MEDICAL HEALTH INFORMATION SYSTEM FOR HEALTH ASSESSMENT, WEIGHT MANAGEMENT AND MEAL PLANNING

• US 20120072233A1
• Filed: 09/20/2011
• Published: 03/22/2012
• Est. Priority Date: 09/20/2010
• Status: Abandoned Application

• Current Assignee: Phenotypeit Incorporated
• Original Assignee: Phenotypeit Incorporated
• Inventors: Hanlon, Alaina B., Connolly, Peter, Grinspoon, Steven K.
• Application Number:
  US13/237,648
• Publication Number:
  US 20120072233A1
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G06Q 30/0271 Personalized advertisement
• CPC Class Codes: G16H 20/60 relating to nutrition control, e.g. diets
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

A system and method provide nutrition assessments and tools for enabling users to achieve health-related goals based on specific health needs. The tools can include a nutrition assessment tool, a weight solution tool, a meal planning tool, and a meal tracking tool. The method includes receiving patient phenotype data. The phenotype data can include, but is not limited to, biometric data specific to the patient, medical claims data specific to the patient, organizational data specific to an organization to which the patient belongs, and behavioral data including dietary habits and nutritional history. One or more algorithms are executed on at least one processor of a computing apparatus to provide analyses of patient data in order. The results are output to a user in various web pages customized to provide features to the user.

Claims

1. A computer implemented method, comprising:

receiving, from one or more input devices, patient data comprising one or more of phenotype data specific to a patient, biometric data specific to the patient, nutritional health data specific to the patient, medical claims data specific to the patient, and organizational data specific to an organization to which the patient belongs;

generating, using one or more processors, one or more predictive models based on the patient data, using one or more algorithms executing on at least one processor of a computing apparatus, the one or more predictive models determining and indicating potential for development by the patient of disease and adverse health conditions, or providing users with weight management guidelines and meal planning, or both; and

outputting, onto one or more output devices, the potential for development by the patient of disease and adverse health conditions, the weight management guidelines and meal planning, or both.

2. The computer implemented method of claim 1, wherein the potential for development by the patient of disease and adverse health conditions, the weight management guidelines and meal planning, or both further are caused to be presented on one or more electronic displays of information.

3. The computer implemented method of claim 1, further comprising providing a weight solution tool.

4. The computer implemented method of claim 1, further comprising:

receiving, from one or more input devices, an ideal body weight for a user;

calculating, using one or more processors, a caloric expenditure value for the user that is based at least in part on the received patient data;

calculating, using one or more processors, a first body mass index for the user that is based at least in part on the caloric expenditure value; and

outputting, onto one or more output devices, a risk percentage change that is based at least in part on the first body mass index and the received ideal body weight.

5. The computer implemented method of claim 4, further comprising calculating, using one or more processors, a basal energy expenditure for the user, wherein the step of calculating a caloric expenditure value is based at least in part on the calculated basal energy expenditure.

6. The computer implemented method of claim 1, further comprising:

receiving, from one or more input devices, a plurality of user data pertaining to a weight goal;

generating, using one or more processors, one or more charts or graphs comprising the received user data pertaining to the weight goal; and

outputting, onto one or more output devices, the one or more generated charts or graphs;

wherein the one or more generated charts or graphs track progress of a user toward the weight goal.

7. The computer implemented method of claim 1, further comprising providing a nutritional health assessment tool.

8. The computer implemented method of claim 1, further comprising calculating, using one or more processors, any one or more of the following:

a caloric intake score, a nutrient score, and a servings score.

9. The computer implemented method of claim 1, further comprising, for each of a plurality of different food groups, calculating a servings score that is based at least in part on the received patient data.

10. The computer implemented method of claim 1, further comprising providing a meal planner tool.

11. The computer implemented method of claim 1, further comprising:

receiving one or more user preferences comprising one or more health needs or health goals; and

outputting, onto one or more output devices, one or more menus presenting meal information;

wherein the meal information is customized according to the one or more health needs or health goals.

12. The computer implemented method of claim 11, further comprising enabling a user to modify one or more of the meal information.

13. The computer implemented method of claim 1, further comprising outputting, onto one or more output devices, a calendar organizing the one or more meal information according to date.

14. The computer implemented method of claim 1, further comprising:

receiving, from one or more input devices, a signal indicating that a user device is within a predetermined distance of a tagged location; and

sending information to the user device, the information being determined at least in part based on the weight management guidelines, the meal planning, or both, and the tagged location.

15. A computer implemented method, comprising:

receiving, from one or more input devices, patient data comprising one or more of phenotype data specific to a patient, biometric data specific to the patient, nutritional health data specific to the patient, medical claims data specific to the patient, and organizational data specific to an organization to which the patient belongs;

generating, using one or more processors, one or more predictive models based on the patient data, using one or more algorithms executing on at least one processor of a computing apparatus, the one or more predictive models determining user specific weight management guidelines, meal planning recommendations, or both; and

outputting, onto one or more output devices, the weight management guidelines, meal planning recommendations, or both, to the user.

16. The computer implemented method of claim 15, wherein the potential for development by the patient of disease and adverse health conditions, the weight management guidelines and meal planning, or both further are caused to be presented on one or more electronic displays of information.

17. The computer implemented method of claim 15, further comprising providing a weight solution tool.

18. The computer implemented method of claim 15, further comprising:

receiving, from one or more input devices, an ideal body weight for a user;

calculating, using one or more processors, a caloric expenditure value for the user that is based at least in part on the received patient data;

calculating, using one or more processors, a first body mass index for the user that is based at least in part on the caloric expenditure value; and

outputting, onto one or more output devices, a risk percentage change that is based at least in part on the first body mass index and the received ideal body weight.

19. The computer implemented method of claim 18, further comprising calculating, using one or more processors, a basal energy expenditure for the user, wherein the step of calculating a caloric expenditure value is based at least in part on the calculated basal energy expenditure.

20. The computer implemented method of claim 15, further comprising:

receiving, from one or more input devices, a plurality of user data pertaining to a weight goal;

generating, using one or more processors, one or more charts or graphs comprising the received user data pertaining to the weight goal; and

outputting, onto one or more output devices, the one or more generated charts or graphs;

wherein the one or more generated charts or graphs track progress of a user toward the weight goal.

21. The computer implemented method of claim 15, further comprising providing a nutritional health assessment tool.

22. The computer implemented method of claim 15, further comprising calculating, using one or more processors, any one or more of the following:

a caloric intake score, a nutrient score, and a servings score.

23. The computer implemented method of claim 15, further comprising, for each of a plurality of different food groups, calculating a servings score that is based at least in part on the received patient data.

24. The computer implemented method of claim 15, further comprising providing a meal planner tool.

25. The computer implemented method of claim 15, further comprising:

receiving one or more user preferences comprising one or more health needs or health goals; and

outputting, onto one or more output devices, one or more menus presenting meal information;

wherein the meal information is customized according to the one or more health needs or health goals.

26. The computer implemented method of claim 25, further comprising enabling a user to modify one or more of the meal information.

27. The computer implemented method of claim 15, further comprising outputting, onto one or more output devices, a calendar organizing the one or more meal information according to date.

28. The computer implemented method of claim 15, further comprising:

receiving, from one or more input devices, a signal indicating that a user device is within a predetermined distance of a tagged location; and

sending information to the user device, the information being determined at least in part based on the weight management guidelines, the meal planning, or both, and the tagged location.

29. In a networked computer environment, a system, comprising:

a storage device storing patient data comprising one or more of phenotype data specific to a patient, biometric data specific to the patient, nutritional health data specific to the patient, medical claims data specific to the patient, and organizational data specific to an organization to which the patient belongs;

at least one processor provided with executable instructions for generating one or more predictive models, using one or more algorithms executing on the at least one processor, the one or more predictive models determining and indicating a potential for development by the patient of disease and adverse health conditions, or providing users with weight management guidelines and meal planning, or both; and

an output mechanism configured to output the potential for development by the patient of disease and adverse health conditions, the weight management guidelines and meal planning, or both.

30. In a networked computer environment, a system, comprising:

a storage device storing patient data comprising one or more of phenotype data specific to a patient, biometric data specific to the patient, nutritional health data specific to the patient, medical claims data specific to the patient, and organizational data specific to an organization to which the patient belongs;

generating one or more predictive models based on the patient data, using one or more algorithms executing on at least one processor of a computing apparatus, the one or more predictive models determining user specific weight management guidelines, meal planning recommendations, or both; and

an output mechanism configured to output the weight management guidelines, meal planning recommendations, or both, to the user.