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.
Patent No.:
Date of Patent:
Jan. 03, 2017
Filed:
Sep. 13, 2012
Rubendran Amarasingham, Dallas, TX (US);
Timothy S. Swanson, Grapevine, TX (US);
Christopher A. Clark, Dallas, TX (US);
Yu Qian, Irving, TX (US);
Sambamurthy Nalla, Flower Mound, TX (US);
George R. Oliver, Southlake, TX (US);
Kimberly P. Gerra, Keller, TX (US);
Ying MA, Southlake, TX (US);
Rubendran Amarasingham, Dallas, TX (US);
Timothy S. Swanson, Grapevine, TX (US);
Christopher A. Clark, Dallas, TX (US);
Yu Qian, Irving, TX (US);
Sambamurthy Nalla, Flower Mound, TX (US);
George R. Oliver, Southlake, TX (US);
Kimberly P. Gerra, Keller, TX (US);
Ying Ma, Southlake, TX (US);
Parkland Center for Clinical Innovation, Dallas, TX (US);
Abstract
A clinical predictive and monitoring system comprising a data store operable to receive and store data associated with a plurality of patients selected from medical and health data; and a number of social, behavioral, lifestyle, and economic data; at least one predictive model to identify at least one high-risk patient associated with at least one medical condition; a risk logic module operable to apply the at least one predictive model to the patient data to determine at least one risk score associated the at least one medical condition and identify at least one high-risk patient; a data presentation module operable to present notification and information to an intervention coordination team about the identified at least one high-risk patient; and an artificial intelligence tuning module adapted to automatically adjust parameters in the predictive model in response to trends in the patient data.