PREVIOUS NEXT PREVIOUS NEXT Oracle Health Sciences User group September 2013
Slide 1
Data Warehouse
Implementation
September, 2013
Mike Grossman Vice President of
Clinical Data Warehousing and
Analytics
BioPharm Systems
PREVIOUS NEXT PREVIOUS NEXT Oracle Health Sciences User group September 2013
Slide 2
Welcome & Introductions
Mike Grossman Vice President of Clinical Data Warehousing and Analytics BioPharm Systems, Inc.
• CDW/CDA practice lead since 2010
– Expertise in managing data for all phases and styles of clinical trials
– Leads the team that implements, supports, enhances, and integrates Oracle’s LSH and other data warehousing and analytic solutions
• Extensive Oracle Life Sciences Hub (LSH) experience
– 10 years of experience designing and developing Oracle Life Sciences Hub at Oracle
– 27 years in the industry
– 5+ years of experiencing implementing LSH at client sites
PREVIOUS NEXT PREVIOUS NEXT Oracle Health Sciences User group September 2013
Slide 3
Agenda
• Example types of Data Warehouses
• Why use LSH
• Techniques for creating Data
Warehouses
• Challenges
PREVIOUS NEXT PREVIOUS NEXT Oracle Health Sciences User group September 2013
Slide 4
Example Types of Data Warehouses
• Oracle Life Sciences Data Hub (LSH) can be used to prepare data for reporting, analysis, medical review, and data mining.
• One of the more complex tasks for successful cross-study reporting, analysis, medical review, and data mining systems is implementing a warehouse that will withstand the test of time.
• Types of warehouses: – Operational data for clinical operations and data
management
– Exploratory analysis and predictive analytics
– Medical review
– Safety mining
PREVIOUS NEXT PREVIOUS NEXT Oracle Health Sciences User group September 2013
Slide 5
Operational Metrics Data Warehouse
• Oracle Clinical Development Analytics (CDA)
• Dimensional Models proven
• Integration of CTMS, EDC, Project management, and
financial systems
• Is this part of corporate enterprise warehouse strategy?
• Match merge of key entities
• Does it need formal validation and audit?
PREVIOUS NEXT PREVIOUS NEXT Oracle Health Sciences User group September 2013
Slide 6
Exploratory Analysis and Predictive Analytics Stage 1. Data Preparation
(Acquire, Transform, Enhance, Standardize)
Historic Dataset Files
Study Data
EDC data and other
study data Data
Standardization
AE
DM …
Outcomes Stage 3. Analytics & Model Building
Analyze, Define and
Train Model
Stage 4. Deployment & Reuse
Predictive Analysis Components Selection Components
Ad hoc &
Std Analysis
Value Added
Processing
Stage 2. Select & Explore (Acquire, Transform, Enhance, Standardize)
Selection Components
PREVIOUS NEXT PREVIOUS NEXT Oracle Health Sciences User group September 2013
Slide 7
Medical Review Data Warehouse
• Sourced from EDC and other clinical trial data
• Automatically pooled study data
• Dimensional model for cross-study review
• Specialized data marts for patient profile
• Write back functionality for review status tracking
• Graphical review tool, typically Spotfire or Jreview
• Some sort of auditing is required to indicate “What has
changed since I last reviewed this subject ?”
PREVIOUS NEXT PREVIOUS NEXT Oracle Health Sciences User group September 2013
Slide 8
Safety Mining Warehouse
• Many Sources including – Safety System such as Argus
– FDA AERS database
– Clinical Trial data
– Healthcare records
• Specific data marts needed for structured mining and signal management – Empirica Signal and Empirica Topics
• Broad data model for exploratory mining – Oracle Health Sciences Translational Research Center
– Oracle Healthcare Data Warehouse Foundation
PREVIOUS NEXT PREVIOUS NEXT Oracle Health Sciences User group September 2013
Slide 9
Why Use LSH?
• Version control, snapshots, and Auditing
• Multiple environments in a single application
– Development, Test, Production
• Security
• Data Blinding/Unblinding
• Life Cycle Management
• Reusability
• LSH APIS can automate complex tasks such as
– Automatically adding studies to dimensional models
– Automatically generate longitudinal data marts from subject subsets
PREVIOUS NEXT PREVIOUS NEXT Oracle Health Sciences User group September 2013
Slide 10
Techniques for creating a Warehouse
• Within LSH – Using Programs to pool, Conform, aggregate data
– Use generated pooling/conformation tools
• External to LSH – Using data sourced from LSH and/or external sources
– Using Informatica external, store data mart in LSH
– Using PLSQL
• Common tools – Data loads
– Pass-through views
– No coding using reusable components
– Automatic creation of target structures from source
– Familiar use of Oracle tables and views, SAS datasets, Text files
– Automated batch loads (scheduled or triggered by message)
PREVIOUS NEXT PREVIOUS NEXT Oracle Health Sciences User group September 2013
Slide 11
Example Data Warehouse Build Processes (show a
few)
• Conform data from multiple sources to a single format
Conform
• Merge the data from multiple sources into a single structure format
Pool • Evaluate data
for audit, if audit is unavailable
Audit
• Establish facts from pooled data using Audit data to establish SCD
Base Facts • Aggregate base
facts to higher levels of aggregation
Aggregate
PREVIOUS NEXT PREVIOUS NEXT Oracle Health Sciences User group September 2013
Slide 12
Challenges in Warehousing Implementation
• Auditing may not be available
• Appropriate expertise may not be available
• Multiple version of Standards/changing
standards
– For source data
– For target data mart
• Big single corporate enterprise warehouse
balances with special purpose warehouses
• Tracking the process around data review
and signal management
PREVIOUS NEXT PREVIOUS NEXT Oracle Health Sciences User group September 2013
Slide 13
Q&A
PREVIOUS NEXT PREVIOUS NEXT Oracle Health Sciences User group September 2013
Slide 14
Contact Us
• North America Sales Contacts:
– Rod Roderick, VP of Sales, Trial Management Solutions
– +1 877 654 0033
– Vicky Green, VP of Sales, Data Management Solutions
– +1 877 654 0033
• Europe/Middle East/Africa Sales Contact:
– Rudolf Coetzee, Director of Business Development
– +44 (0) 1865 910200
• General Inquiries:
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