Understanding compliance data analytics for the life sciences is vital to pharmaceutical, medical device, and biotechnology companies looking to grow without interruption from ineffective compliance monitoring and negative public relations. In gathering data for required transparency reporting, life sciences organizations are amassing a wealth of information. If they can figure out how to harness the power of that data, then they will have an edge on the competition.
Recently, I presented “Implement Advanced Monitoring Strategies and Leverage Data to Provide Value” at the 7th Annual CBI Compliance Monitoring conference in Philadelphia. My goal was to provide participants with an enterprise view for compliance analytics, explore scenarios to gain actionable insights, and review monitoring strategies.
Here is the path I paved for using compliance data analytics:
Get a Central Repository
Establish processes for centrally collecting and refreshing data and maintaining history. Ideally, organizations have invested in technology that allows for ease of collection and the ability of approved staff to view the information with a click of the button. Organizations must have ways to bring together disparate data, so it can easily be searched and viewed.
Marry Hierarchical Dimensional Data With Compliance Data
This sounds more complicated than it really is. Essentially, life sciences organizations should lay out the organization’s hierarchy, from the C-suite down to those working for department heads. Then, they can match the spend data with each department and individual. This allows everyone to easily see what’s happening in every group.
Leaders in the organization can weed out bad actors or reward good behavior. First, they have to incorporate and compare key performance indicators (KPIs), key risk indicators (KRIs), and key quality indicators (KQIs) for departments and groups at different levels. Of course, the system must allow for visibility for stakeholders as they need it by role, group, and user access.
Employ Timely Data Capture
As an example, spend age analysis allows organizations to review the time between spend creation and spend record completion. The longer the lag time between creation and completion, the more likely the data is inaccurate. As a result, organizations can identify and define limits for acceptable and non-compliant spend aging. Because they already have the hierarchical dimensional data, they can easily monitor behaviors organizationally. Then, they can either remediate non-compliant behavior or promote compliant behavior.
Assign Targeted Compliance Tasks
Targeted compliance has companies assigning group-organized tasks for simplicity and discipline. Then, they can use the tasks to direct expense originators and managers to certify that risk area tasks have been executed and completed. They can even assign the tasks in bulk, so they can accurately and regularly direct groups to execute certification activities at whatever frequency they choose.
Being able to easily view this information permits companies to review the status of certification activities as they are happening. In addition, these quality checks ensure the increased accuracy of reported spend. Also, they can identify the groups with the highest percentage of overdue activities and address the problem swiftly.
Analyze Market Spend
Transparency reporting usually requires organizations to make their data available to the public. This is certainly the case with Open Payments in the United States. The Centers for Medicare and Medicaid Services (CMS) data is published and can therefore be gathered and analyzed. Use CMS data to compare spend type and the nature of payment profiles and trends. This allows life sciences organizations to:
- Benchmark by industry, reporting entity, and market competitors and partners
- Make strategy decisions about future spend
- Determine other entities with spend to the same physicians and organizations
- Compare all spend types (general, research, ownership interest)
Life sciences companies can take advantage of leveraging compliance data analytics. To get the most out of the data they are gathering for transparency reporting, they should invest in tools that allow them to keep a central repository that is easily maintained. Then, they should employ methods for breaking down, assessing, and comparing the data at their fingertips. Using compliance data analytics allows organizations to quickly respond to potential risks, reward and encourage best practices, and make strategic decisions.