Invention Grant
- Patent Title: Machine learning model for predicting health plans based on missing input data
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Application No.: US18235492Application Date: 2023-08-18
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Publication No.: US12045894B2Publication Date: 2024-07-23
- Inventor: James L. Poteet, III , Raymond G. Delano, III , Julie Ann Jensen
- Applicant: CERNER INNOVATION, INC.
- Applicant Address: US MO Kansas City
- Assignee: CERNER INNOVATION, INC.
- Current Assignee: CERNER INNOVATION, INC.
- Current Assignee Address: US MO Kansas City
- Agency: Kraguljac Law Group, LLC
- The original application number of the division: US16812535 2020.03.09
- Main IPC: G06Q40/08
- IPC: G06Q40/08 ; G06F18/213 ; G06N20/00 ; G06Q20/40 ; G16H10/60

Abstract:
Methods, computer systems, and computer storage media are provided for utilizing machine learning to predict health plans. A machine learning model is trained to predict valid combinations of employer-payer-health plan in response to one or more missing identifiers based on transaction data from electronic data interchange (EDI) insurance transactions that include valid combinations of employer identifier, payer identifier, and health plan identifier. In response to a request to identify a valid combination based on at least one missing identifier, at least one known identifier corresponding to an employer name, a payer name, or a health plan name is inputted and work location data associated with a patient. The machine learning model generates and displays on a user interface, a predicted set of one or more valid combinations of employer-payer-health plans that correspond to the one known identifier and the work location information that is inputted.
Public/Granted literature
- US20230394588A1 MACHINE LEARNING MODEL FOR PREDICTING HEALTH PLANS BASED ON MISSING INPUT DATA Public/Granted day:2023-12-07
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