Abstract: Data is received that characterizes a plurality of procedures for a single event. Thereafter, one or more dynamically determined groups are associated with the plurality of procedures, the dynamically determined groups being generated from similarity metrics derived from a plurality of historical procedures for a plurality of historical events. A likelihood of the plurality of procedures being associated with the single event can then be determined based on the associated one or more dynamically determined groups. This determined likelihood can be used to determine whether the data is indicative of fraud. Related apparatus, systems, techniques and articles are also described.

Abstract: Data characterizing one or more healthcare insurance claims is received. Each claim comprises variables characterizing aspects of a healthcare service for which reimbursement is sought. The healthcare services being initiated by a single healthcare service provider for a single patient. Thereafter, score variables from the variables of the healthcare insurance claims are generated. Based on these score variables, it is determined whether a presence of one or more of the variables in more than one of the healthcare insurance claims is indicative of fraud or error based on levels of co-occurrence of the one or more pairs of variables in historical healthcare insurance claims being initiated by a single healthcare service provider. Subsequently, notification that the one or more of the healthcare insurance claims are indicative of fraud based on a positive determination is initiated (to allow, for example, a user to manually review the healthcare insurance claims, etc.).

Abstract: Data is received that characterizes a plurality of procedures for a single event. Thereafter, one or more dynamically determined groups are associated with the plurality of procedures, the dynamically determined groups being generated from similarity metrics derived from a plurality of historical procedures for a plurality of historical events. A likelihood of the plurality of procedures being associated with the single event can then be determined based on the associated one or more dynamically determined groups. This determined likelihood can be used to determine whether the data is indicative of fraud. Related apparatus, systems, techniques and articles are also described.

Abstract: A healthcare insurance claim that includes variables characterizing aspects of a healthcare service for which reimbursement is sought is analyzed in order to determine whether there are any aspects that are indicative of fraud or error. This analysis includes generating score variables from the variables of the healthcare insurance claim and determining whether a presence of one or more of the pairs of variables is indicative of fraud or error based on levels of co-occurrence of the one or more pairs in historical healthcare insurance claims. If a positive determination occurs, then the healthcare insurance claim can be flagged or elevated for review by a user. Related techniques, apparatus, systems, and articles are also described.