To effectively conduct clinical research and development you need to collect, manage, and visualize clinical and healthcare data – including mHealth data – using a centralized and secure data repository that can be considered the single source of truth. Oracle Data Management Workbench (DMW) is a proven solution that is used by a number of global pharmaceutical and medical device organizations to aggregate and manage clinical data in support of their R&D initiatives. In this SlideShare, we demonstrate how Oracle DMW can quickly enrich and expand the value of clinical data, as well as support enhanced analytics and decision-making.

1. Enriching the Value of Clinical Data with
Oracle Data Management Workbench
August 2017

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About Perficient
Perficient is the leading digital transformation
consulting firm serving Global 2000 and enterprise
customers throughout North America.
With unparalleled information technology, management consulting,
and creative capabilities, Perficient and its Perficient Digital agency
deliver vision, execution, and value with outstanding digital
experience, business optimization, and industry solutions.

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Perficient Profile
Founded in 1997
Public, NASDAQ: PRFT
2016 revenue $487 million
Major market locations:
Allentown, Atlanta, Ann Arbor, Boston, Charlotte, Chicago,
Cincinnati, Columbus, Dallas, Denver, Detroit, Fairfax,
Houston, Indianapolis, Lafayette, Milwaukee, Minneapolis,
New York City, Northern California, Oxford (UK), Southern
California, St. Louis, Toronto
Global delivery centers in China and India
~3,000 colleagues
Dedicated solution practices
~95% repeat business rate
Alliance partnerships with major technology vendors
Multiple vendor/industry technology and growth awards

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Prabha Ranganathan
Director, Clinical Data Warehousing and
Analytics, Perficient
Today’s Presenters
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Srinivas Karri
Director of Product Strategy, Oracle

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• Oracle Data Management Workbench Overview
• Data Management Use Cases
• Next Steps
• Q&A
Agenda

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Clinical Data Management
More than Electronic Data Capture

8. Copyright © 2017, Oracle and/or its affiliates. All rights reserved. |
Safe Harbor Statement
The following is intended to outline our general product direction. It is intended for
information purposes only, and may not be incorporated into any contract. It is not a
commitment to deliver any material, code, or functionality, and should not be relied upon
in making purchasing decisions. The development, release, and timing of any features or
functionality described for Oracle’s products remains at the sole discretion of Oracle.
8srinivas.karri@oracle.com

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Laboratory Data
ePro Data
mHealth/IoT
InForm EDC Bi-
directional query
resolution Aggregate Clean Transform
Clinical &
Operational
Analytics
Medical Review
Study Data
Tabulation
Model Datasets
Oracle Data Management Workbench
Cloud Platform Service
srinivas.karri@oracle.com
EMR/EHR
End-to-End Data
Management
• Single platform for data
cleaning, reconciliation,
and transformations
across multiple source
systems
• Seamless integration
with InForm, TMS, and
external data sources
Accelerate Trial Timelines
• Automation workflow
reduces time from raw
data collection to data
ready for Biostatistics
• Re-usable template
library of data models,
transformations, and
validation checks
Improve Compliance
• Secure data access,
blinding & masking,
version control, and data
lineage traceability
• Faster access to clean
data for more interim
analyses
Biostats
Data Models
ACQUIRE ANALYSIS

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Data Models

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Manage Discrepancies

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Validation Checks

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Exporting, Reporting, Visualizing Data

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Study Setup - Reusability
DMW Approach
• Study Templates
• Library Data Models
• Copy Functionality
 Data Models and Tables
 Transformations
 Validation Checks
 Custom Listings
Business Use Case
• Standard setup at a Study
Grouping Level
• Multiple Standards
• Reuse Setup from One Standard
definition
Oncology
Template
Study 87123 Study 83456 Study 57432 Study 87523

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Data Review and Cleaning
DMW Approach
• Flags and States
• Record level
• Subject visit level
• Transformations
• Filters
• Discrepancy Workflow
• Customized workflow
• Actions and tags
Business Use Case
• Review Data
• Familiar metadata across all studies
• Mark data issues for review and
data correction
• Mark reviewed data
• Set subject visit status
• Set data status
• Ability to review new/changed data

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Study – Review Progress Tracking
DMW Approach
• Flags and States
• Subject Visit
• Record
• Custom Programs
• Transformations
• Validation Checks
• Filters
Business Use Case
• What is clean
• What needs to be reviewed?
• Whose review is needed?
• Status of updates from external
sources

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Study – Milestone Readiness
DMW Approach
• Flags and States
• Transformations and VCs
• Study performance based on
historic data from similar studies
• Discrepancy workflow
• DataSources
Business Use Case
• Status of study
• Ready for a milestone
• Interim submission
• Study lock
• What is pending
• How long will it take to complete
the tasks to reach a milestone

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Where to Go from Here
Next steps
• For those not quite ready yet
– Collaborate on requirements
• For those interested in seeing more of DMW
– Schedule a demo
• Looking to harmonize your business processes?
– Schedule a call to discuss your situation
Competitive advantages & capabilities
• Architectural, technical, and best-practice guidance
for the implementation of DMW
• Gap assessments
• Development of utilities
• Extensive experience implementing and integrating
clinical and PV applications
• Expertise in project management and process
re-engineering
• Technology evaluation and implementation to
support the strategy
• Health checks
• Roadmap development
• 18+ years of helping organizations select, configure,
implement, integrate, and manage Oracle Health
Sciences applications

23. Questions?

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• “Improving the Clinical Data Review Process with
Oracle Data Management Workbench” | Download
• “How to Review, Cleanse, and Transform Clinical
Data in Oracle InForm” | View On Demand
• “How to Load Data More Quickly and Accurately into
Oracle's Life Sciences Data Hub” | View On Demand
Additional Resources
• Perficient.com/SocialMedia
• Facebook.com/Perficient
• Twitter.com/Perficient_LS
• Blogs.perficient.com/LifeSciences