CDISC Board of Directors Meeting
10-11 Dec 2007
Creating a Clinical Data
Element Dictionary
A Proposal
Preamble
CDISC has made progress on many fronts
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There is a CDISC “brand”
CDISC has worked on strategies/plans over the years
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Currently a strategy in place
Operational plans/objectives for 2008 in place
2008 budget is in place
Fundamentally change some of CDISC’s approach
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Preamble
This is a discussion first and foremost about
WHAT we will do.
What one thing, if done well and consistently, would
have the most impact on your business?
Ken Blanchard, Mission Possible
What is ‘the pearl of great price.’
If we agree on WHAT, then we can discuss HOW.
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Motivation for the WHAT
What standards work is done today – Lilly example
Lilly Data Element Standards
\\Rodan\rodan.grp\GCDS_EB_PUBLIC
3560 pages in our “Dictionary”
~25,000 variables
It’s all pdf (yuk !!!!)
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Motivation for WHAT
Link to Analysis Dataset Standards
http://corpweb.d51.lilly.com/statmath/CoE/ADS/ADS_st
d.html
Thousands of pages of documentation in our total ADS
specifications
For each study, CROs get hundreds of pages of
requirements that describe the data elements that we
want, variable names, valid values, formats, etc.
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Motivation for WHAT
Dozens of people at Lilly and CROs communicate
using these voluminous documents
CROs have dozens of people mapping data to
company-specific formats, naming conventions, etc.
The CDISC Business Case largely predicated on
eliminating these activities
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Reduce mapping data from one form to another to transfer or to
integrate it.
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Motivation for WHAT
http://www.wikihit.org/wiki/index.php/Main_Page
The Clinical Data Definitions created in WikiHIT are not
completely useful for clinical research studies.
caDSR has some useful elements, but is a bit outdated
and not entirely functional for what is needed for
clinical research studies.
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Too complex in all its detail
NCI EVS has some useful elements, but does not
have all the information and functionality that is needed
by companies involved in clinical research.
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Data definitions do not have all information (e.g. valid values)
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The Language of Clinical Trials
It is more important to share a common vocabulary
than it is to have agreement on common
grammatical rules.
 Content is more important than structure.
Es ist wichtiger, einen allgemeinen Wortschatz, als zu
teilen es Vereinbarung über allgemeine grammatische
Richtlinien haben soll.
A common vocabulary more important for sharing than
understanding of typical rules of grammar.
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CDISC Adoption by Pharma
Make SDTM more useful, implementable
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Need more specificity
Need more definitions on variables – data elements
Standard data elements – this is what FDA wants, what
pharma wants, what CROs want
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FDA under pressure to do something quickly?
CDISC dealing with healthcare, other standards
organizations, etc.
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Don’t let the perfect hold up the good
Need more focus from CDISC
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CDISC Adoption by Pharma
It’s about saving dollars for pharma, CROs and labs by
simplifying interchange of data.
It’s about helping companies and FDA integrate data
from regulated clinical research studies.
CDISC Business case has little to do with healthcare at
this point.
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Motivation for WHAT
Summary
There is an enormous unmet need for more content.
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The CDISC Business Case is largely dependent on well defined data
element standards being broadly available.
Others are playing in this space, but do not meet the
needs of pharma clinical research and regulatory
submissions.
CDISC Terminology Program has primarily focused on
controlled terminology supporting SDTM, but not the
data elements themselves.
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What Is a Data Element?
All the pieces of information (i.e. metadata) needed to
unambiguously describe a concept
English dictionary analogy
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Word – desk
Phonetic spelling – dĕsk
Part of speech – noun
Definition – a piece of furniture with a flat top for writing
[could also be thought of as the concept]
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Source – Latin, discus
etc.
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Data Element
A Data Element is a unit of data for which
definition, identification, representation, and
permissible values are specified by means of a
set of attributes; the smallest unit of data.
The purpose of a data element definition is to
define a data element with words or phrases
that describe, explain, or make definite and
clear its meaning.
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Data Elements – Vertical v. Horizontal
Vertical Data Set Structure
Patient
1
1
1
1
1
1
Visit
1
1
1
2
2
2
Variable
HR
SBP
DBP
HR
SBP
DBP
Value
55
128
84
57
122
83
•Valid Values for Variable are:
HR, SBP, DBP.
•A controlled terminology
•For each ‘term’, provide the
metadata to describe it:
•Definition, units, valid
values, etc.
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Data Elements – Vertical v. Horizontal
Horizontal Data Set Structure
Patient
1
1
Visit
1
2
HR
55
57
SBP
128
122
DBP
84
83
Each variable has a name (terminology) and a
corresponding set of metadata to describe it
(definitions, units, valid values, etc.)
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Clinical Data Element for Pharma
Variable name (draft)
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Label / concept
Valid values of the variable itself
Data type (num, char, date, …)
Units
Key words (e.g. biomarker, osteoporosis, …) – facilitate searches
Source / reference (as needed)
SDTM data domain
Regulatory requirement
[A team needs to define what are the essential metadata pieces of
information that are parsimonious – enough to eliminate ambiguity,
but few enough to be useful, consumable, understandable,
burdenless.]
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Creating a Clinical Data Element
Dictionary (CDED)
Task Force Members
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Steve Ruberg
Bron Kisler
Scott Getzin
Doug Fridsma
Chris Chute
Sue Dubman
Dave Iberson-Hurst
Cara Willoughby
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Proposal – WHAT - Unmet Need
Comprehensive, electronically accessible,
organized dictionary of unambiguous data
element standards for our industry
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One of the most fundamental problems we all face within our own
pharma companies, but even more acutely across the pharma
industry/enterprise.
Consistent with Strategy Theme #2, #5, #6
THE place where people go for clinical data
element standards.
THE thing for which CDISC is known ?!?!
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Alignment and Focus
If additional funding can be secured, standards specific
to therapeutic areas will become part of the extended
CDASH scope.
CDISC Press Release #33
15 May 2007
KEY QUESTION
Given the importance of this area and the need to
move quickly, should we re-prioritize and divert
resources (people and $$) to this effort?
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Alignment and Focus
FOCUS
Where do we focus?
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ISO, AHIC, AHRQ, NLMEc, industry architecture, …
Initial focus on meeting pharma industry needs
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If others want to piggyback on that effort, that is fine.
Initial focus on clinical data and clinical trial metadata
Initial focus on raw/observed data
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There is a lot of territory to conquer within this focus area. Other opportunities
(pre-clinical data elements, derived data elements) can be explored in the future.
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Impact on Other CDISC Teams
Clinical Data Element Dictionary (CDED)
Terminology, SDTM, CDASH, LAB and SEND all
converge into a common approach focused on the data
elements and their exquisite definition
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Reduces need to harmonize CDISC models if they all utilize the
same data element definitions
Harmonization happens “on the front end” rather than after the fact
The transport standard for carrying standardized
content (ODM, HL7, SAS, other???) can be whatever
BRIDG – work continues as is
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Tightly coordinate standard data elements with BRIDG efforts
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Creating a Clinical Data Element
Dictionary (CDED)
Initial Inputs
Content
Standards
Transport
Standards
CDED
SAS
CDASH
SDTM
80%
LAB
Protocol
20%ODM
TB?
CV?
HL7
Other
Existing?
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Proposal
HOW - Business model
An open, electronic, peer production environment with
appropriate governance
Like MedDRA, but open and free
Like Wikipedia, but more governance
Like LINUX, but more granular and dynamic
CDISC must adopt a more flexible and rapid
development process
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Clinical Data Element Standards
Governance
Template
Submission
Review
Final
Anyone
Downloadable (define.xml)
Searchable – text, key words
 search shows status (submit, review, final)
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Governance for the CDED
Governing Board
2 Full-Time CDISC
Employees
Lead 1
Team 1
Lead 1
~ 6-8 SME’s
Lead 2
Team 2
Lead 2
~ 6-8 SME’s
Lead 3 ... Lead k
Team 3
Lead 3
~ 6-8 SME’s
...
Team k
Lead k
~ 6-8 SME’s
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Proposal
WHO - CDISC
CDISC has the opportunity to assert an even greater
leadership role in this arena.
Leverage CDISC’s strengths – Strategy Theme #1
Independence
Consensus building
Strong pharmaceutical / clinical research expertise
Global recognition
Place substantial priority and focus on this effort
“The pearl of great price”
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Proposal
WHEN - ASAP
The time is right to charge ahead aggressively
There is a large, unmet business need
FDA and others are looking for a “content leader”
CDISC has ongoing terminology efforts
Technology is in place (i.e. wikis)
Mindset is in place (i.e. people can work virtually)
Others are advancing on this front and we may be left out
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Budget
Transition personnel to this effort
Continue/finalize ongoing CDASH efforts
Redirect some Terminology Team efforts
Need part-time Governance team members
Contracted for ~25% of their time
SMEs for TA or data domains
Leverage CROs, software members of CDISC
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Summary
There remains a clear need to have unambiguous
clinical data element standards (CDES)
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Considerable efforts still spent on exchanging data
Considerable efforts still spent on integrating data
Needed across the drug development industry
Broad set of data domains (safety, efficacy, outcomes,
PK, etc.)
Independent of strategies related to messaging or
transport technologies
Let’s act decisively and move quickly.
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Benefits of Using Documented CDEs
Facilitates common data collection by defining content and
scope.
Supports semantic data relationships.
Defines valid values for enumerated data.
Improves understanding of data.
Simplifies and documents data analysis.
Provides historical context for data collections.
Encourages reuse of existing data structures.
Facilitates sharing of data across organizational entities.
Facilitates integration of data across studies.
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