US 11,721,429 B1
Event prediction based on medical service and provider information using an artificial intelligence prediction engine
Christopher Mayer, Johns Creek, GA (US); and Balaji Lakshmi Ramakrishnan, Alpharetta, GA (US)
Assigned to CHANGE HEALTHCARE HOLDINGS, LLC, Nashville, TN (US)
Filed by Change Healthcare Holdings LLC, Nashville, TN (US)
Filed on Sep. 30, 2020, as Appl. No. 17/38,667.
Int. Cl. G16H 40/20 (2018.01); G16H 50/70 (2018.01); G06Q 40/08 (2012.01); G06N 20/00 (2019.01); G06Q 10/10 (2023.01); G16H 70/20 (2018.01); G06Q 40/12 (2023.01)
CPC G16H 40/20 (2018.01) [G06N 20/00 (2019.01); G06Q 10/10 (2013.01); G06Q 40/08 (2013.01); G06Q 40/12 (2013.12); G16H 50/70 (2018.01); G16H 70/20 (2018.01)] 13 Claims
OG exemplary drawing
 
1. A method, comprising:
receiving information associated with a stimulus, the stimulus comprising a filing of a medical claim with a payor, the information associated with the stimulus comprising first information associated with a medical claim for services provided to a patient and second information associated with a provider that provided the services to the patient;
generating, using a machine learning engine, an artificial intelligence engine; and
predicting, using the artificial intelligence engine, when an event will occur in response to the stimulus, the event comprises payment of the medical claim by the payor;
wherein generating the artificial intelligence engine comprises:
receiving training information associated with the stimulus, the training information associated with the stimulus comprising first training information associated with a plurality of medical claims for services provided to a plurality of patients, respectively, the first training information comprising payment information associated with the plurality of medical claims, and second training information associated with a plurality of providers that provided the services to the plurality of patients;
detecting patterns in the training information associated with the stimulus;
training the machine learning engine based on the detected patterns detected in the training information associated with the stimulus; and
generating the artificial intelligence engine based on the machine learning engine that has been trained.