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An exploration of quality gaps in SDTM implementation activities and ideas on how to address these gaps through appropriate resourcing. Dianne Weatherall: 2013-04-11. GOAL. Adoption of CDISC standards has led to: new processes ( aCRF , metadata, programming) new responsibilities
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An exploration of quality gaps in SDTM implementation activities and ideas on how to address these gaps through appropriate resourcing Dianne Weatherall: 2013-04-11
GOAL • Adoption of CDISC standards has led to: • new processes (aCRF, metadata, programming) • new responsibilities • Goal: to discuss the “best” SDTM team to implement the new process
DEFINE THE PROBLEM Define what is wrong with the current setup
ROOT CAUSE OF QUALITY ISSUES Poll on the SDTM LinkedIn group:What is the primary cause of quality issues in SDTM?
ROOT CAUSE OF QUALITY ISSUES Lack of understanding of SDTM – WHY?
ROOT CAUSE OF QUALITY ISSUES Lack of understanding of clinical data – WHY?
ROOT CAUSE OF QUALITY ISSUES Non-standard data – WHY?
SUMMARY OF ROOT CAUSES Company silo’s Lack of data skills of Biostats teams Lack of CDASH / SDTM skills of Data teams Time and effort to build expertise Customer-specific Poor study planning Expensive - join a user group!
CRITERIA FOR THE BEST SDTM TEAM Corporate structure Team scenarios
CORPORATE STRUCTURE *** Blur the line between DM and BIOS
ROLES AND SKILLS Data Management ----------------------------------------Biostatistics
Other things to consider • Submissions • Continuity across studies • Consistency across studies • Change control • Bottle necks (reviewer team) • ADaM / statistical output resourcing
THE BEST SDTM TEAM *** Understand the data *** Understand the purpose
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