Dianne Weatherall: 2013-04-11

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?

43%

27%

18%

4%4% 2% 2%

Votes

Not understanding SDTM

Not understanding clinical data

Non-standard data

Not enough time/resource

Inadequate review

Protocol design

Company standards

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 Lack of skills 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

Operations

Biometrics

Data Management

Biostatistics

Operations

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 1Study CRF / DB Design aCRF Specs Programming

1 A

Reviewer R1

B1 (domain A)B2 (domain B)EtcReviewer R2

B1B2

Reviewer R2

B1B2

Reviewer R2

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 2Study CRF / DB Design aCRF Specs Programming

1 A

Reviewer R1

B (all domains)

Reviewer R2

C1C2Reviewer R2

C1C2Reviewer R2

Advantages Disadvantages

Consistent mapping across domains

Time consuming

Pressure (updates)

Lack of continuity from CRF design

Inconsistent metadata

TEAM SCENARIO 3Study CRF / DB Design aCRF Specs Programming

1 A

Reviewer R1

Team B (all domains)Reviewer R2

Team B (all domains)Reviewer R2

C1C2Reviewer R2

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 4Study CRF / DB Design aCRF Specs Programming

1 A

Reviewer Team

Team B (all domains)Reviewer Team

Team B (all domains)Reviewer Team

C1C2Reviewer Team

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 tasksExpert 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• 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

QUESTIONS?????????????????????????????????????