Abstract: Systems and methods for automatically benchmarking a process of an organization are provided. A process of an organization is extracted from a database of process data. A semantic understanding of the process of the organization is determined. The process of the organization is benchmarked to a standardized process based on the semantic understanding. Results of the benchmarking are output.

Abstract: Systems and methods for automatically provisioning recommendations for optimizing a process are provided. A knowledge graph for an organization is generated. The knowledge graph for the organization is compared with an optimized knowledge graph. Recommendations for optimizing a process of the organization are generated based on the comparing. The recommendations for optimizing the process are output.

Abstract: Systems and methods for automatically generating a knowledge graph are provided. Entity data, process data, user data, and system data of an organization are extracted from one or more business data sources. A knowledge graph defining relationships between the entities data, the process data, the user data, and the system data is generated. The knowledge graph is output.

Abstract: Systems and methods for automatically creating a data model are provided. A semantic understanding of entities stored in one or more business data sources is determined. The entities are extracted from the one or more business data sources based on the semantic understanding. A data model for the entities is created. The data model is output.

Abstract: Systems and methods for performing process mining are provided. Data from one or more source systems is extracted by a data connector of a process app. The extracted data is transformed into a normalized data model by transforms of the process app. One or more process mining algorithms of the process app are applied to the normalized data. Results of the one or more process mining algorithms are presented to a user via a user interface of the process app.

Abstract: Systems and methods for configuring an RPA (robotic process automation) platform to perform a candidate process automation are provided. Discovery data relating to a candidate process automation is generated. RPA platform design components for configuring an RPA platform to perform the candidate process automation are generated based on the discovery data. The RPA platform design components are presented to a user via a user interface.

Abstract: Systems and methods for configuring an RPA (robotic process automation) platform to perform a candidate process automation are provided. Discovery data relating to a candidate process automation is generated. RPA platform design components for configuring an RPA platform to perform the candidate process automation are generated based on the discovery data. The RPA platform is configured based on the RPA platform design components.

Abstract: Systems and methods for generating an enterprise process graph are provided. Sets of process data relating to an implementation of RPA (robotic process automation) acquired using a plurality of discovery techniques is received. An enterprise process graph representing the implementation of RPA is generated based on the received sets of process data.

Abstract: Systems and methods for generating an enterprise process graph are provided. Sets of process data relating to an implementation of RPA (robotic process automation) acquired using a plurality of discovery techniques is received. An enterprise process graph representing the implementation of RPA is generated based on the received sets of process data.

Abstract: Embodiments of methods and systems for predicting provider negotiated rates are disclosed. One method includes obtaining claims data and provider data, grouping the claims data into priceable units, computing prices for each of the priceable units based on the claims data and the provider data, and estimating provider negotiated rates based on the priceable units and the computed prices for the priceable units.

Abstract: Embodiments of computer-methods and computer systems for predicting out-of-pocket expense for a patient are disclosed. One computer-method includes obtaining claims data and provider data and grouping the claims data into priceable units. A server computes prices for each of the priceable units based on the claims data and the provider data. The priceable units are collected into bundled services as required for predicting the out-of-pocket expense of an episode. Attributes of a health plan of the patient are applied, and an out-of-pocket calculator predicts the out-of-pocket expense based on the collected priceable units and the computed prices for the collected priceable units. The out-of-pocket expense is communicated to patient through a network.

Abstract: Embodiments of methods and systems for predicting provider negotiated rates are disclosed. One method includes obtaining claims data and provider data, grouping the claims data into priceable units, computing prices for each of the priceable units based on the claims data and the provider data, and estimating provider negotiated rates based on the priceable units and the computed prices for the priceable units.

Abstract: Embodiments of methods and systems for providing a payer with a platform for reference pricing of health care deliverables are disclosed. One method includes identifying a set of one or more health care deliverables to which reference pricing is to be applied, and setting a reference price for each health care deliverable of the set. For this embodiment, setting the reference price includes providing the payer with analysis of negotiated rates for the health care deliverable across at least one of geographies, demographics, and centers of excellence, and allowing the payer to set the reference price for each health care deliverable based on the provided analysis. The method further includes receiving a health care deliverable request from a user who is covered by the payer, retrieving the set reference price corresponding to the health care deliverable request, and providing the set reference price or out-of-pocket cost to the user.