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? 1 2 3 Lack of skills Lack of training Expensive It is complicated Too much room for personal preference Customer specific implementations Unclear process Too many cross-functional teams involved Companies are too silo’ed Lack of expert support It takes time and effort to become an expert

ROOT CAUSE OF QUALITY ISSUES Lack of understanding of clinical data – WHY? 1 2 3 Lack of data / clinical skills of teams Clinical data is complicated Highly un-normalized Database structures are often developed for data entry and clinician preference, not CDASH/SDTM standards The CRF changes over time Therapeutic areas have complicated study designs (e.g. cohort changes) Poor planning from the study design stage

ROOT CAUSE OF QUALITY ISSUES Non-standard data – WHY? 1 2 3 Legacy studies SDTM standards are relatively recent Customer specific requirements Customer specific implementations Customer legacy systems are not CDISC-compatible Therapeutic areas have complicated study designs (e.g. cohort changes) Poor planning from the study design stage

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 Operations Biometrics Data Management Biostatistics *** Blur the line between DM and BIOS

BEST TEAM SCENARIO SDTM experts? Programmers? Biostatisticians? Data genius? Cheap? Available?

ROLES AND SKILLS Data collection: CRF design (CDASH / SDTM experts) SDTM mapping: CRF annotation/ specifications (SDTM experts) Programming: (SAS experts) Review: (SDTM + Biostatistics + Data experts) Data Management ----------------------------------------Biostatistics

TEAM SCENARIO 1 Advantages Disadvantages Continuity from aCRF Study CRF / DB Design aCRF Specs Programming 1 A Reviewer R1 B1 (domain A) B2 (domain B) Etc Reviewer R2 B1 B2 Advantages Disadvantages Continuity from aCRF Time consuming SME on certain domains Pressure (updates) Small team Inconsistent mapping across domains Boring Lack of continuity from CRF design Inconsistent metadata

TEAM SCENARIO 2 Advantages Disadvantages Study CRF / DB Design aCRF Specs Programming 1 A Reviewer R1 B (all domains) Reviewer R2 C1 C2 Advantages Disadvantages Consistent mapping across domains Time consuming Pressure (updates) Lack of continuity from CRF design Inconsistent metadata

TEAM SCENARIO 3 Advantages Disadvantages Study CRF / DB Design aCRF Specs Programming 1 A Reviewer R1 Team B (all domains) Reviewer R2 C1 C2 Advantages Disadvantages Consistent mapping across domains Resourcing issue (more people needed), particularly for a submission Less advanced tasks can be done by cheaper resources, freeing advanced programmers for critical tasks Lack of continuity from CRF design Expert group for support

TEAM SCENARIO 4 Advantages Disadvantages Study CRF / DB Design aCRF Specs Programming 1 A Reviewer Team Team B (all domains) C1 C2 Advantages Disadvantages Consistent mapping across domains Difficult to develop/find reviewer skills (for design and mapping) Less advanced tasks can be done by cheaper resources, freeing advanced programmers for critical tasks Expert group for support Continuity of whole process

Other things to consider Submissions Continuity across studies Consistency across studies Change control Bottle necks (reviewer team) ADaM / statistical output resourcing

RESOURCE CRITERIA FROM TO SDTM after design Just save costs Allocate availability TO SDTM during design Invest in expert team Look at continuity

THE BEST SDTM TEAM Expert Reviewer Team (CDASH / SDTM) Team Leader (Biometrics) CRF Designer aCRF / SDTM Mapper Team Programmer(s) *** Understand the data *** Understand the purpose

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