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 method for generating healthcare provider quality rating data includes grouping claim records into one or more claim groups, assigning each claim group to a responsible provider, assessing the claim records in each claim group using guidelines for the particular disease or condition, and generating a compliance score for the claim group, wherein the compliance score indicates the extent to which the claim records in the claim group match the guidelines, and generating normalized provider quality rating data. A method for generating healthcare provider cost rating data includes grouping claim records into one or more claim groups, assigning each claim group to a responsible provider, calculating the total cost of each claim group, aggregating the total cost for each claim group, and comparing the total aggregate cost of each claim group assigned to each provider to an expected cost value.

Abstract: Behavioral clustering of providers may be used to identify outliers of a group of providers. Groups of healthcare providers may be built based on analysis of clinical information related to medical treatments. A plurality of subgroups of healthcare providers may be constructed in the groups, based on analysis of non-clinical information related to demographical information. First-level outlier healthcare providers may be removed from a particular group of healthcare providers, and second-level outlier healthcare providers may be removed from a particular subgroup of healthcare providers. The second-level outlier healthcare providers removed from the particular subgroup may remain in a group that contains the particular subgroup.

Abstract: Systems, methods and apparatuses for analyzing healthcare data are disclosed. In some embodiments, a system for analyzing healthcare data may include a data access module configured to access healthcare data. In some embodiments, the system may further include a server in data communication with the data access device. The server may be configured to execute a rule, the rule comprising one or more rule elements, on the healthcare data to create analyzed healthcare data. In some embodiments, executing the rule may include, correlating each rule element with an object model element. In some embodiments, executing the rule further may include, defining the object model elements correlated to the rule elements using one or more localization indexes linked to the accessed healthcare data. In some embodiments, the server is further configured to return the analyzed healthcare data to an output data location.