Methods and systems for determining universally acceptable prices in healthcare industry

A computer-implemented method, comprising:

• receiving, by a server system, user requests from one or more electronic devices via a communication network;
• providing, by the server system, a software application to perform operations comprising:
• receiving, by the server system, claims data from one or more data sources and a database over the communication network and generating statistical price records from the claims data, wherein the database includes an Artificial Intelligence (AI) or Machine Learning (ML) model used in creation and management of healthcare cost management data and in processing of natural language plan documentation;
• receiving, by the server system, Machine-Readable Files (MRFs) and other pricing arrangements from the one or more data sources, and generating direct price records from the MRFs and the other pricing arrangements;
• receiving, by the server system, one or more of payor rate overrides and provider rate overrides from one or more respective devices associated with one or more of a payor and a provider, respectively;
• generating, by the server system, first recommended price records from the statistical price records, and second recommended price records from the direct price records, wherein the statistical price records and the direct price records are each grouped into a plurality of record groups by dimensions and keys, each record group processed individually to generate the first recommended price records and the second recommended price records, respectively, wherein each record group is processed by:
• determining a calculation method for each record group among the plurality of record groups;
• applying the calculation method to the corresponding record to generate the first recommended price records and the second recommended price records;
• selecting, by the server system, universally acceptable price records from the first recommended price records, the second recommended price records, the payor rate overrides, and the provider rate overrides;
• generating, by the server system, machine-readable files (MRFs) corresponding to the universally acceptable price records, wherein for processing and generation of the MRFs, a data-parallel and scale-out architecture with bespoke data pipelines is utilized;
• performing, by the server system, an adjustment to the universally acceptable price records comprised in the MRFs;
• and
• generating, by the server system, a self-service consumer price shopping tool based on the universally acceptable price records to provide one or more users with access to the universally acceptable price records for healthcare services.

A server system, comprising:

• a processor, and
• a memory unit comprising machine-readable instructions, the machine-readable instructions when executed by the processor, cause the server system to at least:
• receive user requests from one or more electronic devices via a communication network;
• provide a software application to perform operations, wherein to perform the operations, the server system is caused to:
• receive claims data from one or more data sources over the communication network and generate statistical price records from the claims data;
• receive Machine-Readable Files (MRFs) and other pricing arrangements from the one or more data sources and a database, and generate direct price records from the MRFs and the other pricing arrangements, wherein the database includes an Artificial Intelligence (AI) or Machine Learning (ML) model used in creation and management of healthcare cost management data and in processing of natural language plan documentation;
• receive one or more of payor rate overrides and provider rate overrides from one or more respective devices associated with one or more of a payor and a provider, respectively;
• group the statistical price records by a first set of dimensions and keys into a first set of record groups;
• group the direct price records by a second set of dimensions and keys into a second set of record groups;
• determine a calculation method for each record group among the first set of record groups and the second set of record groups;
• apply the calculation method to the corresponding record to generate first recommended price records and second recommended price records;
• select a data source among a plurality of data sources as universally acceptable price records, wherein the plurality of data sources comprise the first recommended price records, the second recommended price records, the payor rate overrides, and the provider rate overrides;
• generate machine-readable files (MRFs) corresponding to the universally acceptable price records, wherein for processing and generation of the MRFs, a data-parallel and scale-out architecture with bespoke data pipelines is utilized;
• perform an adjustment to the universally acceptable price records comprised in the MRFs;
• and
• generate a self-service consumer price shopping tool based on the universally acceptable price records to provide one or more users with access to the universally acceptable price records for healthcare services.

A server system, comprising:

• a processor, and
• a memory unit comprising machine-readable instructions, the machine-readable instructions when executed by the processor, cause the server system to at least:
• receive user requests from one or more electronic devices via a communication network;
• provide a software application to perform operations, wherein to perform the operations, the server system is caused to:
• receive claims data from one or more data sources over the communication network and generate statistical price records from the claims data;
• receive Machine-Readable Files (MRFs) and other pricing arrangements from the one or more data sources and a database, and generate direct price records from the MRFs and the other pricing arrangements, wherein the database includes an Artificial Intelligence (AI) or Machine Learning (ML) model used in creation and management of healthcare cost management data and in processing of natural language plan documentation;
• receive one or more of payor rate overrides and provider rate overrides from one or more respective devices associated with one or more of a payor and a provider, respectively;
• generate first recommended price records from the statistical price records, and second recommended price records from the direct price records, wherein the statistical price records and the direct price records are each grouped into a plurality of record groups by dimensions and keys, each record group processed individually to generate the first recommended price records and the second recommended price records, respectively, wherein each record group is processed by:
• determining a calculation method for each record group among the plurality of record groups;
• applying the calculation method to the corresponding record to generate the first recommended price records and the second recommended price records;
• select universally acceptable price records from the first recommended price records, the second recommended price records, the payor rate overrides, and the provider rate overrides;
• generate machine-readable files (MRFs) corresponding to the universally acceptable price records, wherein for processing and generation of the MRFs, a data-parallel and scale-out architecture with bespoke data pipelines is utilized;
• perform an adjustment to the universally acceptable price records comprised in the MRFs;
• and
• generate a self-service consumer price shopping tool based on the universally acceptable price records to provide one or more users with access to the universally acceptable price records for healthcare services.