esource: a clinical data manager's tale of three studies
DESCRIPTION
‘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.TRANSCRIPT
Maura BeardenClinical Data Manager
DATATRAK International
eSource: Clinical Data Manager’s Tale of Three Studies
Confidential – 2
Agenda
► What are eSource Studies?► Comfort of Paper Source Studies► eSource Case Studies► Challenges of eSource Studies► Benefits of eSource Studies ► Future of eSource
Confidential – 3
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?
Confidential – 4
Comfort of Paper Source Studies
► Familiarity of Paper Source Studies► Standardization of
Paper Source Studies► Security
Confidential – 5
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
Confidential – 6
eSource Case Studies
►Analysis of three studies provides the following information:• Challenges of eSource Studies • Benefits of eSource Studies • Future of eSource
Confidential – 7
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
Confidential – 8
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
Confidential – 9
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)
Confidential – 10
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
Confidential – 11
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
Confidential – 12
Benefits of eSource Studies
► Higher Data Integrity ► Real-Time Data Availability ► Decreased Time for Data
Management Review
Confidential – 13
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
Confidential – 14
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
Confidential – 15
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)
Confidential – 16
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
from Concept to Cure
with DATATRAK ONE
DATATRAK InternationalCleveland, Ohio Bryan, Texas Cary, North Carolina
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