With the government taking a more proactive approach to mining Open Payments data to evaluate, investigate, and detect cases of healthcare fraud, pharmaceutical companies are even more keen to proactively stamp out any suspicion of fraud proactively, and they are turning to analytics techniques to do so.

No pharma company wants to find out second hand that their data showed clues and signs to questionable spend, and only learn about them after they have been brought to light. Instead, the companies are using data mining, auto data finders, outlier reporting, etc., to mitigate damage down the road to reduce internal costs and avert increasing regulatory fines.

The Department of Justice (DoJ) is using advanced analytics tools in order to review and initiate investigations. Irrespective of whether data analytics are used by pharma companies for the compilation of information for governmental reporting purposes or to gain access to metrics for internal assessments and reporting, data analytics is now a vital tool to capture, analyze, and use their data in ways that were not possible before.

Data Analytics – How Open Payments Analytics Can Help

There are multiple ways in which pharma companies can benefit from data analytics. Some of these are:

– Identify unexpectedly high payments made to a certain physician or teaching hospital

– Determine payments made outside of the determined Fair Market Value rates

– Identify prescribing patterns and payment trends

– Evaluate potential off-label promotion

– Test the overall correctness of their transparency data prior to CMS submission

– Analyze competitor data

In summary, Open Payments Analytics can help pharma companies understand what is there in their spend data, how it compares to their budgets, what are their payment trends, and spot outliers. With all of this information available to them, pharma companies can further investigate their data anomalies and take the steps required to respond to external stakeholders regarding their spend information.