3rd Quarter 2007

Using Data Analytics for Business Intelligence

By Joe Crosby

The technological advances of the past decade have allowed companies to collect vast amounts of data from a wide range of sources. However, the ability to collect and report data does not always translate into business intelligence, meaning actionable information that promotes positive change in the marketplace. There are many reasons for these failures:

• Data inconsistencies, such as lack of uniformity and missing data;
• Insufficient analytical capabilities, including lack of expertise, inadequate data mining tools, and limited data warehousing capacity; and
• Inadequate distribution methods, such as the inability to generate timely reports or reliance upon a manual distribution process.

Covance's approach to analytics mitigates these challenges through a four-step process:

1. Pinpoint key questions and identify the right data to collect to answer those questions;
2. Leverage a robust system to ensure complete, accurate data sets;
3. Analyze the results reform queries and assess if the data answered the questions; and
4. Distribute the right information to the right audience at the right time.

This approach, combined with expertise in data analysis and familiarity with our clients' marketplace, has helped Covance fashion innovative solutions to client information needs. In one example, a client with a first-in-class product learned there was a perception among physicians that insurers were not covering the product. To address this issue, Covance and the client leveraged Covance's InTeleTracker™ system to mine the patient and provider records (blinded for patient-identifiable information) collected through the administration of the client's support programs, to assess the coverage environment. The data revealed the following:

• More than 84 percent of patients did not have cost-sharing requirements specific to the product;
• Almost 80 percent of patients had coverage for the product; and
• Most of the time, if a patient did not have coverage, it was due to the patient's benefit design and not a product specific exclusion.

Armed with this information, Covance and the client distributed it to key stakeholders.

• The manufacturer's support services sent individual reports to each physician for whom the support program had conducted an insurance verification, listing the coverage outcomes for all of the physician's patients.
• The client launched an education campaign for the sales force to inform them of the favorable coverage and the limited patient cost-sharing requirements.

As a result, providers become more aware of the favorable coverage environment for the client's product.

If you are interested in learning more about how Covance can help your company use data analytics for business intelligence, please contact us at 1-888-COVANCE.