HOPS Provides Thought Leadership on Provider Cluster Analysis

Miami, FL – Aug 23, 2011 - HOPS, a leading provider of data analytic tools and products will present on the company's revolutionary solution to the intractable industry problem of poor quality "Provider Specialty" data in Fee-For-Service Healthcare Claims. Gene D'Angelo, HOPS' EVP of Product Innovation, will provide an in-depth explanation of HOPS' unique solution for Provider Cluster Analysis at the "Medicare/Medicaid Statistics and Data Analysis Conference 2011", sponsored by Health Integrity in Baltimore Maryland on August 23-25. More information on the conference and D'Angelo's presentation may be found at www.mmsdconference.com.

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.

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 run. By informing these Detection Models of the improved Cluster IDs, HOPS can dramatically limit false positives, lower staff overhead and permit Payers to "turn on" important edits.

In his presentation, D'Angelo will instruct conference attendees as to how HOPS 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 computational integrity through less effective, substitionary techniques. "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 richer and more complete result set," explains D'Angelo.

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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.