Fraud accounts for 19% of the $600B to $800B in waste in the U.S. healthcare system annually.

Data is to analytics as the tune is to a song – we need one for the other to happen. We need a non-traditional approach to manage the data available in health care industry because of the vast number of claims, clinical and additional information generated and shared through practice management and billing systems, electronic medical records and dispersed data warehouses.

One way to reduce the waste in healthcare system, is to identify suspicious actors involved in committing insurance fraud. But detecting the probable fraudulent activities among millions of claim records is a daunting task.

By surfacing the fraudulent cases, PBMs are ensuring to comply with applicable statutory, regulatory and other requirements, sub-regulatory guidance, and contractual commitments related to the delivery of the Medicare. Having a fraud, waste and abuse program in place benefits CMS, Sponsors, and Medicare beneficiaries because it re-targets Medicare dollars to appropriate uses.

Combining industry knowledge with usage of advanced analytics and machine learning techniques, we created an intelligent system to identify the highly probable fraudulent cases of Opioid overdose and usage. Using investigative intelligence and social media analysis, we can predict even better results with higher probability of fraud detection.