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The Data Driven Healthcare EnterpriseThe Transformation to Value Based, Personalized Healthcare
Brett J. DavisSenior Director, Personalized HealthcareOracle Health Sciences Global Business Unit
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The following is intended to outline our general product direction. It is intended for information purposes only, and may 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.
Roadmaps previously communicated by Phase Forward are subject to Oracle review and amendment.
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“To wrest from nature the secrets which have perplexed philosophers in all ages,
to track to their sources the causes of disease, to correlate the vast stores of
knowledge, that they are quickly available for the prevention and cure of
disease – these are our ambitions.”
- Sir William Osler, 1906
Personalized Healthcare:Bringing a century old vision to reality…
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“Supposing is good, but finding out is better.”
- Mark Twain
…Put More Simply
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A Changing Healthcare Landscape
5© 2010 Oracle and/or its affiliates. All rights reserved. Oracle confidential
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Life Sciences and Healthcare are convergingPredictive, Preventive, Personalized and Participatory Healthcare
HEALTHCAREHEALTHCARELIFE SCIENCESLIFE SCIENCES
“Trial and Error”Healthcare
“Trial and Error”Healthcare
“Evidence Based” Healthcare
“Evidence Based” Healthcare
“Precision”Healthcare“Precision”Healthcare
Blockbusters andmass-production of novel drugs
Blockbusters andmass-production of novel drugs
TargetedTherapiesTargetedTherapies
Increased regulation and
efficacy standards
Increased regulation and
efficacy standards
Analytics
LIFE SCIENCES HEALTHCARE
DNA chemistry and advanced
technology
DNA chemistry and advanced
technology
“Managed” Healthcare“Managed” Healthcare
Paper based Records
Electronic Data Capture
Pharmacovigilanceand Risk Mgmt
Safety atPoint of Care
Electronic Medical Records
Paper basedSystems
Personalized Healthcare
Patient Care and Disease Mgmt
Translational Med
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The Future of the Healthcare Industry Lean. Global. Networked.
A transformation is only possible through the synergy of healthcare information technology (HIT) with scientific breakthroughs in the molecular understanding of disease, novel therapeutics and diagnostics, as well as a redesign of our healthcare delivery models. Leveraging data from multiple sources and diverse populations from across the healthcare system will be essential.
Not only is this approach necessary for providing the “best care for the right patient,” but it has major business model implications for many constituents in the healthcare ecosystem including pharma/biotech, health providers, PBMs and payers, and as a result, their IT strategies.
—Bill Dalton, PhD, MD, President/CEO, Moffitt Cancer Center
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The Future of the Life Sciences IndustryLean. Global. Networked.
Our scientists are working in new ways. By using highly-specialized techniques, we're aiming to design treatments personalized for the unique needs of individual people. Science is making this type of personalized medicine possible for the first time in history… This personalized medicine approach means new opportunities for people who are sick, for physicians and for our shareholders.
…finding new treatments depends on collaboration. No company, hospital, lab, or scientist can do it alone. That's why we've formed partnerships with governments, independent medical and scientific groups, companies and advocates….
—Jeff Kindler, CEO
Pfizer Corporation
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Systemic Collaboration to Improve Health
These systems supported individual silos across the health science ecosystem, but must now provide data for an integrated view
Investment is shifting towards R&D and clinical collaboration, personalized / translational medicine and care management
Increasing demand and capabilities for personalized medicine will drive new business models, including more value-based healthcare
Initial customer investment focused on transactional capabilities (EMR, Claims, EDC, Trial Management, etc.)
The new healthcare delivery paradigm requires collaboration
Patient
Researcher Citizen / Member
Individual / Family
Care Managemen
t
Personalized / Translational
Medicine
Value-BasedHealthcare
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The new drug development paradigmA networked healthcare and life science model
Basic Research Discovery & Development
Point of Care
CROCRO
Source: adapted from DataMonitor
Academia, CRO &
SponsorSponsor Healthcare
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Aerospace transformation… Boeing has rapidly shifted the company to embrace a “network” of partners
Aerospace transformation… Boeing has rapidly shifted the company to embrace a “network” of partners
Partners Across the Globe Are Bringing the Boeing 787 Together
Clinical development transformation… Merck is shifting drug development toward embracing a “network” of partners
Clinical development transformation… Merck is shifting drug development toward embracing a “network” of partners
Merck External Basic Research (EBR) team expects to deliver 25% of early pipeline from external partners by 2013 (Source: Pharma Focus Asia)
The new drug development paradigm
Piramal
PoC Oncology Drug Discovery
Patheon
• Commercial Manufacturing
• Pharmaceutical Dev. Services
PPD
• Vaccine Testing
• Central Lab and Sample Storage
Moffitt Cancer Center
Total Cancer Care
Advinus
Candidate Drugs for Metabolic Disorders
Orchid Chemicals
Bacterial and Fungal Infection Dev
WuXi AppTec
Discovery Chemistry
Ranbaxy
Antifungal and Antibiotic Target Programs
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Patient-centered, collaborative care
Reid, Compton, Grossman, and Fanjiang, Editors, Committee on Engineering and the Health Care System, National Academy of Engineering and the Institute of Medicine, National Academies Press, 2005, pg. 20. Adapted from Ferlie and Shortell, 2001, Improving the quality of health care in the United Kingdom and the United States: A framework for change, Milbank Quarterly 79(2): 281-315
“Care that is safe, effective, patient-centered, timely, efficient, and equitable.”
-- Institute of Medicine, 2001
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What is the data driven healthcare enterprise?
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14Page 14
The Learning Healthcare
Organization
Accountable Care Organizations
Enterprise Quality
Standards
Clinical Effectiveness
Comparative Effectiveness
Automating “Today’s”Healthcare Enterprise
Need for Secure, Interoperable Healthcare Data and Analytics
Impact on HC Transformation /
Value to Healthcare
System
Today
Performance Management
Implications for healthcare providersThis evolution has both clinical and operational implications
Core Transactional Systems
Clinical & Enterprise Integration
Enterprise Data Warehouse
Context Specific Analytics and Applications
Core Systems Requirements:
Today’s “Transactional” Systems Were
Not Designed to Enable this
Transformation
Evidence Based Medicine
Evidence Based Medicine
Value-based, Personalized Healthcare
Value-based, Personalized Healthcare
Trial and Error Medicine
Trial and Error Medicine
15
-Basic / Translational Research
-Clinical Research/Trials
-CER
-Deep Analytics / Informatics
Framework for PHC Enabled by HITAchieving this will create a “learning healthcare” paradigm
“Learning Healthcare” Paradigm Supported by Robust, Interoperable Informatics
-Trustworthy data from EHRs
-Longitudinal Biobank data
-Imaging
Translate guidelines and empirical results into specific process steps
Leverage workflow driven informatics processes to drive to point of care with decision support analytics
Trustworthy data to measure protocol with analytics to track outcomes or deviations
Employ analytics to measure results and teach people, activate patients and transform care
16
-Basic / Translational Research
-Adaptive Clinical Research/Trials
-CER
-Deep Analytics / Informatics
“Learning Healthcare” Paradigm Supported by Robust, Interoperable Informatics
-Trustworthy data from EHRs
-Longitudinal Biobank data
-Imaging
Translate guidelines and empirical results into specific process steps
Leverage workflow driven informatics processes to drive to point of care with decision support analytics
Trustworthy data to measure protocol with analytics to track outcomes or deviations
Employ analytics to measure results and teach people, activate patients and transform care
Health Management PlatformEnterprise Health
Analytics Context Specific Analytics
Existing Clinical
Systems
Novel Research Methods for Enabling Rapid Learning
Networks (e.g. adaptive trial design, signal detection)
Real-time FeedbackReal-time Feedback
Framework for PHC Enabled by HITAchieving this will create a “learning healthcare” paradigm
17
Personalized Healthcare Requires Deep Analytics
Departmental “Dashboards”are Insufficient
DASHBOARDS
• “Visible”
PLUMBING
•Mappings to applications and data transformations take expertise & time
• The technology infrastructure has its own complexities
18
Personalized Healthcare Requires An Integrated View Insights From Combining Clinical, Biomedical, Operational and Financial Data
“How is our nurse overtime policy affecting our ICU quality measures? Patient satisfaction?”
FINANCIAL
HR
SUPPLY CHAIN
CLINICAL
“Do our cardiac care reimbursements reflect our improved quality measures?”
“How many patients with a particular molecular profile and clinical attributes are in our system?”
“INTEGRATED VIEW
ANALYTICS”
“GENOTYPE”“SILO ANALYTICS”
“What’s our overall performance? Our quality performance and cost to deliver that quality?”
19
What does this ultimately mean for a health system?Data and applications must be decoupled for robust use of the data and for applications to draw upon multiple data sources
Fulfill Health Information Request
Health Information Services Agreement For Secondary Use
Health Information RequestAuthenticate
Requester
Transform and Normalize Health Information
Patient Health Information Aggregated for Normalization
Transformed into Information Service Format
Patient Health Information Gathered
Clinical Innovations
Clinical & Operational
Benefit
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Analytics coupled with the right health management platform can support longitudinal careFocus for Today: Citizen/Patient Care Cycle
• Identifying, stratifying and targeting patients• Attracting patients• Improving administrative processes to
– Improve utilisation of resources– Help Patients get treatment– Improve patient experience
Unaware Patient AwarePatient
PatientVisits HC
Professional
GetTreatment
Patient Discharged
Patient is Compliant
Patient is Stable
• Support after discharge• Adherence• Patient monitoring• Supporting patient behavior modification
Health Consumer Gateway
Pre-Acute AcuteIntervention
Post-Acute/DiseaseManagement
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Effective Care Cycle Management Has a Positive Impact on Both Cost and Quality
Source: Intel Corp 2006
Cost of Care/Day
0%10
0%
$1 $10 $100 $1,000 $10,000
Acute CareResidential Care
Home Care
ICU
CommunityHospital
SpecialtyClinic
Assisted Living
Skilled Nursing Facility
Doctor’sOffice
CommunityClinic
Chronic Disease Management
Healthy Independent Living
Qua
lity
of L
ife
© 2010 Oracle Corporation Confidential
These platforms also create opportunities for biopharma industry innovation and novel collaborationReal-time Clinical Information Exchange Across the System
Patient RecruitmentClinical Data
PROVIDERSHospital
Clinics
Bio-banksCRO
Pharma/Biotech
Life Sciences
Clinical Trials
Safety & Pharmacovigilance
Learn
Confirm
Learn
Confirm
HEALTHCAREHEALTHCARELIFE SCIENCESLIFE SCIENCES
For Oracle employees and authorized partners only. Do not distribute to third parties.© 2010 Oracle Corporation – Proprietary and Confidential
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Oracle Health Sciences InstituteIn Partnership With Sun Labs
• Focused on research that will accelerate IT innovation to advance personalized medicine andthe delivery of safe and effective treatments and health care services to patients around the globe
• Works in collaboration with academic research centers. Current collaborations include:• Dana Farber Cancer Center (translational research)• The Cleveland Clinic (cardiac decision support)• St. Francis Xavier University (parallelizing ontological reasoning)
• Focuses on areas fundamental to the challenges facing health sciences organizations. Research priorities include: • Artificial intelligence and semantic technology• Genomic, genetic and phenotypic data analysis• Data mining to support optimization of clinical trials• Predictive algorithms to enable earlier detection of adverse events• Advanced decision support at the point of care
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