Abstract: Method, systems, and apparatus for training a machine-learning model on data comprising a plurality of originally filed procedural codes, a plurality of revised procedural codes, one or more insurance providers, descriptions from procedures associated with the procedural codes, procedural approval statuses, and a plurality of fee amounts; receiving one or more candidate procedural codes with respective fee amounts; and using the machine-learning model to generate one or more recommended procedural codes that are different from the one or more candidate procedural codes.

Abstract: Method, systems, and apparatus for receiving a request for appointment availability, wherein the request for appointment availability comprises one or more procedural codes; determining an aggregate appointment duration and provider type data based at least on the one or more procedural codes from a first mapping of procedural codes to procedural durations and a second mapping of procedural codes to provider type data; identifying a plurality of appointment constraints based at least on the request for appointment availability, the aggregate appointment duration, and the provider type data; and applying the plurality of appointment constraints to calendar availability data of a plurality of providers to generate a plurality of candidate appointment slots based at least on the plurality of appointment constraints.

Abstract: Method, systems, and apparatus for generating a plurality of candidate patient procedures based at least on one or more procedural codes; determining, for each of the plurality of candidate patient procedures, a risk score for the candidate patient procedure using a machine-learning model trained on data comprising one or more procedure types, patient information, and frequency scores of procedural incidents for each procedure type, and severity scores of procedural incidents for each procedure type; determining, for each of the plurality of candidate patient procedures, a recommendation score for the candidate patient procedure based at least on insurance provider data for the patient in the candidate patient procedure, a mapping of the candidate patient procedure to revenue per procedure, and the risk score for the candidate patient procedure; and generating one or more appointment creation messages for distribution to a plurality of candidate patients based on the recommendation scores.

Abstract: Method, systems, and apparatus for receiving appointment data about one or more appointments, wherein the appointment data comprises one or more procedural codes for each of the one or more appointments; generating an estimated amount of inventory used for each of the one or more appointments based at least on the one or more procedural codes; calculating a remaining amount of available inventory from the estimated amount of inventory used; generating a threshold for each supply in the remaining amount of available inventory based at least on historical purchase data for the supply, wherein the historical purchase data comprises a duration from order to arrival; determining, for a given supply, that the remaining amount of available inventory for the given supply is under the generated threshold; and in response to the determining, generating a notification for a user to purchase the given supply.

Abstract: A computer based method and system for advanced scenario based alert generation and processing is presented, with the specific ability to broker and investor activities that put either at risk. Advanced scenarios that describe such broker and investor activities are specifically defined. By applying these scenarios to transactional data from a variety of financial institutions, broker and investor activities causing unacceptable amounts of risk can be detected on an automated basis.

Abstract: A computer based method and system for advanced scenario based alert generation and processing is presented, with the specific ability to broker and investor activities that put either at risk. Advanced scenarios that describe such broker and investor activities are specifically defined. By applying these scenarios to transactional data from a variety of financial institutions, broker and investor activities causing unacceptable amounts of risk can be detected on an automated basis.

Abstract: A computer based method and system for advanced scenario based alert generation and processing is presented, with the specific ability to broker and investor activities that put either at risk. Advanced scenarios that describe such broker and investor activities are specifically defined. By applying these scenarios to transactional data from a variety of financial institutions, broker and investor activities causing unacceptable amounts of risk can be detected on an automated basis.