Membership Data Management: The Potential of Automating the Process

Proper management of membership data poses a significant operational challenge for pharmaceutical manufacturers.  Membership data is submitted by Wholesaler, Distributor and GPO (Group Purchasing Organization) customers in the form of “rosters” that are used by Manufacturers to determine eligibility for contract sales when adjudicating chargeback and rebate transactions.  Membership data also serves a second, and equally critical purpose, to assist Manufacturers in designating customer trade class for use in regulated price reporting and sales and marketing activities.

The first challenge in managing membership data is addressing the overwhelming volume of data received.  Most often rosters are sent via email to a processing specialist in the contracts and/or chargeback processing area.  A full listing is provided at the inception of the contract, and then updates detailing additions, changes and deletions to the listing are provided on a periodic basis, typically monthly.  The data then has to be aggregated, cleansed and added to the company’s customer master before it can be used to process transactions.  Even if the member has been previously recorded in the customer master, the accuracy of assignment cannot be guaranteed as a change or deletion may have been submitted by a wholesaler, distributor or GPO client for the current reporting period.

To lend perspective on the volume of members (and corresponding data), take for example a recent study published on GPO membership.  According to Becker’s Hospital Review as of September 2010, the five largest GPOs including Novation, Amerinet, Premier, Broadlane and MedAssets experienced recent growth in membership, totaling over 232,000 members on a combined basis.  Most pharmaceutical manufacturers will contract with several, if not all of these major GPOs.  Now add to that number the total members of the wholesaler and distributor sales channels, and it is not unreasonable to expect that total membership will exceed 200,000 to 500,000 for the average manufacturer.

In addition to the sheer volume of data, another key challenge relates to the quality of data received.  Most often the membership data is submitted in mixed electronic formats and contains only a handful of core elements.  The data includes unique identifiers, such as DEA and HIN numbers, accompanying demographic data elements such as class of trade, mailing address and contact information.  In many cases a manufacturer will receive membership information for the same entity across two or more rosters.   What is the appropriate action when the data is conflicting, especially when the conflict relates to class of trade designation?

Given the potential for data inconsistencies, the most critical challenge is mitigating the compliance risk associated with the use of membership data for regulated price reporting purposes.  In terms of accuracy of trade class designation, the onus is on the manufacturer to validate its accuracy, not on the Wholesaler, Distributor or GPO organizations that submit the data.  The information is often collected from their members and passed through as-is to the manufacturer.

When preparing regulated price calculations, manufacturers are required to use all data available during the reporting period to provide their best estimate for each required price type.  Currently there are a myriad of third-party proprietary data sources available to support validation including the HIN database, the DEA CSA database, the Hayes Directory, the NPI database and the PHS covered entity database to name a few.  Given the prevalence of these third-party proprietary data sources, it begs the question as to whether third party data validation is not just the industry best practice, but perhaps is an “unwritten requirement” for manufacturers.

For further reading on this topic, take a look at our white paper which digs deeper in the issues and proposes an automated process to mitigate the risk, increase quality and decrease effort.

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