Systems and methods for disease control and management

• US 9,754,077 B2
• Filed: 02/21/2008
• Issued: 09/05/2017
• Est. Priority Date: 02/22/2007
• Status: Active Grant

• Current Assignee: WellDoc, Inc
• Original Assignee: WellDoc, Inc
• Inventors: Sysko, Ryan A., Sysko, Suzanne K., Minor, James M., Iyer, Anand, Fletcher, Andrew
• Primary Examiner(s): Hunter, Sean K
• Application Number:
  US12/071,486
• Publication Number:
  US 20080306770A1
• Time in Patent Office: 3,484 Days
• Field of Search: 705 2, 705 3, 705 4
• 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 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16H 70/20 relating to practices or guidelines

Abstract

Methods, computer-readable media, and systems for providing disease management. In one implementation, a system develops a treatment recommendation for a patient based on patient data. The system may receive patient data, execute a basic model of the physiological system of the patient to generate a modified model for the patient based on the patient data, perform a statistical analysis of the patient data to detect data excursions of the parameter values; use the modified model to determine factors causing the data excursions; and use the model to develop a treatment recommendation to ameliorate negative effects of the disease.

Claims

1. A system for management of a patient having a disease, comprising:

an input device for receiving patient data;

a transmitter for transmitting the received patient data from the input device; and

a disease management server, comprising;

a receiver for receiving the transmitted patient data;

a processor for;

executing a basic model of a physiological system of the patient to generate a modified model for the patient based on the patient data, wherein the basic model comprises determining a rate of change in blood glucose level of the patient over a time interval based on food intake, insulin concentration in blood, and blood glucose inventory;

performing a statistical analysis of the patient data to detect data excursions of values of first parameters of the physiological system;

using the modified model to estimate an effect of the data excursions on second parameters of the physiological system;

using the modified model to determine factors causing the data excursions; and

using the modified model to develop a treatment recommendation to ameliorate negative effects of the disease; and

an output device for outputting the treatment recommendation.

2. The system of claim 1, wherein the patient data comprises values of parameters including at least one of:

(a) patient carbohydrate intake,

(b) patient medication doses,

(c) blood glucose level, or

(d) corresponding time for the patient data.

3. The system of claim 1, wherein the processor generates a treatment recommendation comprising at least one of a recommendation for dosing and timing of medication, and a recommendation for patient dietary behavior.

4. The system of claim 1, wherein executing the basic model comprises applying an algorithm to the patient data in a current state in conjunction with auxiliary patient data comprising at least one of patient blood lipid level, blood pressure, age, gender, height and weight, and race.

5. The system of claim 1, wherein the processor is further configured to develop recommendations for collection of the patient data to improve the basic model, wherein the recommendations for collection comprise recommendations for timing of blood glucose measurement.

6. The system of claim 1, wherein using the modified model to develop a treatment recommendation comprises using the modified model to develop a plurality of treatment recommendations at predetermined intervals.

7. The system of claim 6, wherein the intervals are determined based on a most-recent patient data collection time.

8. The system of claim 1, wherein the processor is further configured for performing the statistical analysis employing a statistical design of experiments methodology to identify the factors causing the data excursions.

9. The system of claim 1, wherein the treatment recommendation comprises a recommended time and dose of medication, including recommended combinations of available medications.

10. The system of claim 1, wherein the treatment recommendation comprises a recommended time and amount of carbohydrate intake.

11. The system of claim 1, wherein the input device is a patient-interactive interface operated by the patient.

12. The system of claim 11, further comprising a portable device configured to operate the patient-interactive interface and the transmitter, wherein the transmitter transmits signals over a wireless communication to the disease management server.

13. The system of claim 12, further comprising a physician interface operable to receive information about the patient from the disease management server.

14. The system of claim 1, wherein the patient data is calibrated at a plurality of reading points to provide more information on pharmacodynamic interactions of the patient.

15. The system of claim 1, wherein generating the modified model comprises utilizing equations that simulate interaction of primary factors effecting the rate of change in blood glucose level of the patient, wherein the primary factors are calculated based on the patient data.

16. The system of claim 15, wherein the primary factors comprise at least one of a rate of digestion of patient carbohydrate intake, cellular uptake of blood glucose by the patient, and impact of glucose inventory in liver, skeletal muscle, or fat tissues of the patient.

17. The system of claim 2, wherein:

an equation for cellular uptake of blood glucose by the patient is a function of at least one of the blood glucose level, level of insulin acting as a catalyst, resistance factors, or digestive-activated hormones, and

wherein the level of insulin is calculated based on at least one of the patient medication doses, patient pancreatic production, or insulin kinetics.

18. The system of claim 2, wherein the patient data further comprises activity of the patient.

19. A nontransitory computer-readable storage medium storing a program for causing a computer to perform a method for generating treatment recommendations for a patient, the method comprising:

receiving transmitted patient data;

executing a basic model of a physiological system of the patient to generate a modified model for the patient based on the patient data, wherein the basic model comprises determining a rate of change in blood glucose level of the patient over a time interval based on food intake, insulin concentration in blood, and blood glucose inventory;

performing a statistical analysis of the patient data to detect data excursions of values of first parameters of the physiological system;

using the modified model to estimate an effect of the data excursions on second parameters of the physiological system;

using the modified model to determine factors causing the data excursions;

using the modified model to develop a plurality of treatment recommendations to ameliorate negative effects of the disease; and

outputting the treatment recommendations.

20. The nontransitory computer-readable storage medium according to claim 19, wherein the patient data comprises values of parameters including at least one of:

(a) patient carbohydrate intake,

(b) patient medication doses,

(c) blood glucose level, or

(d) corresponding time for the patient data.

21. The nontransitory computer-readable storage medium according to claim 19, wherein the plurality of treatment recommendations comprise at least one of recommendations for dosing and timing of medication, or recommendations for patient dietary behavior.

22. The nontransitory computer-readable storage medium according to claim 19, wherein executing the basic model comprises applying an algorithm to the patient data in a current state in conjunction with auxiliary patient data comprising at least one of patient blood lipid level, blood pressure, age, gender, height and weight, and race.

23. The nontransitory computer-readable storage medium according to claim 19, wherein the processor is further configured to develop recommendations for collection of the patient data to improve the basic model, wherein the recommendations for collection comprise recommendations for timing of blood glucose measurement.

24. The nontransitory computer-readable storage medium according to claim 19, wherein performing the statistical analysis comprises employing a statistical design of experiments methodology to identify the factors causing the data excursions.

25. A computer-implemented method for generating treatment recommendations for a patient, comprising:

receiving, by a receiver, transmitted patient data;

executing, by a processor, a basic model of a physiological system of the patient to generate a modified model for the patient based on the patient data, wherein the basic model comprises determining a rate of change in blood glucose level of the patient over a time interval based on food intake, insulin concentration in blood, and blood glucose inventory;

performing, by the processor, a statistical analysis of the patient data to detect data excursions of values of first parameters of the physiological system;

estimating, by the processor and using the modified model, an effect of the data excursions on second parameters of the physiological system;

determining, by the processor and using the modified model, factors causing the data excursions;

developing, by the processor and using the modified model, a plurality of treatment recommendations to ameliorate negative effects of the disease; and

outputting, by an output device, the treatment recommendations.