Consistency modeling of healthcare claims to detect fraud and abuse
US8639522B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 16, 2008 |
| Grant date | Jan 28, 2014 |
| Priority date | — |
| Expiry date | Nov 26, 2031 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02A90/10
- WIPO fieldIT methods for management
- WIPO sectorElectrical engineering
Abstract
Transaction-based behavioral profiling, whereby the entity to be profiled is represented by a stream of transactions, is required in a variety of data mining and predictive modeling applications. An approach is described for assessing inconsistency in the activity of an entity, as a way of detecting fraud and abuse, using service-code information available on each transaction. Inconsistency is based on the concept that certain service-codes naturally co-occur more than do others. An assessment is made of activity consistency looking at the overall activity of an individual entity, as well as looking at the interaction of entities. Several approaches for measuring consistency are provided, including one inspired by latent semantic analysis as used in text analysis. While the description is in the context of fraud detection in healthcare, the techniques are relevant to application in other industries and for purposes other than fraud detection.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.