Method and System for Improving Weight Management Interventions by Assessing Variability in Serial Weight Measurements

• US 20170084195A1
• Filed: 09/17/2015
• Published: 03/23/2017
• Est. Priority Date: 09/17/2015
• Status: Abandoned Application

• Current Assignee: Susan Roberts
• Original Assignee: Susan Roberts
• Inventors: Roberts, Susan
• Application Number:
  US14/856,669
• Publication Number:
  US 20170084195A1
• Time in Patent Office: Days
• 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: G09B 19/0092 Nutrition
• CPC Class Codes: G09B 5/00 Electrically-operated educational appliances working with questions and answers G09B7/00; simulators G09B9/00; advertising or displaying in general G09F
• CPC Class Codes: G16H 20/60 relating to nutrition control, e.g. diets

Abstract

The present disclosure features novel methods and systems of using a computer system to facilitate improvement of a weight management intervention. In one embodiment, a method of improving a weight management intervention comprises receiving, by an analysis agent executing on a processor, a daily weight measurement of a patient enrolled in the weight management intervention. A short term period of adherence or non-adherence to the weight management intervention is detected based on the daily weight measurement and at least one previous daily weight measurement. A cause of the short term period of non-adherence is identified. Based on the cause, the weight management intervention can be modified in response. Short-term detection and response to adherence and non-adherence is extremely useful in promoting greater adherence to a weight management intervention, and through greater adherence leading to greater weight loss, lower drop out, greater sustainability of weight loss and greater participant satisfaction.

Claims

1. A method of using a computer system to facilitate improvement of a weight management intervention, comprising:

receiving, by an analysis agent executing on a processor, a daily weight measurement of a patient enrolled in the weight management intervention;

detecting a short term period of adherence or non-adherence to the weight management intervention based on the daily weight measurement and at least one previous daily weight measurement;

identifying a cause of the short term period of non-adherence; and

adjusting the weight management intervention in response to the identified cause.

2. The method of claim 1, further comprising detecting a short term period of adherence, and providing feedback on identified adherence, and receiving a second daily weight measurement of the patient.

3. The method of claim 1, wherein detecting a short term period of non-adherence to the weight management intervention based on the daily weight measurement and at least one previous daily weight measurement comprises calculating the variability between the daily weight measurement and the at least one previous daily weight measurement.

4. The method of claim 3, wherein detecting a short term period of non-adherence to the weight management intervention based on the daily weight measurement and at least one previous daily weight measurement comprises calculating the magnitude difference and direction of change between the daily weight measurement and the at least one previous daily weight measurement.

5. The method of claim 4, wherein the magnitude difference in change and direction of change are compared to predefined criteria.

6. The method of claim 1, wherein the short term period of adherence or non-adherence comprises a single day.

7. The method of claim 1, wherein the at least one previous daily weight measurement comprises the daily weight measurement from the previous day.

8. The method of claim 1, wherein detecting a short term period of non-adherence to the weight management intervention based on the daily weight measurement and at least one previous daily weight measurement comprises calculating a linear regression based on the daily weight measurement and a plurality of previous daily weight measurements.

9. The method of claim 8, wherein calculating a linear regression based on the daily weight measurement and a plurality of previous daily weight measurements comprises calculating a slope and an error of fit.

10. The method of claim 9, wherein detecting a short term period of non-adherence to the weight management intervention based on the daily weight measurement and at least one previous daily weight measurement comprises analyzing the error of fit.

11. The method of claim 8, wherein the linear regression is performed using weight measurement observations from the previous week.

12. The method of claim 1, wherein identifying a cause of the short term period of non-adherence comprises identifying a period of weekend eating based on the short term period of non-adherence.

13. The method of claim 1, wherein the weight management intervention is a weight loss intervention.

14. A method of determining adherence to a weight loss intervention, comprising:

receiving, by an analysis agent executing on a processor, a plurality of weight measurements of an individual prescribed a weight loss intervention;

determining, on a daily basis, the variability of the plurality of weight measurements;

analyzing the variability of the plurality of weight measurements to identify a short term period of non-adherence to the weight loss intervention; and

identifying a cause of the short term period of non-adherence.

15. A computer system for facilitating improvement of a weight management intervention, comprising:

a memory storing;

a plurality of daily weight measurements; and

a weight management intervention; and

an analysis agent executing on a processor and configured to;

receive a daily weight measurement of a patent enrolled in the weight management intervention;

detect a short term period of non-adherence to the weight management intervention based on the daily weight measurement and at least one previous daily weight measurement from the plurality of daily weight measurements;

identify a cause of the short term period of non-adherence; and

adjust the weight management intervention in response to the identified cause.

16. The computer system of claim 15, wherein the analysis agent executing on a processor is further configured to calculate the variability between the daily weight measurement and the at least one previous daily weight measurement.

17. The computer system of claim 15, wherein the analysis agent executing on a process is configured to detect a short term period of adherence or non-adherence to the weight management intervention by calculating a linear regression based on the daily weight measurement and a plurality of previous daily weight measurements.

18. The computer system of claim 17, wherein calculating a linear regression based on the daily weight measurement and a plurality of previous daily weight measurements comprises calculating a slope and an error of fit.

19. The computer system of claim 18, wherein detecting a short term period of adherence or non-adherence to the weight management intervention based on the daily weight measurement and at least one previous daily weight measurement comprises analyzing the error of fit.

20. The computer system of claim 17, wherein the linear regression is performed using weight measurement observations from the previous week.