System and method of applying state of being to health care delivery

• US 9,305,140 B2
• Filed: 07/16/2012
• Issued: 04/05/2016
• Est. Priority Date: 07/16/2012
• Status: Active Grant

• Current Assignee: Georgetown University
• Original Assignee: Georgetown University
• Inventors: Federoff, Howard, Frieder, Ophir, Burger, Eric
• Primary Examiner(s): Reyes, Mariela
• Assistant Examiner(s): HARMON, COURTNEY N
• Application Number:
  US13/549,890
• Publication Number:
  US 20140019468A1
• Time in Patent Office: 1,359 Days
• Field of Search: 707/758
• US Class Current: 1/1
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 40/63 for local operation
• 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

Abstract

A system for assisting a subject to select a proper form of treatment. The system comprises: a monitoring section that remotely monitors a health status of the subject; an inference section that infers medical information about the subject based on information subject posted on social networks; a subject database that stores subject'"'"'s information; and a symptom engine that stores symptoms of medical situations. The inference section applies the health status and the medical information against symptoms stored in the symptom engine to determine a proper form of treatment.

Claims

1. A system for assisting a patient to select a treatment, comprising:

an interface for a monitoring section that monitors a health status of the patient;

an inference section that infers medical information about the patient based at least in part on social behavior data of the patient from at least one social network;

a patient database that stores patient information; and

a symptom engine that stores symptom data of medical conditions;

wherein the inference section comprises an integration and inference module configured to integrate data from a plurality of data sources including the health status and the medical information and compare against symptom data stored in the symptom engine to determine a treatment response;

wherein the inference section comprises a medical trend analysis module configured to determine a medical trend associated with the patient information; and

wherein the inference section is configured to continually infer a state of being including recent mood information for the patient by identifying abnormal or normal behaviors of the patient based at least in part on social behavior data of the patient to determine and deliver a notification of the treatment response;

wherein the inference section further infers the state of being of the patient as the medical information based on a symptom of the patient and information obtained through the at least one social network, the information including at least one or more of time spent on the social network by the patient and frequency of visit by the patient to the social network; and

wherein the inference section further infers the medical trend as the medical information based on a symptom of the patient and data regarding select members of the at least one social network, the select members being members of a family circle of the patient on the social network.

2. The system according to claim 1, wherein the inference section further infers the medical trend as the medical information based on a symptom of the patient and data regarding the patient, the data provided by one or more family circle members via the social network.

3. The system according to claim 1, wherein the inference section correlates symptoms and a plurality of states of being from multiple patients.

4. The system according to claim 1, wherein the monitoring section comprises a mobile wireless monitoring device.

5. The system according to claim 1, wherein the system comprises:

an interface with an aggregation component configured to aggregate information from the monitoring section about the health status of the patient.

6. The system according to claim 1, wherein the system contacts a health care provider when a medical treatment is needed.

7. A method for assisting a patient to select a treatment, compromising:

remotely monitoring a health status of the patient;

inferring medical information about the patient based at least in part on social behavior data of the patient from at least one social network;

storing patient information; and

storing symptoms of medical situations;

wherein the inferring comprises determining a treatment response based on a comparison of the health status and the medical information against the stored symptoms,

wherein the inferring further comprises continually inferring a state of being including recent mood information for the patient by identifying abnormal or normal behaviors of the patient based at least in part on social behavior data of the patient to determine and deliver a notification of the treatment response;

wherein the inferring further comprises inferring the state of being of the patient as the medical information based on a symptom of the patient and information obtained through the at least one social network, the information including at least one or more of time spent on the social network by the patient and frequency of visit by the patient to the social network; and

wherein the medical information further includes a medical trend based on a symptom of the patient and data regarding the patient, the data provided by one or more family circle members of the patient on the at least one social network.

8. The method according to claim 7, wherein the medical information further includes the state of being of the patient based on a symptom of the patient and information from the at least one social network, the information including at least one comment by a family circle member regarding one or more of an activity of the patient, a feeling of the patient and a mood of the patient.

9. The method according to claim 7, wherein the inferring further comprises obtaining information including at least one or more of time spent on the social network by the patient and frequency of visit by the patient to social network.

10. The method according to claim 7, wherein the inferring comprises correlating symptoms and a plurality of states of being from multiple patients.

11. The method according to claim 7, wherein the monitoring comprises using a mobile wireless monitoring device.

12. The method according to claim 7, wherein the method further comprises:

receiving aggregated health status information from an aggregation component that aggregates the health status information of the patient.

13. The method according to claim 7, wherein the method further comprises:

contacting a health care provider when a medical treatment is needed.

14. A non-transitory storage medium storing a program that, when executed, causes a processor to execute a method for assisting a patient to select a treatment, the method comprising:

remotely monitoring a health status of the patient;

inferring medical information about the patient based at least in part on social behavior data of the patient from at least one social network;

storing patient information; and

storing symptoms of medical situations;

wherein the inferring comprises comparing the health status data and the medical information against the stored symptoms to determine a treatment response, and

wherein the inferring further comprises continually inferring a state of being including recent mood information by identifying abnormal or normal behaviors based at least in part on social behavior data of the patient to determine and deliver a notification of the treatment response;

wherein the inferring further comprises inferring the state of being of the patient as the medical information based on a symptom of the patient and information obtained through the at least one social network, the information including at least one or more of time spent on the social network by the patient and frequency of visit by the patient to the social network; and

wherein the inferring further comprises inferring a medical trend as the medical information based on a symptom of the patient and data regarding select members of the at least one social network, the select members being members of a family circle of the patient on the social network.

15. The storage medium according to claim 14, wherein the inferring further comprises inferring the state of being of the subject as the medical information based on a symptom of the patient and social behavior data of the patient obtained through the at least one social network, the social behavior data including at least one comment by a family circle member regarding one or more of an activity of the patient, a feeling of the patient and a mood of the patient.

16. A device comprising:

an aggregation component configured to monitor a health status of a patient and aggregate information about the health status of the patient; and

an interface with a system comprising;

an inference section that infers medical information about the patient based at least in part on social behavior data of the patient from at least one social network;

a patient database that stores patient information; and

a symptom engine that stores symptom data of medical conditions;

wherein the inference section comprises an integration and inference module configured to integrate data from a plurality of data sources including the health status and the medical information and compare the integrated health status and medical information data against symptom data stored in the symptom engine to determine a treatment response,

wherein the inference section further comprises a medical trend analysis module configured to determine a medical trend associated with the patient information based at least in part on data regarding select members of the at least one social network, the select members having a connection to the patient; and

wherein the inferring comprises continually inferring a state of being including recent mood information for the patient by identifying abnormal or normal behaviors of the patient based at least in part on social behavior data of the patient to determine and deliver a notification of the treatment response;

wherein the social behavior data includes at least one comment by a family circle member regarding one or more of an activity of the patient, a feeling of the patient and a mood of the patient; and

wherein the inferring further comprises inferring the state of being of the patient as the medical information based on a symptom of the patient and information obtained through the at least one social network, the information including at least one or more of time spent on the social network by the patient and frequency of visit by the patient to the social network.

17. The device according to claim 16, wherein the aggregation component is connected with the patient database and the symptom engine via a network.

18. The device according to claim 16, wherein the aggregation component comprises an interface that monitors the health status of the patient, and a communication unit that communicates with the inference engine.

19. The device according to claim 16, wherein the aggregation component comprises a device selected from an advanced mobile phone, a tablet, or a wireless radio base station.

20. The device according to claim 16, wherein the aggregation component normalizes readings of at least one monitoring device.

21. The device according to claim 16, wherein the aggregation component is configured to filter out insignificant health status information to reduce the amount of network traffic.

22. The device according to claim 16, wherein the aggregation component is configured to preprocess the health status information to reduce load on the server or improve data accuracy.