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Using Aggregated Lab Test Results for Pharmaceutical Marketing and Research

Posted Mar 19 2012 12:00am

This is a guest blog by Theo McCormick. He is the Director of RxDx Services, Pharmaceutical & Diagnostics Consulting, Management Science Associates , in Pittsburgh, PA.

For the the readers of this blog, it is established that clinical lab testing has a profound impact on clinical decisions, providing clinicians with information that aids in the prevention, diagnosis, treatment, monitoring and management of diseases. For pharmaceutical organizations, these insights are in the evolutionary infancy as pharmaceutical market researchers...and business intelligence analysts [begin] to understand the dynamics of clinical value, clinical utility, access and reimbursement to build a successful laboratory diagnostics and data strategy that will ensure appropriate uptake of their brand and increase market share. The biopharmaceutical industry is beginning to understanding how the lack of consistent testing in populations needing screening tests, or barriers to access to a specific assay, prevent a clinician from making the best clinical decisions. These issues can decrease appropriate use of a drug and negatively impact a brand.

As the lab industry consolidates and LIS/Billing/EMR systems grow from stand alone single-institution datasets to national interconnected real-time datamarts, the information contained has value beyond the patient - clinician interaction. Pharmaceutical brand teams, health policy makers and payors are becoming increasingly knowledgeable about these large, de-identified laboratory datasets available from various organizations [such as large national reference labs]. HIPAA compliant Anonymous Patient-Level Data (APLD) contains no protected health information. These aggregated results typically include results, payor types, ICD-9 codes and more, all of which can help a brand team optimize targeting criteria and add a new dimension to understanding the market opportunities.

As an example of the power of these aggregated data-sets, we recently examined nearly 3 million HCV Ab assays over 18 months to determine differences in positivity throughout the US. The top 10 cities (as defined by the number of assays) are shown below. Each of these metropolitan areas has at least 1500 physician accounts that contribute to the data. The national HCV Ab positive rate is 6.4%.   Baltimore, Maryland stands out as a metropolitan area with higher then average HCV positive rate.  ZIP Codes that did not align with any metropolitan area (as defined by US Census Bureau) are noted as 'Rural or No Code' and it is notable that the HCV Ab positive rate for this segment of the population is the nations’ highest (see below). As laboratory datasets merge and become larger, lab professionals may see an increase in the interest in their datasets for external use and analysis by biopharma organizations.


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