‘eSource: A Clinical Data Manager’s Tale of Three Studies’ highlights the challenges and benefits of eSource studies, and a look to the potential future. With the continuing adoption of eClinical solutions in clinical research, the need to understand, address, and utilize the time and cost savings benefits of eSource will grow increasingly important.

1. Maura Bearden
Clinical Data Manager
DATATRAK International
eSource: Clinical Data Manager’s
Tale of Three Studies

2. Confidential –
Agenda
► What are eSource Studies?
► Comfort of Paper Source Studies
► eSource Case Studies
► Challenges of eSource Studies
► Benefits of eSource Studies
► Future of eSource
2

3. Confidential –
eSource Studies
► eSource studies pertain to clinical trials
where direct data entry into an electronic
data capture system (EDC) is used in
contrast to paper source studies where
data is transcribed from the paper source
into EDC.
► Why are companies moving toward
eSource studies?
3

4. Confidential –
Comfort of Paper Source Studies
► Familiarity of Paper Source Studies
► Standardization of
Paper Source Studies
► Security
4

5. Confidential –
eSource Case Studies
► Three Different eSource Studies
► Study 1:
• Phase 2, 160 subjects and 24 sites
► Study 2:
• Phase 3, 400 subjects and 31 sites
► Study 3:
• Phase 2, 210 subjects and 20 sites
5

6. Confidential –
eSource Case Studies
► Analysis of three studies provides the
following information:
• Challenges of eSource Studies
• Benefits of eSource Studies
• Future of eSource
6

7. Confidential –
Challenges of eSource Studies
► Workflow process between monitoring and
data management
► Protocol-Specific system checks
► FDA Guidelines pertaining to data
originator elements for transcribed
assessments
► Site Compliance of FDA Guidance of
electronic source data
7

8. Confidential –
Challenge of Workflow Process
► Workflow process between
monitoring and data management
• Study: Cross-comparison of all three
studies
• Problem: How to document the review
between monitors and data
management
► Solution: Additional data review flag
8

9. Confidential –
Challenges of Protocol-Specific
Checks
► Protocol-Specific System Checks
• Study: Progression of all three studies
• Problem: Number of protocol-specific system
checks
► Solution: Identification of integral protocol
checks, help prompts and additional
electronic case report forms (eCRFs)
9

10. Confidential –
Challenges of FDA Guidelines
► FDA Guidelines pertaining to data
originator elements for transcribed
assessments
• Study: Study 3
• Problem: Coordinator entering information
into eCRF that is being read off by PI and the
conflict with the data originator in EDC.
► Solution: additional review fields on eCRF
that correspond to authorized data
originator
10

11. Confidential –
Challenges of FDA Guidance
► Site Compliance of FDA Guidance of
electronic source data
• Study: Study 1
• Problem: Sites writing study information on
paper
► Solution: Note-to-File regarding paper
sources and retraining of site
11

12. Confidential –
Benefits of eSource Studies
► Higher Data Integrity
► Real-Time Data Availability
► Decreased Time for Data Management
Review
12

13. Confidential –
Higher Data Integrity Benefit
► Higher Data Integrity
• No queries needed to correct transcription
errors between paper source and EDC
• Protocol-specific edit checks in the system
and eCRF prompts prevent subjects who are
not qualified from being randomized in the
study
13

14. Confidential –
Real-Time Data Availability Benefit
► Real-Time Data Availability
• Allows for all information to be available at
any time
• Reduce review time querying site to enter
information
• Allows for real-time reports with all available
data
14

15. Confidential –
Decreased Time for Data Mngt
Review
► Decreased Time for Data Management
Review
• Reduced number of confirmation queries
• Limits data management review to cross-
checks and traditional data management
reviews
• Remote monitoring (increased importance)
15

16. Confidential –
The Future of eSource
► Familiarity and optimization of start-up and
workflow process of eSource studies
• Familiarity and optimization can be seen in an
analysis of study 2 and study 3.
–Decreased study deployment time
–Distinct data review responsibilities for data
managers and monitors
–Streamlining user errors
16

17. from Concept to Cure
with DATATRAK ONE
DATATRAK International
Cleveland, Ohio
Bryan, Texas
Cary, North Carolina
888.677.DATA (3282) Toll Free
www.datatrak.com
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