Pharma companies made $7.15 billion worth of ‘transfers of value’ in 2015 to physicians and hospitals. With all that wealth of industry data made publicly available through the Federal Open Payments program, the Department of Justice (DoJ) and federal and state prosecutors have sprung into action to investigate fraud across the healthcare system.
This treasure trove of industry data is seen by enforcement agencies as a ready resource that can be used to uncover heavy spending and unusual arrangements with specific providers that can assist in identifying questionable and in some cases, illegal activities.
At the moment, the Open Payments system contains information pertaining to 28 million records on $16.8 billion in transactions spanning across 2013-2015.
Spend data for 2016 will be added to the database in June 2017. Prosecutors have already started using Open Payments data in ongoing criminal and civil actions (for example, Tenet Healthcare Corporation, Atlanta Medical Center Inc. and Insys Therapeutics, etc.) and are particularly targeting anti-kickback schemes and false claims.
For the record, investigators specifically look for outliers related to certain activities within data reports. For instance, the spend data for 2015 indicated increased payments to HCPs that were reported as charitable contributions, together with grants to hospitals that were in line with increased sales transactions.
The Case for Spend Data Analytics
As law enforcement agencies work to sniff out clues, are you truly in the position to take the risk and submit spend data that MIGHT be incomplete, inaccurate, or contain outliers and other data anomalies, or would you rather validate your spend report using compliance analytics prior to submitting it to CMS? With rising penalties in place and your reputation on the line, this question needs some serious answers.
As a pharma company, there is a dire need for you to know all there is in your spend data and have the potential to detect exceptions and fraud in your data while also monitoring your spend – and you need to do all of this before the feds coming knocking at your door with allegations.
With data analytics, it will be possible for you to identify issues such as a high volume of payments that have been made to a single physician or teaching hospital and payments made outside of the company determined Fair Market Value rates, etc.
Most importantly, data analytics will also allow you, as a pharma manufacturer, to analyze competitor data for potential risks.
For example, it will be possible for you to check whether the number of interactions that your company is reporting is in line with what similarly sized competitors are reporting? Is there a specific physician or institution that supposedly received a large number of transactions within the industry? In case you identify such elements within your spend data, it will be easier for you to resolve them way before government officials notice them and come to question your transactions.
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