Big Data Challenge – From EMR’s to Translational Research
Miroslav Končar, PhD
Oracle Healthcare Business Development Director
© 2012 Oracle Corporation
– Proprietary
and Confidential
HL7
Croatia
Chair, Associate Professor for Biomedical Informatics
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What is Big Data
Why it is important for Healthcare Providers Now
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MIT Big Data Definition
What kind of big are we talking about here?
Big Data: The management and use of ultra-large amounts of information
Management and use = efficient storage, search, analysis, visualization
Ultra-large = >1Petabyte
5 million bytes (megabytes)
Complete printed works of Shakespeare
20 billion bytes (gigabytes)
Complete recorded works of Beethoven
10 trillion bytes (terabytes)
Printed works in the Library of Congress
2 quadrillion bytes (petabytes)
Google Earth information managed today
Typical person’s EHR
600 petabytes-10 exabytes
(exabyte = billion gigabytes)
1.5 million
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~1MB healthy young, no images
40MB middle-aged w/health issues, no images
3-5GB with several health issues w/images
Estimated size of current US digitized patient data
• U.S. Healthcare data is
growing by 15 Petabytes
a day – currently
• Up to 80% of healthcare
data is currently
unstructured.
Estimated different medical devices (WHO)
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Where Are Your Big Data Opportunities?
Lower care cost and raise care quality
Chronic Disease Mgt.
Care Patterns
Population Health
Pay for Performance
Telemedicine
Patient Advocacy
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Customer Satisfaction
Disease Mgt. / Prevention
Social Media Interactions
Care / Process
Improvements
• Marketing / Branding
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Operational
Excellence
Patient Engagement
Accountable Care
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Capacity Management
Staffing Optimization
Protocol Optimization
Process Efficiency
Supply Standardization
Cost Accounting
Personal & Translational
Medicine
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Personal Preferences
Individualized Treatment
Biometrics
Data Management
Apply Research
New Clinical Protocols
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Why Oracle for Big Data
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Big Data: Oracle’s Definition
Large volumes, high change velocity, complex variety, unknown value per byte
The
Four
V
s
• Emerging sources of data, ie. sensor, machine generated, social, images, unstructured, etc., that exhibit
any or all of “the four V’s”, potentially integrated with “traditional” structured data
• Healthcare providers can acquire, organize, process, analyze massive amounts of data, primarily through
the use of scale-out on low-cost hardware, non-relational data models, APIs
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Oracle’s Leadership Across the Entire Healthcare
Ecosystem Provides Us Unique Design Insights
R&D
Productivity
Discovery
Research
Translational
Medicine
Diagnostics
Pharma/Biotech
Medical Devices
Quality
& Safety
Clinical
Research
Personalized
Care
Care
Delivery
Care
Management
Participatory
& Preventive Care
Population/
Global Health
Outcomes
“Value-based” healthcare
Leading provider in:
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BioPharma
Clinical Trials
Translational Research
Healthcare Insurers
CMS
HIE & Insurance Exchanges
Population Health Mgt.
Healthcare Data Models
Healthcare Analytics
Interoperability
Identity & Security Mgt.
Collaborating across the life sciences and healthcare industries
improves care, lowers costs and delivers greater value
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Our Translational Research Center (TRC) Can Be
Added For Those Involved in The Research Domain
Discovery
TRC accelerates
discovery
Strategic
Development
Partners
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Diagnosis
Therapy
Wellness
Analytics extend into care delivery & daily life
Strategic
Development
Partners ?
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Customer Success Story
Erasmus MC, The Netherlands
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Erasmus MC
• Erasmus Overview
– The biggest Dutch University Medical
Centre located in the City of Rotterdam
– A 1.200-bed, 1.4BUS$ operational
budget, 12.000 employees
– Erasmus MC is one of the top 40 best
research institutes of the world
• Long years an Oracle customer
– Full ERP (financials, procurement, HR,
learning management), Performance
Management
– Technology – Database, Fusion
Middleware
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Translational Research in Erasmus
• Today - Clinical genetic testing is typically done
for patients who are considered at risk of
carrying genetic variations that are linked to a
particular disease or disease predisposition.
• Next step - all variants in coding and non-coding
DNA is mapped at once.
• The vast amount of knowledge that is offered by
whole-genome sequencing can provide the
scientics with new oppprtunities for disease
management
• Barrier – how to manage vast amounts of data in
real time, and manage all risks associated
(security, perfromance, etc)
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HuVariome Database – Business Problem
• Genome sequencing is time and resources demanding process
– Complete human variants per sample generate 1.5TB of data
• Need to provide overview of all variants in genetically defined populations
– Variations are displayed in the context of public knowledge
– Statistical quality measure for variants
– Disease association and functional impact
• Provide easy access to translational research scientists
– Simple search web page to access variation data
– Summary reports for disease association
– Cytogenetic visual representation of variations
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Why Oracle Exadata
Data storage is 10x smaller, Scanning process is 2000x faster
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Conclusion
• Complete genomics offer new
opportunities for disease management
– Identifying novel DNA variants relevant for
Dx and therapy
– Companion diagnostics for targeted
therapy
• Key areas of research – cancer
conditions
• Visit Erasmus and HuVariome project at
– http://www.erasmusmc.nl/
– http://www.youtube.com/watch?v=KVvVs2
SVfHU
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miroslav.koncar@oracle.com
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