"'"'s diabetic condition. The collected information may be filtered based on the glycemic control indicators to produce a subset of information that includes information only for patients that exhibit acceptable glycemic control. The plurality of basal rate models may be generated based on the subset of the collected information, and may be stored in a memory unit.

Claims

1. A method of generating a plurality of basal rate models that together model delivery of a corresponding plurality of basal rates of a diabetes treatment drug to a patient over a period of time, the method comprising:

collecting information from a plurality of patients that have a diabetic condition and to which the diabetes treatment drug has been delivered, the collected information including a glycemic control indicator for each of the plurality of patients that is indicative of an efficacy of the diabetes treatment drug in treating the patient'"'"'s diabetic condition,

filtering the collected information based on the glycemic control indicators to produce a subset of the collected information that includes information only for patients that exhibit acceptable glycemic control,

generating the plurality of basal rate models based on the subset of the collected information, and

storing the generated plurality of basal rate models in a memory unit.

2. The method of claim 1 wherein the collected information includes values of the basal rates of the diabetes treatment drug delivered to each of the plurality of patients over the period of time,

and wherein generating the plurality of basal rate models comprises generating the plurality of basal rate models based, at least in part, on the values of the plurality of basal rates of the diabetes treatment drug delivered to each of the plurality of patients in the subset of the collected information.

3. The method of claim 1 wherein the collected information includes a plurality of categorical patient parameters for each of the plurality of patients, each of the plurality of categorical patient parameters for each of the plurality of patients having one of two or more possible values or ranges,

and wherein the method further comprises partitioning the subset of the collected information into a number of different patient information subgroups each identified by a different combination of the two or more possible values or ranges of at least two of the plurality of categorical patient parameters,

and wherein generating the plurality of basal rate models comprises generating the plurality of basal rate models based on at least one of the number of different patient information subgroups.

4. The method of claim 3 further comprising:

generating a number of sets of basal rate models, each of the number of sets of basal rate models comprising a plurality of basal rate models that are generated based on a different one of the number of different patient information subgroups, and

storing each of the generated number of sets of basal rate models in the memory unit.

5. The method of claim 1 wherein the collected information comprises a plurality of patient records each for a different one of the plurality of patients, each of the plurality of patient records including a reference time within the period of time and a basal rate profile defining a plurality of basal rates of the diabetes treatment drug sequentially delivered to the corresponding patient over the period of time beginning with a first basal rate and ending with a last basal rate,

and wherein the method further comprises aligning the basal rate profiles in the plurality of patient records as functions of the reference times such that in each of the plurality of patient records the first basal rate of the corresponding basal rate profile begins at the corresponding reference time,

and wherein filtering the collected information comprises filtering the collected information after aligning the basal rate profiles in the plurality of patient records.

6. A method of generating a plurality of basal rate models that together model delivery of a corresponding plurality of basal rates of a diabetes treatment drug to a patient over a period of time, the method comprising:

collecting information from a plurality of patients to which the diabetes treatment drug has been delivered, the collected patient information including a plurality of categorical patient parameters for each of the plurality of patients, each of the plurality of categorical patient parameters for each of the plurality of patients having one of two or more possible values or ranges,

partitioning the collected information into a number of different patient information subgroups each identified by a different combination of the two or more possible values or ranges of at least two of the plurality of categorical patient parameters,

generating the plurality of basal rate models based on the collected information in at least one of the number of different patient information subgroups, and

storing the generated plurality of basal rate models in a memory unit.

7. The method of claim 6 further comprising generating a number of sets of the plurality of basal rate models each based on the collected information in a different one of the number of different patient information subgroups.

8. The method of claim 7 further comprising storing the generated number of sets of the plurality of basal rate models in the memory unit.

9. The method of claim 6 wherein the collected information includes a plurality of medical condition indicators each indicative of a medical condition of a different one of the plurality of patients,

and wherein the method further comprises filtering the collected information based on the plurality of medical condition indicators to produce a subset of the collected information that includes patient information only for patients for which the corresponding medical condition is acceptable.

10. The method of claim 9 wherein partitioning the collected information into a number of different patient information subgroups comprises partitioning the collected information from the subset of the collected information into the number of different patient subgroups.

11. A method of generating a plurality of basal rate models that together model a basal rate profile defining a corresponding plurality of basal rates of a diabetes treatment drug sequentially delivered to a patient over a period of time beginning with a first basal rate and ending with a last basal rate, the method comprising:

collecting information in the form of a plurality of patient records each for a different patient to which the diabetes treatment drug has been delivered, each of the plurality of patient records including a reference time within the period of time and a basal rate profile that are specific to the corresponding patient,

aligning the basal rate profiles in the plurality of patient records as functions of the reference times such that in each of the plurality of patient records the first basal rate of the corresponding basal rate profile begins at the corresponding reference time,

generating the plurality of basal rate models based on the patient records having aligned basal rate profiles, and

storing the generated plurality of basal rate models in a memory unit.

12. The method of claim 11 wherein the reference time in each of the plurality of patient records is a time within the period of time that the corresponding patient normally falls asleep.

13. The method of claim 11 wherein each of the plurality of patient records further includes a start time that corresponds to a time within the period of time that the first basal rate of the corresponding basal rate profile normally begins,

and wherein aligning the basal rate profiles further comprises aligning the basal rate profiles in the plurality of patient records further as functions of the start times such that in each of the patient records the first basal rate of the corresponding basal rate profile begins at the corresponding reference time regardless of the corresponding start time.

14. The method of claim 13 wherein the reference time in each of the plurality of patient records is a time within the period of time that the corresponding patient normally falls asleep.

15. The method of claim 14 wherein the period of time is twenty four hours in duration,

and wherein the basal rate profile in each of the plurality of patient records comprises twenty four basal rates each having a time duration of one hour.

16. A method of determining a set of basal rate models that define delivery of a diabetes treatment drug to a particular patient over a period of time, the method comprising:

collecting information from a plurality of patients to which the diabetes treatment drug has been delivered,

generating a number of sets of basal rate models based on the information collected from the plurality of patients,

collecting information that is specific to the particular patient,

determining the set of basal rate models for the particular patient based on the number of sets of basal rate models and on the collected information that is specific to the particular patient, and

storing the determined set of basal rate models for the particular patient in a memory unit.

17. The method of claim 16 wherein the information collected from the plurality of patients includes a plurality of categorical patient parameters for each of the plurality of patients,

and wherein the method further comprises partitioning the information collected from the plurality of patients into a number of different patient information subgroups each identified by a different combination of the plurality of categorical patient parameters,

and wherein generating the number of sets of basal rate models comprises generating each of the number of sets of basal rate models based on a different one of the number of different patient information subgroups.

18. The method of claim 17 wherein collecting information that is specific to the particular patient comprises collecting the plurality of categorical patient parameters for the particular patient,

and wherein determining the set of basal rate models for the particular patient comprises selecting from the number of sets of basal rate models a set of basal rate models that was based on a plurality of the categorical patient parameters that most closely matches the plurality of categorical patient parameters for the particular patient.

19. The method of claim 18 wherein generating a number of sets of basal rate models based on the information collected from the plurality of patients is carried out on a first electronic device or system,

and wherein collecting information that is specific to the particular patient and determining the set of basal rate models for the particular patient are carried out on a second electronic device that is remote from the first electronic device or system,

and wherein storing the determined set of basal rate models for the particular patient comprises storing the determined set of basal rate models for the particular patient in a memory unit of the second electronic device.

20. The method of claim 16 further comprising delivering the diabetes treatment drug to the particular patient according to the set of basal rate models for the particular patient over successive time periods each having duration equal to the period of time.

21. A method of generating a basal rate profile that defines delivery of a plurality of basal rates of a diabetes treatment drug to a particular patient over a period of time, the method comprising:

collecting information from a plurality of patients to which the diabetes treatment drug has been delivered,

generating a plurality of basal rate model sets based on the information collected from the plurality of patients, each of the plurality of basal rate model sets modeling delivery of a different plurality of basal rates of the diabetes treatment drug to a patient over the period of time,

collecting a first set of information that is specific to the particular patient,

selecting one of the plurality of basal rate model sets based on the first set of information that is specific to the particular patient,

collecting a second set of information that is specific to the particular patient,

generating the basal rate profile based on the selected one of the plurality of basal rate model sets and on the second set of information that is specific to the particular patient, and

storing the generated basal rate profile in a memory unit.

22. The method of claim 21 wherein the information collected from the plurality of patients includes a plurality of categorical patient parameters for each of the plurality of patients,

and wherein the method further comprises partitioning the information collected from the plurality of patients into a number of different patient information subgroups each identified by a different combination of the plurality of categorical patient parameters,

and wherein generating the plurality of basal rate model sets comprises generating each of the plurality of basal rate model sets based on a different one of the number of different patient information subgroups,

and wherein collecting a first set of information that is specific to the particular patient comprises collecting the plurality of categorical patient parameters for the particular patient,

and wherein selecting one of the plurality of basal rate model sets based on the first set of information that is specific to the particular patient comprises selecting from the plurality of basal rate model sets the one of the plurality of basal rate model sets that was based on a plurality of the categorical patient parameters that most closely matches the plurality of categorical patient parameters for the particular patient.

23. The method of claim 22 wherein collecting a second set of information that is specific to the particular patient comprises collecting a number of independent variables that are specific to the particular patient,

and wherein generating the basal rate profile comprises computing a plurality of basal rates of the diabetes treatment drug to be sequentially delivered to the particular patient over successive time periods each having duration equal to the period of time, each of the plurality of basal rates of the diabetes treatment drug based on a different basal rate model of the selected one of the plurality of basal rate model sets and on the number of independent variables that are specific to the particular patient.

24. The method of claim 23 further comprising sequentially delivering the plurality of basal rates of the diabetes treatment drug to the particular patient over each of the successive time periods.

25. The method of claim 21 wherein generating a plurality of basal rate model sets based on the information collected from the plurality of patients is carried out on a first electronic device or system,

and wherein collecting the first set of information, selecting the one of the plurality of basal rate model sets, collecting the second set of information and generating the basal rate profile are carried out on a second electronic device that is remote from the first electronic device or system,

and wherein storing the generated basal rate profile comprises storing the generated basal rate profile in a memory unit of the second electronic device.