Teradata Creates Innovative 'First' for Social Services: State Health-Human Services and Medicaid Logical Data Model

DAYTON, Ohio, Aug. 3, 2011 /PRNewswire/ -- Teradata Corporation (NYSE: TDC), the world's largest company focused on big data analytics, data warehousing and integrated marketing management today announced the general availability of a new Medicaid Logical Data Model (MC-LDM).  The MC-LDM enables state Medicaid agencies and Health and Human Services (HHS) departments to rapidly and effectively implement an innovative 'person-centric' HHS data warehouse. Designed to provide a focus on the recipient from a single point of view, states can better integrate, centralize, analyze and interpret Medicaid claims and other program data while understanding the program's overall success in accomplishing its mission.

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The MC-LDM is based on Teradata's Healthcare Logical Data Model (HC LDM), extending the payer- and provider-focused subject areas to relevant state assistance programs such as Medicaid, Temporary Assistance to Needy Families (TANF), Supplemental Nutrition Assistance Program (SNAP), Women Infant and Children programs (WIC), Long-Term Care, State Children's' Health Insurance Programs (SCHIP), Mental Health and Long Term Care, among others.

One of the most valuable benefits of the MC-LDM is that it structures state Medicaid and social services program data so that agency users have something they may not have had before – an integrated view of the recipient across programs and services.

"The beauty of the LDM is that it provides important visibility to the individual Medicaid recipient, who can be viewed across multiple programs as a single entity," said David Scott, vice president, Teradata Government Systems. "This is really much more than a foundation for a data repository in the Medicaid claims area; it is also the first step in a greater vision – to expand the data warehouse beyond the Medicaid program and create an integrated analytic foundation which supports all state HHS programs."  

Scott added that a number of states have implemented data warehouses to identify and control fraud; however, very few have extended their data systems to the level of a true enterprise data warehouse, integrating data across multiple programs and agencies.  

"Often, an obstacle is understanding where and how to start," he said. "The MC-LDM can provide a roadmap and a data strategy to phase in a comprehensive state-wide data warehouse over time."

Teradata has built its success on the premise that the real value of enterprise data is gained from data integration and analytics at the detail level. Teradata solutions have historically delivered strong ROI on analytic platforms – and today these platforms have evolved to accommodate very large sets of data. These data sets can be economically stored, integrated and analyzed for improved insight, better decisions and lower costs.

"By leveraging the MITA (Medicaid Information Technology Architecture) development and our vast experience with top healthcare organizations, our new LDM contains very flexible and elegant data structures that support state Medicaid agencies, human services organizations and policymakers," Scott said. "The MC-LDM contains core constructs to support both administrative claim and clinical data."

Relevant news links

• More insight on the growing use and important role of LDMs and models
• Teradata Government industry information web page
• Teradata Healthcare-Life Sciences information web page
• Report to the President: Every federal agency needs a big data strategy

About Teradata

Teradata Corporation (NYSE: TDC) is the world's largest company focused on raising intelligence through data warehousing, big data analytics and integrated marketing management. Our customers trust Teradata's innovative products and services expertise to deliver measurable business value. Please visit teradata.com for details.

Teradata is a trademark or registered trademark of Teradata Corporation in the United States and other countries.

SOURCE Teradata Corporation

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