BDE2016

1. Big data
changing lives
Floortje Scheepers, MD
PhD, head of the
department of
Psychiatry UMC Utrecht
big data expo
21 september 2016
Volume
velocity
valu€
veracity
variety

2. What is changing?
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Egge vd Poel, datascientist, Erasmus
Patient
citizen
Doctor
ICT
treatment
Based on Trials
Based on clinical intelligence

3. data explosion

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Exposome


Genome
Microbiome

6. • Sensordata
• Data and user driven science and
patient empowerment
• risk profiling based on normative
models in stead of causality
• (complex) models and analytics
• P4 medicine (predictive,
preventive, personalized,
participating)
• Combining domains!!
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From ‘big’ to
one and back
elofte: lagere kosten, betere resultaten
uwe dynamiek qua sturing, eigenaarschap
ser driven science
atient empowerment
uwe uitdagingen / onderzoeksvragen
centives en waarborgen voor koppeling bronnen
dividuele causale effecten en prognoses
tidisciplinair onderzoek nodig om impact te realiseren
Van ‘big’ naar i
k
en terug
75% NL population
BIG DATA & HEALTH
Bron: https://infocus.emc.com/wp-content/uploads/2012/10/New-Health-Sciences-Data-Sources.png

7. Symptoms Brain function Genes
What do we know about the
disturbed mind?

8. 1. DSM was born 1952
schizophrenia mania depression Autism

9. 2. Investigating the brain
Structure Activity Function

10. 3. Investigating genes

11. 4. EPI-genetics

12. 5. Vulnerability versus resilience

13. 1. Selection bias:
‐ severe patients not included
‐ Co-morbidity not included
2. Brain changes over time:
‐ Brain plasticity/adaptation
‐ Effect of development
‐ Effect of medication
3. Environmental influences changes over time!
4. Results overlap, don’t stick to classification
Problems current research to
overcome

14. Research vs real life
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16. Governance

18. National data
like
psychiatric
(Nemesis)
and healthy
(CBS)
Regional data
like
psychiatric
(casusregister
) and healthy
(municipal/yo
uth cohort)
All
psychiatric
patients of
one local
hospital
individual
psychiatric
patient
profile

19. collect
Integrate
Explore
Analyse
 Research Data
Platform (RDP)
 Lokale opslag
 RDP
 Python
 Jupyter
 Excel
 SynerScope
 Postgres
 SynerScope
 R
Pseudonymise
Prepare
apply
Applications

20. Two different worlds meet
Hackathons

21. Aanpak

23. From descriptive through predictive to
prescriptive…

24. themes
• Medication use (short acting vs long acting)
• Aggression (prediction models; written notes in
EPF)
• Duration of submission (blue, green)
• Wearables (stress level, activity, sleep)
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25. New problems to overcome
• FAIR (findable, accessible, interoperable, re-
usable)
• Privacy, ownership
• From molecular to system level to organism level
• Data storage and processing
• Management and analytics (error correction,
normalization, mathematical modelling,
computational simulation)
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26. Compute visits the data → mental health consortium
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Aggregation/conclusion algorithms on serial/parallel analyses of
(encrypted) datasets → norm profiles  replicate/validate

27. 2020: A patient is referred to the hospital

28. The psychiatric fingerprint is
already known

29. Enough time for a personal
conversation about needs

30. A personalized diagnose and
treatment plan

31. Questions?