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:
Apr. 11, 2023

Filed:

Apr. 02, 2019
Applicant:

Clarify Health Solutions, Inc., San Francisco, CA (US);

Inventors:

Jean P. Drouin, San Francisco, CA (US);

Samuel H. Bauknight, San Francisco, CA (US);

Todd Gottula, San Francisco, CA (US);

Yale Wang, San Francisco, CA (US);

Adam F. Rogow, San Francisco, CA (US);

Jeffrey D. Larson, San Francisco, CA (US);

Justin Warner, San Francisco, CA (US);

Erik Talvola, San Francisco, CA (US);

Assignee:

Clarify Health Solutions, Inc., San Francisco, CA (US);

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06Q 40/08 (2012.01); G06N 20/00 (2019.01); G06F 17/18 (2006.01); G06N 5/02 (2023.01);
U.S. Cl.
CPC ...
G06Q 40/08 (2013.01); G06F 17/18 (2013.01); G06N 20/00 (2019.01); G06N 5/02 (2013.01);
Abstract

Computer network architectures for machine learning, and more specifically, computer network architectures for the automated completion of healthcare claims. Embodiments of the present invention provide computer network architectures for the automated completion of estimated final cost data for claims for healthcare clinical episodes using incomplete data for healthcare insurance claims and costs, known to date. Embodiments may use an automatic claims completion web application, with other computer network architecture components. Embodiments may include a combination of third-party databases to generate estimated final claims for pending patient clinical episodes, and to drive the forecasting models for the same, including social media data, financial data, social-economic data, medical data, search engine data, e-commerce site data, and other databases.


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