feam 2016-big data big health
TRANSCRIPT
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BIG DATA & BIG HEALTH
PERSONALIZED MEDICINE AS A PARADIGM SHIFT
University of Twente, Enschede
University Medical Center
Groningen
The Netherlands
FEAM Bern
May 20th 2016
Lisette van Gemert-Pijnen
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The University of Twente is noted for:
• Excellent education & research
• New technology as a catalyst for change, innovation and progress
• Combination of technology & social sciences
• Entrepreneurial attitude
Themes: ICT, Nano-, Bio-, Geo-Engineering, Management, Behavioral Science
26/08/2016
OUR PROFILE: HIGH TECH HUMAN TOUCH
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• What are the paradigm shifts in Healthcare?
• What are the challenges? Value creation of Big Data
• What are we doing? Our new research projects
THIS TALK
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1. People-centered versus disease-centered
• Health as the ability to adapt and to self-manage, (Huber, 2011)
• Function oriented; self-management; resilience
• No one size fits all
2. Medicine digitized, unplugged, democratized
• Bottom up
• From hospital to self-organizing communities (resilience)
PERSONALIZED MEDICINE VS PERSONALIZED HEALTHCAREPARADIGM SHIFTS
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BOTTOM UP MEDICINE
Eric Topol, 2015
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Amount of data is growing explosively
3. Breaking the wall of knowledge
4. Health Industry blurs medicine
DATA DRIVEN SOCIETYPARADIGM SHIFTS
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5. Pervasive tech: breaking wall of connectivity
• A fusion of Technologies (mobile health environments)
• Cloud based Healthcare Information Technology
6. Science: tech to collect, store, analyse, interpret data
• Flow of data management; Safety, security (e.g. Personal Health Train)
• Age of Algorithms: real-time personal coaching (UT/UMCG)
DATA DRIVEN HEALTHCAREPARADIGM SHIFTS
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The datification of our world gives us
boundless data in terms of Volume,
Velocity, Variety and Veracitiy
Advanced analytics allows us to
leverage all types of data to gain
insights and add Value
Marr 2015
CHALLENGE: BIG DATA; NOT ALL DATA IS BIG
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BIG DATA-BIG INSIGHTS? DATA WISDOM
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WHAT ARE THE CHALLENGES? SOME EXAMPLES
VALUE OF BIG DATA
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SMART HOMES, SMART COMMUNITIESVALUE: DIGITAL EMPOWERED CITIZENS
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VALUE: MEANINGFUL Real-Time FEEDBACK
BOTTOM–UP MEDICINEDATA GENERATED BY PATIENTS; 24 H MONITORING
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Super surveillance…Smart Blood to track 24h, everywhere
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Big data hubris
missing swine flu (2009),
the peak of flu season (2013)
VALUE: Need for Prediction models
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COMPUTERS WITH ATTITUDE NOT ON THE HORIZON
It Was A Bad Idea For Watson The Supercomputer To Learn The Urban
Dictionary…
Value: Sense making Communication (NLP, contextualized)
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• Big Data experts ’views
• Psychology
• Philosophy
• Computer Science
• Business Administration
• Law
• Data Science
• HCWs’ experiences
• Cardiology
• Microbiology
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WHAT ARE WE DOING? SOME EXAMPLES
DIGGING INTO THE VALUE OF DATA
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Profiling
• Affinity groups, filter bubble
• Personalizing without knowing persons
Autonomy
• Data sharing > data ownership
• Data arrogance, accountability
• Algorithms rule; are we still in control?
EMPOWERMENTCRITICAL THOUGHTS
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• Disruptive business models; who benefits?
• Liability; Who is liable when things go wrong?
• Accountability; Who has to prove what and how it is regulated?
• Interpretation; Data versus a Clinical eye
TRUSTCRITICAL THOUGHTS
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• Knowing what vs. knowing why
• Relationships are correlational, not causal
• Quantity above quality
• Those who generate data, do not have the knowledge to analyse. Those
who analyse lack domain insights
• Data education to support critical and creative thinking
• Multidisciplinary Data-skills
DATA WISDOMCRITICAL THOUGHTS
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• Search for patterns rather than testing hypotheses
• Critical volume, variety, veracity of data
• Beyond RCTs; Life Logging
• Power of Analytics (Machine learning)
• Bottom up evidence (reverse epidemiology)
EVIDENCECRITICAL THOUGHTS
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• Crossing boundaries (social-technology sciences)
• Crossing Borders (Germany, Finland, Canada)
• Real time monitoring (Lifelogging; data generated by use of tech)
• Persuasive coaching (tailored, contextualized) based on real-time
analysis (qual & quan)
BIG DATA & BIG HEALTHOUR RESEARCH
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BIG DATA
WEARABLES @WORK; @ HOME
Unobtrusive life–tracking 24h
Just in time coaching
Prevention of complications
Empowerment, Trust, Wisdom
Evidence: real time analysis
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Twente-Thales ImEdisense Telemonitoring
in stAble Chronic Heart Failure (Twente
TEACH)
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BIG DATA IN PSYCHIATRY JUST IN TIME COACHING
Pervasive Technology to better measure, aggregate and make sense of
behavioral, psychosocial, biometric and geodata to develop
personalized coaching programs,
to make predictions about how a given individual will proceed
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Highly Resistant Micro Organism, e.g. MRSA; Zoonotics
(Animal>humans)
Digital surveillance to track, trace infections and to develop a
predictive model to detect and prevent outbreaks
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BIG DATA IN INFECTION PREVENTION
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Patient
Mobility &
Infections
eSurveillance
for just in time
Interventions
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• Integrating geospatial data with epidemiological and clinical data
• to develop a smart surveillance system (EWS)
• Path of movements (HCWs inside/outside hospital)
• Pathogens and HRMO are monitored real-time (over 5 years)
• New computational methods for analysing geospatial and
laboratory data
• User centred methods for presenting (visualization of) data
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PREDICTIVE MODELING COOPERATION HEALTH-BUSINESS-SCIENCE
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• Bottom up Medicine
• Management of security/privacy, regulations
• Data Wisdom to make sense of Big Data
• Boundless potentials (health, business, science)
• Evidence via real time observations
• knowing what & knowing why
• individuals vs populations
WRAP UPBIG DATA & BIG HEALTH & BIG VALUE
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MOOC eHealth
https://www.futurelearn.com/courses/ehealth
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www.healthbytech.com www.cewr.nl (persuasive technology lab)
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PREDICTIVE MODELINGRISK FACTORS USING DATA FROM SMART-COPD INHALERS
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EBOLA SPREADeSURVEILLANCE SYSTEMS
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It Was A Bad Idea For Watson The Supercomputer To Learn
The Urban Dictionary…
Understanding Natural Language, BIG Challenge
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Update with Geospatial data & behavioral data