Centralized practice portal with machine learning claim processing

A claim scrubber system, comprising:

• a database of processed dental insurance claims that includes at least:
• a set of processed dental insurance claims rejected by an insurance company, and
• a set of processed dental insurance claims accepted by an insurance company;
• a claim analyzer subsystem comprising a machine learning model trained on the database of processed dental insurance claims and configured to:
• receive an input dental insurance claim for evaluation, and
• generate, using the trained machine learning model, a predicted payment outcome score indicating a likelihood that an insurance company will pay the evaluated dental insurance claim;
• a display subsystem to render, for display on an electronic display, the predicted payment outcome score associated with the evaluated dental insurance claim;
• and
• a machine learning model feedback subsystem to:
• determine, after submission of the evaluated dental insurance claim, a payment status of the submitted dental insurance claim as being paid, partially paid, or unpaid by the insurance company, and
• provide, as training feedback to the machine learning model of the claim analyzer subsystem, the submitted dental insurance claim and the payment status of the submitted dental insurance claim to improve predicted payment outcome scoring of subsequently provided dental insurance claims.

A method of scrubbing dental insurance claims, comprising:

• accessing a database of processed dental insurance claims from multiple independent dental offices;
• training a machine learning model on the database of processed dental insurance claims to predict a payment outcome score for input dental insurance claims, where the predicted payment outcome score of each dental insurance claim indicates a likelihood of payment;
• evaluating, via the machine learning model, a first plurality of dental insurance claims for a first dental office to determine a predicted payment outcome score for each of the first plurality of dental insurance claims;
• evaluating, via the machine learning model, a second plurality of dental insurance claims for a second dental office to determine a predicted payment outcome score for each of the second plurality of dental insurance claims;
• receiving payment outcome information from the first dental office for at least some of the first plurality of dental insurance claims submitted by the first dental office;
• and
• receiving payment outcome information from the second dental office for at least some of the second plurality of dental insurance claims submitted by the second dental office.

A system, comprising:

• a claim analyzer subsystem with a machine learning model trained on a general database of processed dental insurance claims from multiple independent dental offices configured to:
• determine a predicted payment outcome score for an input dental insurance claim, and
• determine a suggested modification to the input dental insurance claim that is predicted to increase the predicted payment outcome score;
• a feedback subsystem to receive feedback including:
• modification feedback indicating whether a user accepted the suggested modification to the dental insurance claim prior to submission to an insurance carrier, and
• outcome feedback indicating whether the dental insurance claim was paid by the insurance carrier;
• and
• a training subsystem to continuously train the machine learning model using the received modification feedback and outcome feedback to improve determinations of predicted payment outcome scores and suggested modifications of subsequently input dental insurance claims.