Means and method for improved glycemic control for diabetic patients

• US 9,965,596 B2
• Filed: 08/15/2017
• Issued: 05/08/2018
• Est. Priority Date: 09/11/2012
• Status: Active Grant

• Current Assignee: Aseko, Inc.
• Original Assignee: Aseko, Inc.
• Inventors: Booth, Robert C., Fischell, Robert E.
• Primary Examiner(s): Kanaan, Maroun P
• Application Number:
  US15/677,397
• Publication Number:
  US 20170344725A1
• Time in Patent Office: 266 Days
• CPC Class Codes: A61B 2562/0295 Strip shaped analyte sensors for apparatus classified in A61B5/145 or A61B5/157 disposable multilayered or laminated electrodes G01N27/307; details of handling chemical test elements G01N33/4875
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• 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: G06F 3/04847 Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• 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: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 80/00 ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

A glycemic control system includes a physician processor, remote processor, and a portable telephone having a data input mechanism, a display, and an internal processor for bi-directional communication with the physician'"'"'s processor and the remote processor. A patient inputs data to the internal processor responsive to input from the physician'"'"'s processor and then transmits the information to the remote processor where an optimized number of units to be administered is sent back and displayed on the portable telephone.

Claims

1. A method comprising:

obtaining, by data processing hardware, a target blood glucose range defined by upper and lower blood glucose limits for a patient from memory hardware;

receiving, at the data processing hardware, a current blood glucose measurement of the patient and current patient condition parameters during a pre-meal time from a user device controlled by the patient and in communication with the data processing hardware, the current patient condition parameters comprising a number of carbohydrates consumed by the patient and an exercise parameter for the patient, and the pre-meal time associated with a meal type corresponding to one of breakfast, lunch, or dinner, wherein the user device is configured to;

receive, in a user interface executing on the user device, inputs from the patient for each patient condition parameter; and

transmit the current patient condition parameters from the user device to the data processing hardware;

determining, by the data processing hardware, whether the current blood glucose measurement is less than a midpoint of the target blood glucose range for the patient;

when the current blood glucose measurement is less than the midpoint of the target blood glucose range for the patient;

determining, by the data processing hardware, carbohydrate intake instructions for the patient including a predetermined number of carbohydrates for the patient to ingest based on the exercise parameter; and

transmitting the carbohydrate intake instructions to the user device, the carbohydrate intake instructions when received by the user device, causing the user interface executing on the user device to display the predetermined amount of carbohydrates for the patient to ingest;

determining, by the data processing hardware, a recommended meal bolus based on the number of carbohydrates consumed by the patient for the associated meal type;

obtaining, by the data processing hardware, previous patient condition parameters and a previous dosage of insulin administered by the patient for the associated meal type from the memory hardware, the previous patient condition parameters comprising a previous exercise parameter substantially equal to the exercise parameter associated with the current patient condition parameters;

obtaining, by the data processing hardware, a previous next scheduled blood glucose measurement from the memory hardware, the previous next scheduled blood glucose measurement resulting from the previous dosage of insulin administered by the patient;

determining whether the previous next scheduled blood glucose measurement is less than a hypoglycemia blood glucose limit for the patient;

when the previous next scheduled blood glucose measurement is less than the hypoglycemia blood glucose limit, determining, by the data processing hardware, a reduced insulin dosage value to prevent a next scheduled blood glucose measurement from falling below the hypoglycemia blood glucose limit;

subtracting, by the data processing hardware, the reduced insulin dosage value from the recommended meal bolus to determine a recommended dosage of insulin for the patient to administer; and

transmitting the recommended dosage of insulin from the data processing hardware to the user device, the recommended dosage of insulin, when received by the user device, causing the user interface to display the recommended dosage of insulin.

2. The method of claim 1, wherein the exercise parameter comprises a duration and/or severity of an exercise planned by the patient or recently completed by the patient.

3. The method of claim 2, wherein determining the carbohydrate intake instructions including the predetermined number of carbohydrates comprises determining the predetermined number of carbohydrates for the patient to ingest based on the duration of the exercise.

4. The method of claim 2, wherein determining the carbohydrate intake instructions including the predetermined number of carbohydrates comprises determining the predetermined number of carbohydrates for the patient to ingest based on the severity of the exercise.

5. The method of claim 2, wherein determining the carbohydrate intake instructions including the predetermined number of carbohydrates comprises determining the predetermined number of carbohydrates for the patient to ingest based on the duration and the severity of the exercise.

6. The method of claim 1, wherein the target blood glucose range is inputted to the memory hardware by a medical professional computing device associated with an authorized medical professional.

7. The method of claim 1, further comprising, storing, by the data processing hardware, the recommended dosage of insulin and the current patient condition parameters in the memory hardware.

8. The method of claim 1, wherein determining the recommended meal bolus comprises:

obtaining a carbohydrate-to-insulin ratio for the patient from the memory hardware, the carbohydrate-to-insulin ratio input to the memory hardware by a medical professional computing device associated with an authorized medical professional; and

dividing the number of carbohydrates consumed by the patient by the carbohydrate-to-insulin ratio to determine the recommended meal bolus.

9. The method of claim 8, wherein the carbohydrate-to-insulin ratio is calculated as follows:

CIR=450×

TDD

wherein CIR is the carbohydrate-to-insulin ratio and TDD is a total prescribed daily dose of insulin for the patient based on a weight of the patient.

10. The method of claim 1, further comprising:

obtaining, by the data processing hardware, an insulin sensitivity factor for the patient from the memory hardware, the insulin sensitivity factor inputted to the memory hardware by a medical professional computing device associated with an authorized medical professional;

determining, by the data processing hardware, whether the current blood glucose measurement exceeds the midpoint of the target blood glucose range for the patient; and

when the current blood glucose measurement exceeds the midpoint of the target blood glucose range for the patient;

determining, by the data processing hardware, a correction dose based on a function of the current blood glucose measurement, the mid-point of the target blood glucose range and the insulin sensitivity factor; and

transmitting the correction dose from the data processing hardware to the user device, the correction dose, when received by the user device, causing the user interface executing on the user device to display the correction dose.

11. The method of claim 1, wherein the user device is configured to:

receive the current blood glucose measurement from a blood glucose meter in communication with the user device; and

transmit the current blood glucose measurement of the patient to the data processing hardware.

12. The method of claim 1, wherein the user device is configured to:

receive, in the user interface, a blood glucose input from the patient indicating the current blood glucose measurement; and

transmit the current blood glucose measurement of the patient to the data processing hardware.

13. A system comprising:

a user device controlled by a patient and having a screen, the user device configured to;

display the user interface on the screen; and

receive, in the user interface displayed on the screen, inputs from the patient for patient condition parameters during a pre-meal time, the patient condition parameters comprising a number of carbohydrates consumed by the patient and an exercise parameter for the patient, and the pre-meal time associated with a meal type corresponding to one of breakfast, lunch, or dinner; and

data processing hardware in communication with the user device, the data processing hardware configured to perform operations comprising;

obtaining a target blood glucose range defined by upper and lower blood glucose limits for the patient from memory hardware in communication with the data processing hardware;

receiving a current blood glucose measurement of the patient during the pre-meal time from the user device;

receiving the patient condition parameters input to the user interface during the pre-meal time from the user device;

determining whether the blood glucose measurement is less than a midpoint of the target blood glucose range for the patient; and

when the current blood glucose measurement is less than the midpoint of the target blood glucose range for the patient;

determining carbohydrate intake instructions for the patient including a predetermined number of carbohydrates for the patient to ingest based on the exercise parameter; and

transmitting the carbohydrate intake instructions to the user device, the carbohydrate intake instructions when received by the user device, causing the user interface executing on the user device to display the predetermined amount of carbohydrates for the patient to ingest;

determining a recommended meal bolus based on the number of carbohydrates consumed by the patient for the associated meal type;

obtaining previous patient condition parameters and a previous dosage of insulin administered by the patient for the associated meal type from the memory hardware, the previous patient condition parameters comprising a previous exercise parameter substantially equal to the exercise parameter associated with the current patient condition parameters;

obtaining a previous next scheduled blood glucose measurement from the memory hardware, the previous next scheduled blood glucose measurement resulting from the previous dosage of insulin administered by the patient;

determining whether the previous next scheduled blood glucose measurement is less than a hypoglycemia blood glucose limit for the patient;

when the previous next scheduled blood glucose measurement is less than the hypoglycemia blood glucose limit, determining a reduced insulin dosage value to prevent a next scheduled blood glucose measurement from falling below the hypoglycemia blood glucose limit;

subtracting the reduced insulin dosage value from the recommended meal bolus to determine a recommended dosage of insulin for the patient to administer; and

transmitting the recommended dosage of insulin from the data processing hardware to the user device, the recommended dosage of insulin, when received by the user device, causing the user interface to display the recommended dosage of insulin.

14. The system of claim 13, wherein the exercise parameter comprises a duration and/or severity of an exercise planned by the patient or recently completed by the patient.

15. The system of claim 14, wherein determining the carbohydrate intake instructions including the predetermined number of carbohydrates comprises determining the predetermined number of carbohydrates for the patient to ingest based on the duration of the exercise.

16. The system of claim 14, wherein determining the carbohydrate intake instructions including the predetermined number of carbohydrates comprises determining the predetermined number of carbohydrates for the patient to ingest based on the severity of the exercise.

17. The system of claim 14, wherein determining the carbohydrate intake instructions including the predetermined number of carbohydrates comprises determining the predetermined number of carbohydrates for the patient to ingest based on the duration and the severity of the exercise.

18. The system of claim 13, further comprising a medical professional computing device associated with an authorized medical professional, the medical professional computing device configured to input the target blood glucose range to the memory hardware.

19. The system of claim 13, wherein the operations further comprise storing the recommended dosage of insulin and the current patient condition parameters in the memory hardware.

20. The system of claim 13, wherein determining the recommended meal bolus comprises:

obtaining a carbohydrate-to-insulin ratio for the patient from the memory hardware, the carbohydrate-to-insulin ratio input to the memory hardware by a medical professional computing device associated with an authorized medical professional; and

dividing the number of carbohydrates consumed by the patient by the carbohydrate-to-insulin ratio to determine the recommended meal bolus.

21. The system of claim 20, wherein the carbohydrate-to-insulin ratio is calculated as follows:

CIR=450×

TDD

wherein CIR is the carbohydrate-to-insulin ratio and TDD is a total prescribed daily dose of insulin for the patient based on a weight of the patient.

22. The system of claim 13, wherein the operations further comprise:

obtaining an insulin sensitivity factor for the patient from the memory hardware, the insulin sensitivity factor inputted to the memory hardware by a medical professional computing device associated with an authorized medical professional;

determining whether the current blood glucose measurement exceeds the midpoint of the target blood glucose range for the patient; and

when the current blood glucose measurement exceeds the midpoint of the target blood glucose range for the patient;

determining a correction dose based on a function of the current blood glucose measurement, the mid-point of the target blood glucose range and the insulin sensitivity factor; and

transmitting the correction dose from the data processing hardware to the user device, the correction dose, when received by the user device, causing the user interface executing on the user device to display the correction dose.

23. The system of claim 13, further comprising a blood glucose meter in communication with the user device and configured to measure blood glucose measurements of the patient, wherein the user device is configured to:

receive the current blood glucose measurement from the blood glucose meter; and

transmit the current blood glucose measurement of the patient to the data processing hardware.

24. The system of claim 13, wherein the user device is configured to:

receive, in the user interface, a blood glucose input from the patient indicating the current blood glucose measurement; and

transmit the current blood glucose measurement of the patient to the data processing hardware.