Abstract: Healthcare intelligence and analytics may be improved by combining sets of disparate healthcare records and matching records between patients. The matched records may then be analyzed by identifying relevant individuals and providing information to a user containing the combined sets of healthcare records and the analysis. The information may be customized for the user after identifying the user accessing the interface. Additionally, rules may be applied to the analyzed data to enhance the data when viewed by the user.

Abstract: A drug registry database is administered by storing healthcare claims for a plurality of patients and providing a user interface that displays new drug/comparator drug pairings in which a new drug includes a threshold number of healthcare claims and a comparator drug with substantially similar medical indications as the new drug. Based on receiving a new drug/comparator drug pairing selection, an analysis engine identifies from healthcare claims a statistically matched first of patients having used the new drug and second group of patients having used the comparator drug; identifies a comparative occurrence of existing medical conditions or new medical conditions in the statistically matched groups; and calculates a probability value indicating a relative likelihood that a patient taking the new drug will have a medical condition from the new or existing medical conditions in comparison to a likelihood that a patient taking the comparator drug will have the medical condition.

Abstract: A system for processing healthcare claims and remittances comprises a database and an electronic portal. The database contains previously received healthcare claims from a plurality of healthcare providers and previously received remittances from a plurality of payers. The electronic portal, connected to the database, receives a healthcare claim from a provider or a remittance from a payer, and splits the received claim or remittance into a plurality of data elements. The portal assigns a unique identifier and a shared identifier to each of the data elements of the received claim or remittance. The portal performs a duplicate claim edit and/or a third party liability edit on the received claim, or performs a duplicate remittance edit an/or a third party payment edit on the received remittance. Based on the result of the edits, the portal submits the received claim to a payer or submits the received remittance to a provider.

Abstract: System and methods for rapid assessment of lab value distributions are provided. In one embodiment, the system includes a data storage device and a server. The data storage device may be configured to store a database comprising one or more records, wherein the records are identified by one or more test codes. The server may receive a medical code, search the database to obtain a first group of records associated with individuals having the medical code, wherein each record of the first group of records is identified by a test code, search the database to obtain a second group of records associated with a control population, wherein each record of the second group of records is identified by the test code, and generate an output comprising a distribution graph on a shared scale from the first and second group of records.

Abstract: Apparatuses, computer program products, and methods for identifying redundancy and consolidation opportunities in databases and application systems are disclosed. In one embodiment, the apparatus may include at least one meta data scanner. The apparatus may also include an enterprise meta data source. The apparatus may further include a meta data repository. The meta data repository receives system-specific meta data from the at least one meta data scanner. The meta data repository may also receive enterprise canonical data model meta data from the enterprise meta data source. The meta data repository may be configured to generate at least one individual system CRUD matrix that may then used to produce an enterprise canonical model CRUD matrix. The enterprise canonical model CRUD matrix may be analyzed by a data mining clustering algorithm. The clustering algorithm may group together modules and database elements that may be redundant and may indicate opportunities for consolidation.

Abstract: A system for processing healthcare claims and remittances comprises a database and an electronic portal. The database contains previously received healthcare claims from a plurality of healthcare providers and previously received remittances from a plurality of payers. The electronic portal, connected to the database, receives a healthcare claim from a provider or a remittance from a payer, and splits the received claim or remittance into a plurality of data elements. The portal assigns a unique identifier and a shared identifier to each of the data elements of the received claim or remittance. The portal performs a duplicate claim edit and/or a third party liability edit on the received claim, or performs a duplicate remittance edit an/or a third party payment edit on the received remittance. Based on the result of the edits, the portal submits the received claim to a payer or submits the received remittance to a provider.

Abstract: A system and computer-implemented method for grouping medical records implements a multi-level analysis of the records. The level of analysis for each record is determined based upon the time proximity of each record to the defining medical procedure or service (anchor procedure) to be analyzed. Once an anchor procedure is identified, claim records are processed to determine whether any of the records should be grouped with the anchor procedure into a procedure episode group (PEG). First, the date of service for each claim record is identified to determine whether the claim record falls within time window. The claim records falling within the window then are assessed to determine whether each claim record is sufficiently related to the anchor procedure (for example, by determining whether the diagnostic, procedure, or episode treatment group coding of each claim record is associated with the anchor procedure).

Abstract: A computer implemented system and method for matching drugs and diseases and generating a weighted relationship between the matched drugs and diseases. The system stores a quantity of patient medical history billing records identifiable as patient prescription claim records and medical claim records. The system also stores a grouping of drug codes and groupings of diagnosis codes. The system is configured to match drugs identified in a specific patient's prescription claim records with diseases identified in the patient's medical claims. The system generates a weighted relationship between the matched drugs and diseases by calculating a link weight in accordance with a preprogrammed formula for each occurrence of the diagnosis codes identified in the patient's medical claims that is identified as associated with the disease identified and the drug upon which the query is being processed. The link weight provides a statistical match association value to each of the matched diseases.

Abstract: A computer-implemented method for profiling medical claims to assist health care managers in determining the cost-efficiency and service quality of health care providers. The method allows an objective means for measuring and quantifying health care services. An episode treatment group (ETG) is a patient classification unit, which defines groups that are clinically homogenous (similar cause of illness and treatment) and statistically stable. The ETG grouper methodology uses service or segment-level claim data as input data and assigns each service to the appropriate episode. The program identifies concurrent and recurrent episodes, flags records, creates new groupings, shifts groupings for changed conditions, selects the most recent claims, resets windows, makes a determination if the provider is an independent lab and continues to collect information until an absence of treatment is detected.