The document discusses using data analytics from neonatal intensive care units (NICUs) to support clinical decision making. It outlines stakeholders in NICU data analytics like hospitals, practitioners, patients, and monitoring systems. It also discusses using patient data for improved healthcare, including disease trajectories, outcomes from treatment stratification, and integrating omics data. Barriers to using data like legacy systems, privacy regulations, and silos are also mentioned.

1. INTERNAL – CONFIDENTIAL
MAKING HEALTH DATAVALUABLE
ELLIE D’HONDT

2. CONFIDENTIAL — DO NOT SHARE
$$$ $$$
THE UNDERPANT GNOMES METAPHOR

3. CONFIDENTIAL — DO NOT SHARE
$$$ $$$
THE UNDERPANT GNOMES METAPHOR
DATA
VALUE

4. 4
NICU DATA ANALYTICS FOR CLINICAL DECISION SUPPORT

5. 5
[Van Laere & al, J. Pediatrics, 178(119-124), 2016]

6. 6
[Van Laere & al, J. Pediatrics, 178(119-124), 2016]
BACKGROUND
?

7. 1. NICU DATA ANALYTICS: STAKEHOLDERS & INTERACTIONS
intervention service
7
EMR platform
hospitals
medical
grade sensor
health
practitioners
patient
infrastructure
care
data
monitoring
system (PDMS)
decisionsupport
sensor
fusion
events
centralised
UI
events
real-tim
e
analytics
= hospital context
data
sharing

8. PATIENT DATA ANALYTICS FOR IMPROVED HEALTHCARE
VEHICLES: DISEASE TRAJECTORIES & OMICS

9. FEMALE MORTALITY RATE HIGHER AFTER CARDIAC ARREST
180.368 patients with diagnosis of cardiac arrest
Sweden, 2003-2013, 73 hospitals
survival rates after 1y: ♀ 83%, ♂ 87%
survival rates after 5y: ♀ 75%, ♂ 82%
i.e. triple risk of death at 1 year and a double risk
at 5 years ♀ vs. ♂
confounders considered
no diff when following best-practice guidelines
why?? speculation so far.
9
Alabas OG et al. Sex Differences in Treatments, Relative Survival, and Excess Mortality
Following Acute Myocardial Infarction: National Cohort Study Using the SWEDEHEART
Registry Journal of the American Heart Association. Published online December 14 2017

10. 10
patient
stratification
fine-grained
treatment
outcomes
fine-grained
epidemiology
comorbidities
⬌ treatments
unexpected
treatment
effects (+/-)
treatment
trajectory
analysis
+ omics (gen-, proteo-,
metabol-,radi-)

11. 11
patient
stratification
fine-grained
treatment
outcomes
fine-grained
epidemiology
comorbidities
⬌ treatments
unexpected
treatment
effects (+/-)
treatment
trajectory
analysis
+ omics (gen-, proteo-,
metabol-,radi-)
adaptive trial
design
outcome-based
reimbursement
personalised
treatments
clinical decision
support
drug
repurposing
health
expenditure
planning
prevention
strategies

12. CLINICAL TRIALS TODAY
12
EMR system
hospitals
health
practitioners
patient
infrastructure
care
clinical sensors
monitoring
system (PDMS)
events
events
data
extraction
pharma
clinical research
organisation
trial design
trial execution
= hospital context = new

13. ADAPTIVE CLINICAL TRIALS
adaptive trial service
new stakeholder
13
EMR system
hospitals
health
practitioners
patient
infrastructure
care
clinical sensors
monitoring
system (PDMS)apps &
wearables
events
events
pharma
clinical research
organisation
daily
updates
initial design
& updatestrial execution
= new
trial execution
outside hospital
= hospital context
wearable platform
daily analytics
research
partners

14. UTOPIA
14
MedTech
government
patients
hospitals
pharma
virtual medical wallet
mutualiteithealth
practitioners
pharmacies
software
engineering
clinical trials
CRO
reim
bursem
ent
care &
follow-up
care &
reimbursement
admin &ownership
reimbursement
& adherence to
guidelines
trusted intermediary

15. 15

16. BARRIERS
16
legacy systems
value from
data
privacy
regulation legacy behaviour
virtual medical wallet
knowledge
from data
standards
governance
16
silos
budget

17. 17

18. state-of-the-art
300mm
cleanroom
(2016 – 4000m2) ▪ unique high-tech
infrastructure
▪ pre-competitive research
▪ full eco-system
▪ 3500 people
▪ 6 countries

19. LIFE SCIENCES
BODY AREA
NETWORKS
NERF
HIGH PERFORMANCE
COMPUTING FOR
LIFE SCIENCES

20. WHOLE GENOME ANALYSIS
20
SAMPLE SEQUENCINGCELL SORTER
REPORT GENOME ANALYSIS
SOFTWARE
GENOME ALIGNMENT
SOFTWARE
SEQUENCER DATA
VARIANT DATA
@ IMEC

21. HIGH PERFORMANCE COMPUTING
FOR LIFE SCIENCES