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Alliance Life Sciences Study Advocates Automated Membership Management For Mitigating Compliance Risk
 
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Alliance Life Sciences Study Advocates Automated Membership Management For Mitigating Compliance Risk  
 
   
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Wednesday, November 27, 2013 Alliance Life Sciences Consulting Group (ALSCG), an innovative management and technology consultancy, today announces the release of a White Paper examining the key challenges for pharmaceutical manufacturers in properly managing automated membership data in order to improve efficiency, increase consistency and ensure accuracy. Manufacturers can achieve these goals by utilizing data standardization, data enrichment and automation of membership validation procedures.






“The biggest challenges in managing membership data are addressing the overwhelming volume received and the quality of it,” says Jim Burke, senior vice president, Contracting and Pricing Solutions. “Usually, the membership data is submitted in mixed electronic formats and contains only a handful of core elements. 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.”

According to the ALSCG paper, data enrichment yields the most robust insights because it tells the whole story about a given member and gives the user the ability to quickly compare all aspects reported for a specific member. Automated membership data management significantly reduces the error-prone manual effort and directly increases profitability margins. For example, an automated process has been proven to deliver significant benefits, including:

Enhanced revenue by avoiding discounts provided to ineligible recipients

Improved efficiency and reduced costs by automating manual processes

Reduced risk by avoiding potential Best Price calculation inaccuracies

Burke adds, “The additional time that is conserved as a result of the automation can be realigned to higher value processes throughout the organization. Manufacturers can improve accuracy in Class of Trade assignments by incorporating different data sources, and significantly reduce the manpower and time required to process the data.”



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