Implementing CDASH standards into data

Implementing CDASH Standards Into Data Collection and Database Design Robert Stemplinger ICON Clinical Research â 2010 Agenda ã ã • • Reasons for Using CDASH Project Outline Implementation Discussion of Results © 2010 Reasons for Using CDASH © 2010 Why CDASH? • Desire to streamline / standardize CRF library and database structures • Develop internal standard as well as maintain sponsor specific standards • Internal Standard – Started with SDTM / “SDTM Aware” – Migrated to CDASH • CRO – Industry wide standard facilitated adoption as internal standard © 2010 Why CDASH? (2) Clinical Database Extract Data incorporating third party data: Labs, ECG, etc (restructuring when necessary) SDTM standards to the extent possible Statistical Analysis Plan CDASH CT CDISC SDTM CT define.xml © 2010 ADaM CT define.xml TLGs SDTM, ADaM, define.xml, TLGs to Client and/or FDA Benefits of CDASH • Push standardization toward the beginning of the clinical trial process, have those standards propagate through to the end • Standard templates reduce time / resources required for CRF/eCRF and database development • Considerably less remapping of raw data structures to SDTM © 2010 Project Outline © 2010 Implementation Team • CRF Design (CRFD) – CRF/eCRF design, CRF/eCRF creation, CDASH expertise • Data Management (DM) – CRF design, database design • Database Administration (DBA) – Database design, database creation • Data Integration and Standardization (DIS) – CDASH expertise, SDTM expertise, Controlled Terminology expertise â 2010 Implementation Package ã Platforms Supported: InForm, RAVE, OC/RDC, OC • Deliverables – CRF • CRF Completion Guidelines / Help text – Database Structures • Data Handling Conventions – Data Validation Specification / Edits – Transformations / Mapping to SDTM • Standard Templates / Modules – Validation vested at the study level © 2010 Implementation Process Maintain Standards Documentation ADMIN CRFD Design CRF Module Build Database Modules DBA Program Edit Checks Create DHC & DVS DM Annotate Module to SDTM DIS © 2010 Map/ Program to SDTM CRF Development Issues • DM – Subject Initials, AGE - EU Data Protection / Privacy • MH – Multiple Iterations / Versions • No verbatim Description text, only body systems • No dates • SU – Disagreement on how best to implement verbatim text versus pre-defined text • SC – Difficult to gain consensus on what should appear on the form â 2010 CRF Development Issues (2) ã DM – Subject Initials, AGE - EU Data Protection / Privacy – Regional Standards • MH – Multiple Iterations / Versions • No verbatim Description text, only body systems • No dates – Settled on form with body systems and verbatim Description text • SU – Disagreement on how best to implement verbatim text versus predefined text – Decision to implement at study level • SC – Difficult to gain consensus on what should appear on the form – Did not implement © 2010 © 2010 © 2010 CRF Completion Guidelines / Help Text • Used CDASH documentation in conjunction with existing standards ã Modified per study requirements â 2010 Database Development • Core team comprised of DM, DB Programming • Three month duration • Did not use Data Collection Field text from CDASH to describe variables • Implemented CDASH recommended variable names – Defined very simplistic naming conventions for additional text fields required for EDC systems • Utilized standard SDTM specification template to populate other variable attributes • Utilized data dictionaries, elements, DVGs to attach controlled terminology © 2010 Database Development Issues ã No major implementation issues! â 2010 Table Name Table Description Target Variable Target Label Data Type DM_STD Demography STUDYID Protocol/Study Identifier $ 200 DM_STD Demography SITEID Site Identifier $ 200 DM_STD Demography SUBJID Subject Identifier $ 200 DM_STD Demography VISIT Visit Name $ 200 DM_STD Demography VISITNUM Visit Number BEST DM_STD Demography VISDAT Visit Date DATE DM_STD Demography VISDATC Visit Date (char) $ 200 DM_STD Demography INIT Subject Initials $ 200 DM_STD Demography DSSTDAT Consent Date DATE DM_STD Demography DSSTDATC Consent Date (char) $ DM_STD Demography BRTHDAT Date of Birth DATE DM_STD Demography BRTHDATC Date of Birth (char) $ DM_STD Demography AGE Age BEST DM_STD Demography SEX Sex $ 200 DM_STD Demography SEX_C Sex (code) $ 200 DM_STD Demography ETHNIC Ethnicity $ 200 DM_STD Demography ETHNIC_C Ethnicity (code) $ 200 DM_STD Demography S_ETHNIC Other Ethnic Group $ 200 DM_STD Demography RACE Race $ 200 DM_STD Demography RACE_C Race (code) $ 200 © 2010 Length 200 200 Discussion of Results © 2010 Development Results • Anecdotal – Positive – Don’t have to start from scratch / copy from one study to the next • Metrics – Four studies – All EDC – ~10-20% reduction in number of hours required to develop CRF and database structures as compared to four “similar” studies put into production without the use of these standard structures © 2010 Development Results (2) Average Hours to Create Deliverables (n=4) Deliverable Non-CDASH Standards (hrs) CDASH Standards (hrs) CRF/eCRF Database Edit Checks 73.25 194.25 253.50 64.35 163.25 203.21 © 2010 Downstream Results • Anecdotal – Positive – Much less manipulation of raw data structures • Metrics – – – – Four studies All EDC platforms Limited implementation of controlled terminology ~32% reduction in number of hours required to create SDTM compliant data sets as compared to four “similar” studies put into production without the use of these standard structures © 2010 Downstream Results (2) Average Hours to Create SDTM Data Sets (n=4) Deliverable SDTM Data Sets © 2010 Non-CDASH Standards (hrs) CDASH Standards (hrs) 89.3 60.1 Future Enhancements / Challenges • Additional CDASH domains – CDASH specific terminology • Protocol Representation Model • Increase number of sponsors who utilize the standard structures © 2010 Strength through collaboration © 2010 31 ... expertise • Data Management (DM) – CRF design, database design • Database Administration (DBA) – Database design, database creation • Data Integration and Standardization (DIS) – CDASH expertise,... Results (2) Average Hours to Create Deliverables (n=4) Deliverable Non -CDASH Standards (hrs) CDASH Standards (hrs) CRF/eCRF Database Edit Checks 73.25 194.25 253.50 64.35 163.25 203.21 â 2010 Downstream... studies put into production without the use of these standard structures © 2010 Downstream Results (2) Average Hours to Create SDTM Data Sets (n=4) Deliverable SDTM Data Sets © 2010 Non -CDASH Standards