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Decoding the
Acronyms in
C l i n i c a l
Data
Standards
Whois
Behind
C l i n i c a l
D a t a
S t a n d a r d s ?
Bi omedi ca
l
Research
Integrated
Domain
Group
Collaborative effort among advocates f o r data standardization.
A Domain Analysis Model.
It's goal i s to standardize domains and structures f o r c l i n i c a l data.
C l i n i c a l
Data
I nt er change
Standards
Consortium
Non-profit organization founded i n 1997.
Sponsored by 32 companies across the globe.
Works to streamline the submission of c l i n i c a l data to the FDA.
Wor l d
Wide
Web
Consor t i um
"International community that develops open
standards" f o r data exchange across the web.
Provides an ideal framework f o r healthcare data
i n i t i a t i v e s .
Decodi ng
The
Acr onyms
Acr onym: SDTM
F u l l Name: Study Data Tabulation Model
Description:
CDISC standard for submitting c l i n i c a l data to the FDA.
Groups data i n t o variables, which can be grouped i n t o domains.
Acr onym: CDASH
F u l l Name: C l i n i c a l DataAcquisition
Standards Harmonization
Description:
Provides a content template for Case Report Forms (CRFs).
Provides collection data for 18 domains.
Acr onym: ADaM
F u l l Name: Analysis Data Model
Description:
Standardizes the display of data for analysis purposes.
Emphasizes principles of data order and organization.
Acr onym: SHARE
F u l l Name: Shared Health And Research
Electronic Library
Description:
Global electronic l i b r a r y for CDISC metadata standards.
Response to FDApressure for a universal metadata repository.
Acr onym: RDF
F u l l Name: Resource Description
Framework
Description:
Aims to translate English i n t o a programming language.
Helps show relationships amongstvariables.
Acr onym: OWL
F u l l Name: WebOntology Language
Description:
B u i l t inside the RDF.
Allows additional classification & description information.
Acr onym: SKOS
F u l l Name: Simple Knowledge
Organization System
Description:
RDF-Based.
Vocabulary for creating terminologies.
Aboutd-Wise
d-Wise works wi t h l i f e science and healthcare organizations to solve t h e i r
business optimization challenges.
d-Wise’s ten-year h i s t o ry of t a i l o r i n g solutions to meet i n d i v i d u a l c l i e n t needs
and d e l i v e r data integration, data warehousing and standards solutions w i t h i n
highly-regulated industries i s rooted i n extensive domain knowledge of SAS
software, c l i n i c a l drug development and c l i n i c a l data standards l i k e CDISC.
Our solutions f o r c l i n i c a l t r i a l optimization, metadata management, and c l i n i c a l
standards provide a s o l i d foundation f o r extracting accurate business analytics,
enabling c r i t i c a l business decisions to be made r a p i d l y and based on a l l the data.
W ithin the healthcare arena, d-Wise provides data optimization f o r actuarial,
quality, medical-management, and operational data marts and warehouses, as well
as support f o r fraud detection using data-driven and repeatable processes.

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Decoding the Acronyms in Clinical Data Standards

  • 1. Decoding the Acronyms in C l i n i c a l Data Standards
  • 2. Whois Behind C l i n i c a l D a t a S t a n d a r d s ?
  • 3. Bi omedi ca l Research Integrated Domain Group Collaborative effort among advocates f o r data standardization. A Domain Analysis Model. It's goal i s to standardize domains and structures f o r c l i n i c a l data.
  • 4. C l i n i c a l Data I nt er change Standards Consortium Non-profit organization founded i n 1997. Sponsored by 32 companies across the globe. Works to streamline the submission of c l i n i c a l data to the FDA.
  • 5. Wor l d Wide Web Consor t i um "International community that develops open standards" f o r data exchange across the web. Provides an ideal framework f o r healthcare data i n i t i a t i v e s .
  • 7. Acr onym: SDTM F u l l Name: Study Data Tabulation Model Description: CDISC standard for submitting c l i n i c a l data to the FDA. Groups data i n t o variables, which can be grouped i n t o domains.
  • 8. Acr onym: CDASH F u l l Name: C l i n i c a l DataAcquisition Standards Harmonization Description: Provides a content template for Case Report Forms (CRFs). Provides collection data for 18 domains.
  • 9. Acr onym: ADaM F u l l Name: Analysis Data Model Description: Standardizes the display of data for analysis purposes. Emphasizes principles of data order and organization.
  • 10. Acr onym: SHARE F u l l Name: Shared Health And Research Electronic Library Description: Global electronic l i b r a r y for CDISC metadata standards. Response to FDApressure for a universal metadata repository.
  • 11. Acr onym: RDF F u l l Name: Resource Description Framework Description: Aims to translate English i n t o a programming language. Helps show relationships amongstvariables.
  • 12. Acr onym: OWL F u l l Name: WebOntology Language Description: B u i l t inside the RDF. Allows additional classification & description information.
  • 13. Acr onym: SKOS F u l l Name: Simple Knowledge Organization System Description: RDF-Based. Vocabulary for creating terminologies.
  • 14. Aboutd-Wise d-Wise works wi t h l i f e science and healthcare organizations to solve t h e i r business optimization challenges. d-Wise’s ten-year h i s t o ry of t a i l o r i n g solutions to meet i n d i v i d u a l c l i e n t needs and d e l i v e r data integration, data warehousing and standards solutions w i t h i n highly-regulated industries i s rooted i n extensive domain knowledge of SAS software, c l i n i c a l drug development and c l i n i c a l data standards l i k e CDISC. Our solutions f o r c l i n i c a l t r i a l optimization, metadata management, and c l i n i c a l standards provide a s o l i d foundation f o r extracting accurate business analytics, enabling c r i t i c a l business decisions to be made r a p i d l y and based on a l l the data. W ithin the healthcare arena, d-Wise provides data optimization f o r actuarial, quality, medical-management, and operational data marts and warehouses, as well as support f o r fraud detection using data-driven and repeatable processes.