Machine-learning driven real-time data analysis

A data processing system comprising:

• a processor;
• and
• a machine-readable medium storing executable instructions that, when executed, cause the processor alone or in combination with other processors to perform operations comprising:
• obtaining policy coverage information for each of a plurality of insurance policies associated with an insured user, the policy coverage information being formatted according to a standard schema for processing policy and claim information;
• obtaining insurance claim information associated with a plurality of insurance claims associated with the insured user, the insurance claim information being formatted according to the standard schema for processing policy and claim information;
• grouping the insurance claim information based on events requiring medical treatment by analyzing the insurance claim information using a claims grouping model to obtain event-related claim grouping information, the claims grouping model being trained with first training data formatted according to the standard schema to recognize patterns in insurance claim information indicative of an occurrence of specific types of events requiring medical treatment, the event-related claim grouping information including an indication of one or more events predicted to have occurred based on the insurance claim information and one or more insurance claims of the plurality of insurance claims included in the insurance claim information predicted to be associated with each event of the one or more events;
• analyzing each group of claims of the event-related claim grouping information and the policy coverage information using a coverage prediction model to obtain coverage prediction information, the coverage prediction model being trained to output a prediction for a group of claims whether one or more insurance policies of the plurality of insurance policies identified in the policy coverage information will cover the group of claims;
• and
• providing, via a network connection, the coverage prediction information to a computing device associated with the insured user.

A method implemented in a data processing system for insurance claims analysis and adjudication, the method comprising:

• obtaining policy coverage information for each of a plurality of insurance policies associated with an insured user, the policy coverage information being formatted according to a standard schema for processing policy and claim information;
• obtaining insurance claim information associated with a plurality of insurance claims associated with the insured user, the insurance claim information being formatted according to the standard schema for processing policy and claim information;
• grouping the insurance claim information based on events requiring medical treatment by analyzing the insurance claim information using a claims grouping model to obtain event-related claim grouping information, the claims grouping model being trained with first training data formatted according to the standard schema to recognize patterns in insurance claim information indicative of an occurrence of specific types of events requiring medical treatment, the event-related claim grouping information including an indication of one or more events predicted to have occurred based on the insurance claim information and one or more insurance claims of the plurality of insurance claims included in the insurance claim information predicted to be associated with each event of the one or more events;
• analyzing each group of claims of the event-related claim grouping information and the policy coverage information using a coverage prediction model to obtain coverage prediction information, the coverage prediction model being trained to output a prediction for a group of claims whether one or more insurance policies identified in the policy coverage information will cover the group of claims;
• and
• providing, via a network connection, the coverage prediction information to a computing device associated with the insured user.

A machine-readable medium on which are stored instructions that, when executed, cause a processor of a programmable device alone or in combination with other processors to perform operations of:

• obtaining policy coverage information for each of a plurality of insurance policies associated with an insured user, the policy coverage information being formatted according to a standard schema for processing policy and claim information;
• obtaining insurance claim information associated with a plurality of insurance claims associated with the insured user, the insurance claim information being formatted according to the standard schema for processing policy and claim information;
• grouping the insurance claim information based on events requiring medical treatment by analyzing the insurance claim information using a claims grouping model to obtain event-related claim grouping information, the claims grouping model being trained with first training data formatted according to the standard schema to recognize patterns in insurance claim information indicative of an occurrence of specific types of events requiring medical treatment, the event-related claim grouping information including an indication of one or more events predicted to have occurred based on the insurance claim information and one or more insurance claims of the plurality of insurance claims included in the insurance claim information predicted to be associated with each event of the one or more events;
• analyzing each group of claims of the event-related claim grouping information and the policy coverage information using a coverage prediction model to obtain coverage prediction information, the coverage prediction model being trained to output a prediction for a group of claims whether one or more insurance policies identified in the policy coverage information will cover the group of claims;
• and
• providing, via a network connection, the coverage prediction information to a computing device associated with the insured user.