Subcutaneous outpatient management

• US 9,892,234 B2
• Filed: 10/26/2015
• Issued: 02/13/2018
• Est. Priority Date: 10/27/2014
• Status: Active Grant

• Current Assignee: Aseko, Inc.
• Original Assignee: Aseko, Inc.
• Inventors: Booth, Robert C., Hebblewhite, Harry
• Primary Examiner(s): Riggs, II, Larry D
• Application Number:
  US14/922,763
• Publication Number:
  US 20160117481A1
• Time in Patent Office: 841 Days
• Field of Search: None
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/14503 invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors A61B5/1459, A61B5/1464, A61B5/1473, A61B5/1482, A61B5/14865 take precedence
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61M 2205/3303 Using a biosensor
• CPC Class Codes: A61M 5/1723 using feedback of body parameters, e.g. blood-sugar, pressure measurement of body parameters A61B5/00
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 20/60 relating to nutrition control, e.g. diets
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

A method of administering insulin includes receiving subcutaneous information for a patient at a computing device and executing a subcutaneous outpatient program for determining recommended insulin dosages. The subcutaneous outpatient program includes obtaining blood glucose data of the patient from a glucometer in communication with the computing device, aggregating blood glucose measurements to determine a representative aggregate blood glucose measurement associated with at least one scheduled blood glucose time interval, and determining a next recommended insulin dosage for the patient based on the representative aggregate blood glucose measurement and the subcutaneous information. The method also includes transmitting the next recommended insulin dosage to a portable device associated with the patient. The portable device displays the next recommended insulin dosage.

Claims

1. A method comprising:

receiving, at data processing hardware, subcutaneous information for a patient;

executing, at the data processing hardware, a subcutaneous outpatient program for determining recommended insulin dosages, the subcutaneous outpatient program comprising;

receiving, at the data processing hardware, sequential scheduled blood glucose time intervals throughout a day from a healthcare provider computing device in communication with the data processing hardware, each scheduled blood glucose time interval associated with a corresponding adjustable time boundary that does not overlap with other time boundaries associated with the other scheduled blood glucose time intervals;

obtaining, at the data processing hardware, blood glucose data of the patient from a glucometer in communication with the computing device, the blood glucose data including blood glucose measurements of the patient, blood glucose times associated with the blood glucose measurements, and insulin dosages administered by the patient and associated with the blood glucose measurements;

for each scheduled blood glucose time interval, aggregating, by the data processing hardware, the blood glucose measurements associated with the corresponding scheduled blood glucose time interval based on the blood glucose times to determine a corresponding representative aggregate blood glucose measurement associated with the corresponding scheduled blood glucose time interval;

determining, by the data processing hardware, a next recommended meal bolus for the patient during a selected time interval based on the representative aggregate blood glucose measurement associated with the scheduled blood glucose time interval that occurs immediately after the selected time interval and the subcutaneous information; and

transmitting the next recommended meal bolus to an administration device in communication with the data processing hardware, the administration device comprising;

a doser; and

an administration computing device in communication with the doser, the administration computing device configured to automatically dial in a number of units of insulin for the next recommended meal bolus and cause the doser to administer the number of units of insulin for the next recommended meal bolus.

2. The method of claim 1, further comprising transmitting the next recommended meal bolus from the data processing hardware to a portable device associated with the patient, the portable device displaying the next recommended meal bolus.

3. The method of claim 1, wherein obtaining the blood glucose data comprises one or more of:

receiving the blood glucose data from a remote computing device in communication with the data processing hardware during a batch download process, the remote computing device executing a download program for downloading the blood glucose data from the glucometer;

receiving the blood glucose data from the glucometer upon measuring the blood glucose measurement;

receiving the blood glucose data from a meter manufacturer computing device in communication with the data processing hardware during the batch download process, the meter manufacturer receiving the blood glucose data from the glucometer;

or

receiving the blood glucose data from a patient device in communication with the data processing hardware and the glucometer, the patient device receiving the blood glucose data from the glucometer.

4. The method of claim 1, further comprising:

aggregating, by the data processing hardware, one or more of the blood glucose measurements associated with a breakfast blood glucose time interval to determine a representative aggregate breakfast blood glucose measurement;

aggregating, by the data processing hardware, one or more of the blood glucose measurements associated with a midsleep blood glucose time interval to determine a representative aggregate midsleep blood glucose measurement;

selecting, by the data processing hardware, a governing blood glucose as a lesser one of the representative aggregate midsleep blood glucose measurement or the representative aggregate breakfast blood glucose measurement;

determining, by the data processing hardware, an adjustment factor for adjusting a next recommended basal dosage based on the selected governing blood glucose measurement;

obtaining, at the data processing hardware, a previous day recommended basal dosage; and

determining, by the data processing hardware, the next recommended basal dosage by multiplying the adjustment factor times the previous day recommended basal dosage.

5. The method of claim 1, further comprising:

aggregating, by the data processing hardware, one or more of the blood glucose measurements associated with a lunch blood glucose time interval to determine a representative aggregate lunch blood glucose measurement;

selecting, by the data processing hardware, a governing blood glucose as the representative aggregate lunch blood glucose measurement;

determining, by the data processing hardware, an adjustment factor for adjusting a next recommended breakfast bolus based on the selected governing blood glucose measurement;

obtaining, at the data processing hardware, a previous day recommended breakfast bolus; and

determining, by the data processing hardware, the next recommended breakfast bolus by multiplying the adjustment factor times the previous day recommended breakfast bolus.

6. The method of claim 1, further comprising:

aggregating, by the data processing hardware, one or more of the blood glucose measurements associated with a dinner blood glucose time interval to determine a representative aggregate dinner blood glucose measurement;

selecting, by the data processing hardware, a governing blood glucose as the representative aggregate dinner blood glucose measurement;

determining, by the data processing hardware, an adjustment factor for adjusting a next recommended lunch bolus based on the selected governing blood glucose measurement;

obtaining, at the data processing hardware, a previous day recommended lunch bolus; and

determining, by the data processing hardware, the next recommended lunch bolus by multiplying the adjustment factor times the previous day recommended lunch bolus.

7. The method of claim 1, further comprising:

aggregating, by the data processing hardware, one or more of the blood glucose measurements associated with a bedtime blood glucose time interval to determine a representative aggregate bedtime blood glucose measurement;

selecting, by the data processing hardware, a governing blood glucose as the representative aggregate bedtime blood glucose measurement;

determining, by the data processing hardware, an adjustment factor for adjusting a next recommended dinner bolus based on the selected governing blood glucose measurement;

obtaining, at the data processing hardware, a previous day recommended dinner bolus; and

determining, by the data processing hardware, the next recommended dinner bolus by multiplying the adjustment factor times the previous day recommended dinner bolus.

8. The method of claim 1, further comprising:

aggregating, by the data processing hardware, one or more of the blood glucose measurements associated with a selected one of the scheduled blood glucose time intervals to determine a representative aggregate blood glucose measurement associated with the selected scheduled blood glucose time interval;

selecting, by the data processing hardware, a governing blood glucose as the representative aggregate blood glucose measurement associated with the selected scheduled blood glucose time interval;

determining, by the data processing hardware, an adjustment factor for adjusting a next recommended carbohydrate-to-insulin ratio governed by the selected scheduled blood glucose time interval based on the selected governing blood glucose measurement;

obtaining, at the data processing hardware, a previous day recommended carbohydrate-to-insulin ratio governed by the selected scheduled blood glucose time interval; and

determining, by the data processing hardware, the next recommended carbohydrate-to-insulin ratio by multiplying the adjustment factor times the previous day recommended carbohydrate-to-insulin ratio.

9. The method of claim 8, wherein the selected scheduled blood glucose time interval includes one of a lunch blood glucose time interval, a dinner blood glucose time interval, or a bedtime blood glucose time interval.

10. The method of claim 1, wherein each scheduled blood glucose time interval correlates to an associated blood glucose type including one of a pre-breakfast blood glucose measurement, a pre-lunch blood glucose measurement, a pre-dinner blood glucose measurement, a bedtime blood glucose measurement and a midsleep blood glucose measurement.

11. The method of claim 10, further comprising:

determining, using the data processing hardware, the blood glucose type for each of the blood glucose measurements, the blood glucose type is tagged by the patient when measuring the blood glucose measurement.

12. The method of claim 1, wherein a portion of the scheduled blood glucose time intervals are associated with time intervals when the patient is consuming meals and a remaining portion of the scheduled blood glucose time intervals are associated with time intervals when the patient is not consuming meals.

13. The method of claim 1, further comprising:

receiving, at the data processing hardware, a specified date range from the remote healthcare provider computing device; and

aggregating, using the data processing hardware, one or more of the blood glucose measurements associated with at least one of the scheduled blood glucose time intervals and within the specified date range.

14. The method of claim 1, wherein the representative aggregate blood glucose measurement includes a mean blood glucose value for the associated scheduled blood glucose time interval.

15. The method of claim 1, wherein the representative aggregate blood glucose measurement includes a median blood glucose value for the associated scheduled blood glucose time interval.

16. A dosing controller comprising:

data processing hardware; and

memory hardware in communication with the data processing hardware, the memory hardware storing instructions for a subcutaneous outpatient program that when executed on the data processing hardware cause the data processing hardware to perform operations comprising;

receiving subcutaneous information for a patient;

receiving sequential scheduled blood glucose time intervals throughout a day from a healthcare provider computing device in communication with the data processing hardware, each scheduled blood glucose time interval associated with a corresponding adjustable time boundary that does not overlap with other time boundaries associated with the other scheduled blood glucose time intervals;

obtaining blood glucose data of the patient from a glucometer in communication with the data processing hardware, the blood glucose data including blood glucose measurements of the patient, blood glucose times associated with the blood glucose measurements, and insulin dosages administered by the patient and associated with the blood glucose measurements;

for each scheduled blood glucose time interval, aggregating the blood glucose measurements associated with the corresponding scheduled blood glucose time interval based on the blood glucose times to determine a corresponding representative aggregate blood glucose measurement associated with the corresponding scheduled blood glucose time interval;

determining a next recommended meal bolus for the patient during a selected time interval based on the representative aggregate blood glucose measurement associated with the scheduled blood glucose time interval that occurs immediately after the selected time interval and the subcutaneous information; and

transmitting the next recommended meal bolus to an administration device in communication with the data processing hardware, the administration device comprising;

a doser; and

an administration computing device in communication with the doser, the administration computing device configured to automatically dial in a number of units of insulin for the next recommended meal bolus and cause the doser to administer the number of units of insulin for the next recommended meal bolus.

17. The dosing controller of claim 16, wherein the operations further comprise transmitting the next recommended meal bolus from the data processing hardware to a portable device associated with the patient, the portable device displaying the next recommended meal bolus.

18. The dosing controller of claim 16, wherein obtaining the blood glucose data comprises one or more of:

receiving the blood glucose data from a remote computing device in communication with the dosing controller during a batch download process, the remote computing device executing a download program for downloading the blood glucose data from the glucometer;

receiving the blood glucose data from the glucometer upon measuring the blood glucose measurement;

receiving the blood glucose data from a meter manufacturer computing device in communication with the dosing controller during the batch download process, the meter manufacturer receiving the blood glucose data from the glucometer;

or

receiving the blood glucose data from a patient device in communication with the dosing controller and the glucometer, the patient device receiving the blood glucose data from the glucometer.

19. The dosing controller of claim 16, wherein the operations further comprise:

aggregating one or more of the blood glucose measurements associated with a breakfast blood glucose time interval to determine a representative aggregate breakfast blood glucose measurement;

aggregating one or more of the blood glucose measurements associated with a midsleep blood glucose time interval to determine a representative aggregate midsleep blood glucose measurement;

selecting a governing blood glucose as a lesser one of the representative aggregate midsleep blood glucose measurement or the representative aggregate breakfast blood glucose measurement;

determining an adjustment factor for adjusting a next recommended basal dosage based on the selected governing blood glucose measurement;

obtaining a previous day'"'"'s recommended basal dosage; and

determining the next recommended basal dosage by multiplying the adjustment factor times the previous day'"'"'s recommended basal dosage.

20. The dosing controller of claim 16, wherein the operations further comprise:

aggregating one or more of the blood glucose measurements associated with a lunch blood glucose time interval to determine a representative aggregate lunch blood glucose measurement;

selecting a governing blood glucose as the representative aggregate lunch blood glucose measurement;

determining an adjustment factor for adjusting a next recommended breakfast bolus based on the selected governing blood glucose measurement;

obtaining a previous day'"'"'s recommended breakfast bolus; and

determining the next recommended breakfast bolus by multiplying the adjustment factor times the previous day'"'"'s recommended breakfast bolus.

21. The dosing controller of claim 16, wherein the operations further comprise:

aggregating one or more of the blood glucose measurements associated with a dinner blood glucose time interval to determine a representative aggregate dinner blood glucose measurement;

selecting a governing blood glucose as the representative aggregate dinner blood glucose measurement;

determining an adjustment factor for adjusting a next recommended lunch bolus based on the selected governing blood glucose measurement;

obtaining a previous day'"'"'s recommended lunch bolus; and

determining the next recommended lunch bolus by multiplying the adjustment factor times the previous day'"'"'s recommended lunch bolus.

22. The dosing controller of claim 16, wherein the operations further comprise:

aggregating one or more of the blood glucose measurements associated with a bedtime blood glucose time interval to determine a representative aggregate bedtime blood glucose measurement;

selecting a governing blood glucose as the representative aggregate bedtime blood glucose measurement;

determining an adjustment factor for adjusting a next recommended dinner bolus based on the selected governing blood glucose measurement;

obtaining a previous day'"'"'s recommended dinner bolus; and

determining the next recommended dinner bolus by multiplying the adjustment factor times the previous day'"'"'s recommended dinner bolus.

23. The dosing controller of claim 16, wherein the operations further comprise:

aggregating one or more of the blood glucose measurements associated with a selected one of the scheduled blood glucose time intervals to determine a representative aggregate blood glucose measurement associated with the selected scheduled blood glucose time interval;

selecting a governing blood glucose as the representative aggregate blood glucose measurement associated with the selected scheduled blood glucose time interval;

determining an adjustment factor for adjusting a next recommended carbohydrate-to-insulin ratio governed by the selected scheduled blood glucose time interval based on the selected governing blood glucose measurement;

obtaining a previous day'"'"'s recommended carbohydrate-to-insulin ratio governed by the selected scheduled blood glucose time interval; and

determining the next recommended carbohydrate-to-insulin ratio by multiplying the adjustment factor times the previous day'"'"'s recommended carbohydrate-to-insulin ratio.

24. The dosing controller of claim 23, wherein the selected scheduled blood glucose time interval includes one of a lunch blood glucose time interval, a dinner blood glucose time interval, or a bedtime blood glucose time interval.

25. The dosing controller of claim 16, wherein each scheduled blood glucose time interval correlates to an associated blood glucose type including one of a pre-breakfast blood glucose measurement, a pre-lunch blood glucose measurement, a pre-dinner blood glucose measurement, a bedtime blood glucose measurement and a midsleep blood glucose measurement.

26. The dosing controller of claim 25, wherein the operations further comprise determining the blood glucose type for each of blood glucose measurement, the blood glucose type is tagged by the patient when measuring the blood glucose measurement.

27. The dosing controller of claim 16, wherein a portion of the scheduled blood glucose time intervals are associated with time intervals when the patient is consuming meals and a remaining portion of the scheduled blood glucose time intervals are associated with time intervals when the patient is not consuming meals.

28. The dosing controller of claim 16, wherein the operations further comprise:

receiving a specified date range from the remote healthcare provider computing device; and

aggregating one or more of the blood glucose measurements associated with at least one of the scheduled blood glucose time intervals and within the specified date range.

29. The dosing controller of claim 16, wherein the representative aggregate blood glucose measurement includes a mean blood glucose value for the associated scheduled blood glucose time interval.

30. The dosing controller of claim 16, wherein the representative aggregate blood glucose measurement includes a median blood glucose value for the associated scheduled blood glucose time interval.