Teradata launches Medicaid Logical Data Model

 

Teradata Corporation, a company focused on big data
analytics, data warehousing and integrated marketing management, 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.

 

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.

 

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.  

 

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 Telecomlead.com Team
[email protected]