Data analysis was one of the hot topics everyone was discussing at the recent National Healthcare Anti-Fraud Association's Annual Training Conference in Dallas, and I heard some great speakers tackle the issue. For example, Shantanu Agrawal, deputy administrator of the CMS and director of its Center for Program Integrity (CPI), said CMS is considering expanding the Fraud Prevention System (FPS) to target improper billing beyond pure fraud. The FPS, which has been in operation for over three years, uses predictive modeling and data analytics to identify and prevent fraudulent payments before they are made.
Agrawal also spoke about the Healthcare Fraud Prevention Partnership (HFPP), an initiative designed to share fraud data and best practices between the public and private sector. He said the HFPP has had a positive impact at CMS, helping to improve dialogue between the agency and private insurance plans as well as leading to the creation of new payment edits as the result of completed data exchange studies.
Data exchange studies are designed to pool information from private and public sector partners in the HFPP to examine potential fraud hot spots, and three studies are currently underway, with 13 on deck, Alanna Lavelle, health-care fraud project manager at MITRE Corp., said during the conference. MITRE serves as the HFPP's trusted third party, collecting all the data for the studies in a secure environment and providing the results to study participants.
Gejaa Gobena, the head of the health-care fraud unit within DOJ's criminal division, also addressed the topic of data analysis, and said it can help the government spot billing anomalies and provider outliers. Gobena said the government has access to numerous data sources, including Medicare enrollment data, complaint files, bank records, corporate records and medical licensing information.
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