Method and Apparatus for Monitoring Medication Adherence

• US 20120316897A1
• Filed: 07/24/2011
• Published: 12/13/2012
• Est. Priority Date: 06/10/2011
• Status: Abandoned Application

• Current Assignee: AIC Innovations Group, Inc.
• Original Assignee: AI CURE Technologies Incorporated
• Inventors: Hanina, Adam, Kessler, Gordon, Guan, Lei
• Application Number:
  US13/189,518
• Publication Number:
  US 20120316897A1
• Time in Patent Office: Days
• US Class Current: 705/3
• CPC Class Codes: G06F 18/217 Validation; Performance evaluation; Active pattern learning techniques
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 2207/30196 Human being; Person
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06V 20/41 Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items segmenting video sequences G06V20/49
• CPC Class Codes: G06V 40/20 Movements or behaviour, e.g. gesture recognition recognition of facial expressions G06V40/16
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 20/70 relating to mental therapies, e.g. psychological therapy or autogenous training
• CPC Class Codes: G16H 40/67 for remote operation

Abstract

A method and apparatus for monitoring medication adherence. The method includes the steps of determining a present adherence state of a patient, receiving video analysis information reporting on a medication administration session, and determining a next adherence state of a patient based upon the present adherence state of the patient and the video analysis information.

Claims

1. A method for monitoring medication adherence, comprising the steps of:

determining a present adherence state of a patient;

receiving video analysis information reporting on a medication administration session;

determining a next adherence state of a patient based upon the present adherence state of the patient and the video analysis information

2. The method of claim 1, further comprising the step of initiating one or more actions based upon determination of the next adherence state.

3. The method of claim 1, further comprising the step of initiating one or more actions based upon a trend from the present adherence state and the next adherence state.

4. The method of claim 1, wherein the video analysis information includes an automated determination from a video record whether a user has taken a medication.

5. The method of claim 1, wherein the video analysis information comprises a computer vision analysis of a medication administration session.

6. The method of claim 1, wherein the video analysis information comprises a trend of a predetermined variable over time.

7. The method of claim 1, wherein the video analysis information comprises a determination that a particular variable differs by greater than a predetermined threshold amount from one or more prior variable values.

8. The method of claim 1, wherein a confidence level associated with the video analysis information is employed to determine the next patient adherence state.

9. The method of claim 8, wherein the confidence level comprises a confidence trend level over time.

10. The method of claim 1, further comprising the step of displaying the patient adherence state information on a dashboard display.

11. The method of claim 1, wherein the dashboard display shown a plurality of trends over time determined from the video analysis information.

12. The method of claim 11, wherein the plurality of trends are used to determine the next patient adherence state.

13. The method of claim 1, wherein further processing of the video analysis information at a time remote from the time of medication administration is employed at least in part to determine a next adherence state of a patient.

14. The method of claim 1, wherein one or more common patient states between a plurality of patients are employed to group those patients.

15. The method of claim 14, wherein the grouped patients may be addressed under a common scheme.

16. The method of claim 15, wherein the common scheme may be employed to address particular high risk patients.

17. The method of claim 1, wherein one or more next adherence states are determined through a computer learning analysis of the received video analysis information.

18. The method of claim 1, further comprising the use of audio information in conjunction with the video information.

19. A system for implementing the method of claims 1-16.