informatics and the clinical and translational science ecosystem
TRANSCRIPT
Integrating Informatics Into The Clinical and Translational Science Ecosystem
September, 2013
Philip R.O. Payne, Ph.D.Associate Professor and Chair, Biomedical Informatics (College of Medicine)Associate Professor, Health Services Management and Policy (College of Public Health)Associate Director for Data Sciences, Center for Clinical and Translational ScienceExecutive-in-residence, Office of Technology Transfer and Commercialization
COI/Disclosures
Federal Funding: NCI, NLM, NCATS, AHRQ
Additional Research Funding: SAIC, Rockefeller Philanthropy Associates, Academy Health, Pfizer
Academic Consulting: CWRU, Cleveland Clinic, University of Cincinnati, Columbia University, Emory University, Virginia Commonwealth University, University of California San Diego, University of California Irvine, University of California San Francisco, University of Minnesota, Northwestern University
Other Consulting/Honoraria: American Medical Informatics Association (AMIA), Institute of Medicine (IOM)
Editorial Boards: Journal of the American Medical Informatics Association, Journal of Biomedical Informatics
Study Sections: NLM (BLIRC), NCATS (formerly NCRR), NIDDK
Corporate: Epic Systems, IBM, Accelmatics (Chief Scientific Officer)
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Outline
Motivation The evolving clinical and translational science ecosystem The role of informatics in clinical and translational research The OSU Center for Clinical and Translational Science (CCTS)
Lessons from the OSU CCTS Next Steps
Emergent needs The importance of implementation science Workforce development
Discussion
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Outline
Motivation The evolving clinical and translational science ecosystem The role of informatics in clinical and translational research The OSU Center for Clinical and Translational Science (CCTS)
Lessons from the OSU CCTS Next Steps
Emergent needs The importance of implementation science Workforce development
Discussion
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Defining Translation
trans·la·tion (noun): an act, process, or instance of translating: as a: a rendering from one language into another; also :
the product of such a rendering b: a change to a different substance, form, or
appearance c: a transformation of coordinates in which the new
axes are parallel to the old ones
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Source: Merriam Webster Dictionary (http://www.merriam-webster.com/)
Basic Science
Clinical Research
Clinical and Public Health
Practice
Clinical and Translational Science (CTS): Translation in the Context of Biomedicine
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KnowledgeGeneration
Common information needs, including: Data collection and
management Integration Knowledge
management Delivery Presentation
Application
ContinuousCycle
T1
T2
Defining Systems Thinking
Systems thinking is the process of understanding how things influence one another within a whole Approach to problem solving where "problems" are
viewed as parts of an overall system Major goal is to avoid development of unintended
consequences as a result of solving problems in isolation Promotes organizational communication at all levels in
order to avoid the “silo” effect
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Source: Wikipedia (http://en.wikipedia.org/wiki/Systems_thinking)
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An Argument For “Translational Informatics”: Bridging Translation and Systems Thinking
Improved Translation
Systems Thinking
Advances in Human
Health
Enabled by Biomedical Informatics
Extending the Argument for Translational Informatics: Current Trends
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Learning Healthcare Systems
• Instrumenting the clinical environment
• Generating hypotheses
• Creating a culture of science and innovation
Precision Medicine
• Rapid evidence generation cycle(s)
• ‘omics’• Analytics/decision
support
Big Data• System-level thinking• Data science
Integrated and High Performing
Healthcare Research and Delivery Systems
Learning from every
patient encounter
Leveraging the best
science to improve care
Identifying and solving
complex problems
Rapid Translation
A Test-Bed: The Center for Clinical and Translational Science (OSU CCTS) was founded
in 2006, and is a collaboration among The Ohio State University (OSU)
All seven health sciences colleges Colleges of arts and sciences, business, and engineering
OSU Wexner Medical Center (OSUWMC) Nationwide Children's Hospital (NCH) Community health and education agencies Business partnerships Regional institutional networks
CTSA funded in 2008
The OSU CCTS provides financial, organizational, and educational support to biomedical researchers, as well as opportunities for community members to participate in credible and valuable research.
Focused on turning the scientific discoveries of today into life-changing disease prevention strategies and the health diagnostics and treatments of tomorrow
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Outline
Motivation The evolving clinical and translational science ecosystem The role of informatics in clinical and translational research The OSU Center for Clinical and Translational Science (CCTS)
Lessons from the OSU CCTS Next Steps
Emergent needs The importance of implementation science Workforce development
Discussion
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Applying a Strategic Framework to Translational Informatics
Dynamic Informatics
Strategy
Anticipating needs
Challenging assumptions
Interpreting “signals”
Translating plans
Alignment
Learning and improving
Anticipating Needs: Simplifying Programmatic Objectives
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Challenging Assumptions: Improving Stakeholder Access and Optimizing Resource Utilization
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Interpreting Signals: Identifying Opportunities for Structural and Functional Improvements
• Regular environmental scans (internal and external)
• Stakeholder surveys (annual)
• Targeted workflow and ethnographic studies
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In this context, an “Ecosystem” = …a community of interacting and highly interdependent actors, resources, and processes, which function as a cohesive and collective whole…
Translating Plans: Leveraging Partnerships and Complementary Capabilities
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Alignment: Making Use of Existing Infrastructure and Pursuing Targeted Enhancements
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Learning and Improving: Measuring Processes and Outcomes and Providing Access to Evaluation Data
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Outline
Motivation The evolving clinical and translational science ecosystem The role of informatics in clinical and translational research The OSU Center for Clinical and Translational Science (CCTS)
Lessons from the OSU CCTS Next Steps
Emergent needs The importance of implementation science Workforce development
Discussion
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Strategies & Future Directions: HIT
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Informatics “translation”
Holistic approach to planning, implementation and management
Adoption of knowledge management practices as a core competency
Transition to agile, lightweight technologies as the “edge” of enterprise systems
• Eliminating traditional boundaries• Focusing on economies of scale
across mission areas• Bridging applied informatics and
HIT practice• Semantics• NLP• Temporal Reasoning• IR• Visualization
• Enabling end-user self service
Strategies & Future Directions: BMI
• Answering people-centric questions:
• Workflow• Usability• Software Design Patterns
• True platform integration:• SOA and Cloud Computing• Semantic web• Knowledge engineering• Visualization and HCI
• Reasoning:• Data mining• Text mining/NLP• Data integration• Knowledge discovery
• Enable all stakeholders to ask and answer questions
• Includes informaticians
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Strategies & Future Directions: Culture Harmonization of regulatory frameworks:
Early successes related to universal bio-specimen collection projects and GWAS/PWAS study paradigms
HIT and BMI must be partners: Technology and methodological silos are major barriers
Socio-technical approach to platform adoption: Adoption means more than being on-time and under-budget
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Innovative Platform
Development
EvaluationServices
Implementation Science: An Opportunity to Balance Science and Service
•Knowledge representation models
•Semantic reasoning algorithms•Novel architectures•Workflow modeling•Human-factors
•Informatics “translation”•Workflow modeling•Human-factors•System-level models of IT
adoption•“Research on research”
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Empowering Knowledge Workers
Driving Biological
and Clinical Problems
Knowledge Workers
Solutions to Real World Problems
Critical Issues: Workflows that enable engagement by Subject Matter Experts Tight coupling of engineering efforts and research programs that can
define driving “real world” problems Facilitation and support of interdisciplinary, team science models
(including basic and translational scientists, clinical researchers, and informaticians)
Incorporation of human and cognitive factors in all aspects of projects
Differentiating Acculturation and Practice
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Steering Wheel
Pedals
Transmission
VS
Familiarity with structure/function Conceptual knowledge Minimal strategic/procedural
knowledge
Emphasis on strategic/procedural knowledge
Demonstrable efficacy and resiliency with regard to practice
Outline
Motivation The evolving clinical and translational science ecosystem The role of informatics in clinical and translational research The OSU Center for Clinical and Translational Science (CCTS)
Lessons from the OSU CCTS Next Steps
Emergent needs The importance of implementation science Workforce development
Discussion
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Data Generation
Application AND Evaluation
of Knowledge
Unification
“4I” Values
Information-Centricity
Focusing on Context
IntegrationConnecting the
Dots
InteractivityEngaging End-Users
InnovationCreating New
Solutions
Proposed ApproachTraditional Model
Data Generation
Application of Knowledge
Linear Translation
Data Focused
ApplicationSpecific
Silos
Engineering Approach to
Design
Leveraging Existing
Technologies
CurrentTrends
Towards a “4I” Approach to Translational Informatics
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Evolution To
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Collaborators: Peter J. Embi, MD, MS
Albert M. Lai, PhD
Kun Huang, PhD
Po-Yin Yen, RN, PhD
Yang Xiang, PhD
Marcelo Lopetegui, MD
Tara Borlawsky-Payne, MA
Omkar Lele, MS, MBA
Marjorie Kelley
William Stephens
Arka Pattanayak
Caryn Roth
Andrew Greaves
Funding: NCI: R01CA134232, R01CA107106,
P01CA081534, P50CA140158, P30CA016058
NCATS: U54RR024384
NLM: R01LM009533, T15LM011270
AHRQ: R01HS019908
Rockefeller Philanthropy Associates
Academy Health – EDM Forum
Acknowledgements
Laboratory for Knowledge Based Applications and Systems Engineering (KBASE):
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Thank you for your time and attention!• [email protected]• http://go.osu.edu/payne