HOPS Unveils Industry Breakthrough in Provider Clustering Analysis

Miami, FL – Jan 22, 2010 - HOPS, a leading provider of data analytic tools and products recently announced a revolutionary solution to the intractable industry problem of poor quality "Provider Specialty" data in Fee-For-Service Healthcare Claims. HOPS' Provider Clustering solution offers Healthcare Payers the first opportunity to assign all Providers into meaningful peer clusters, resulting in fewer false positives, new detection possibilities, improved recoveries and lower staffing overhead.

HOPS EVP of Healthcare Business Development, George Rogers explains the importance of HOPS' breakthrough. "All payers are well familiar with the frustrations of the existing poor quality of "Provider Specialty" entries in existing claims data. Using "Provider Specialty" relegates the Payer to sifting through reams of "false positives" resulting from code combinations which don't match the indicated Specialty. Payers must heavily invest staff time in manually validating these false positives or reduce their number through turning off "edits", allowing true fraud, waste and abuse to slip by undetected."

The HOPS Data Processing Engine (HOPS DPE) uniquely enables optimal hierarchical processing techniques to assign all Providers within a large Healthcare Claims data set to meaningful peer groups based upon similar Diagnosis and Procedure coding. HOPS' approach doesn't require pre-selection for a reduced number of Providers or variables, as with other products. And HOPS doesn't compromise computation integrity through less effective, substitutionary techniques. "Having conducted exhaustive research, I can attest that the HOPS solution for Provider Cluster Analysis is the only solution on the market which permits an entire data set to be processed such that all providers and variables are fed into the calculation. This provides payers a rich and more complete result set," explains Gene D'Angelo, HOPS EVP for Product Innovation.

Deriving accurate Provider peer clusters allows Healthcare Payers to make huge gains in both the efficiency and effectiveness of their Program Integrity efforts. HOPS' Provider Clustering solution uncovers unique providers who must be handled differently from the core analytic workstream and immediately flags suspicious provider profiles. Flagging suspicious providers enables analytic teams to focus more investigative efforts at the Provider level, rather than chasing individual claims. HOPS' Provider Clustering provides a better peer benchmark against which Providers can be measured along a host of KPIs and derives an important new measure to be written back into the data against which a host of 2nd order Detection Models can be run. By informing these Detection Models of the improved Clustering IDs, HOPS can dramatically limit false positives, lower staff overhead and permit Payers to "turn on" important edits.

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About HOPS

HOPS (www.hops.com) is a leading provider of data analytic tools and products, utilizing its unique data processing engine to quickly get clients accessing their data for a cost point previously thought impossible. HOPS, which stands for Heuristic Optimized Processing System, is the fastest and most flexible on-demand analysis solution available for large sets of data. HOPS is headquartered in Miami Lakes, FL.