The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Aug. 06, 2024

Filed:

May. 31, 2019
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Zhiguo Li, Yorktown Heights, NY (US);

Ching-Hua Chen, New York, NY (US);

Chandramouli Maduri, Elmsford, NY (US);

Pei-Yun Hsueh, New York, NY (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G16H 20/10 (2018.01); G06F 16/28 (2019.01); G06F 30/20 (2020.01); G16H 50/30 (2018.01);
U.S. Cl.
CPC ...
G16H 20/10 (2018.01); G06F 16/285 (2019.01); G06F 30/20 (2020.01); G16H 50/30 (2018.01);
Abstract

A method, a computer program product, and a computer system predict medication adherence of a patient. The method includes identifying risk factors associated with medication adherence of the patient. The method includes determining a likely behaviour for medication adherence of the patient based on the identified risk factors and a temporal causal model. The temporal causal model is based on features of a patient cluster to which the patient belongs. The features are nodes in the temporal causal model. The likely behaviour is based on causality measures for each identified risk factor to the nodes. The method includes determining a current medication adherence value of the patient. The current medication adherence value is indicative of a ratio between an actual medication regiment and an expected medication regiment. The method includes determining a future medication adherence value of the patient based on the current medication adherence value and the causality measures.


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