This document discusses how data sharing is changing healthcare by empowering patients. It outlines a shift from a traditional care model, where patients are passive recipients of care, to one where patients are engaged and empowered through access to their own health data and contextual knowledge. Key drivers of this change include affordable technology, the quantified self-movement, big data, and empowered patients. The document discusses how patient registries and personalized medicine can utilize data to better understand treatment efficacy for similar patients and provide personalized care plans. It also notes challenges around data privacy and the need for guidelines. Overall, the document advocates for empowering patients through access to their own health data while using data and technology to coordinate and improve healthcare.

1. Data sharing
and how it’s changing healthcare
Asst Prof Matic Meglic MD PhD MBA
Strategy Director, Medtronic Hospital Solutions EMEA
@CONNECTED HEALTH & ME
Dublin, Nov 24 2014

2. Agenda
How data
enables
empowerment
What’s next
Patient registries
In EU

4. Traditional care model
EHR Clinical
knowledge
CARE

5. Patient engagement
EHR Clinical
knowledge
CARE
DO

6. Patient empowerment
ENABLER
EHR Clinical
knowledge
CARE
Contextual
Knowledge
Digitized
self / PHR
INFLUENCE
ENABLER / DISINTERMEDIATION
DO

7. The paradigm shift towards empowerment
requires e/mHealth as an enabler.

8. Key change drivers / enablers in healthcare
and their implications in healthcare:
• Affordable Technology
• Connected 24/7
• The quantified self
• Big Data & Open Data
• The empowered patient
• Personalized medicine
• New ePublicHealth paradigm

9. Patient empowerment
EHR Clinical
knowledge
CARE
Contextual
Knowledge
Digitized
self / PHR
INFLUENCE
ENABLER / DISINTERMEDIATION
DO

10. Empower to discover
• PatientsLikeMe
• Frost et al. JMIR 2011
• taking certain drugs “off-label“
with higher perceived efficacy
• side effect of amitriptyline (dry
mouth) as the purpose for taking
the drug (e.g. to treat excessive
salivation).

11. ePublicHealth paradigm change
• Personalisation of public health
• Infomediation (and consequent patient empowerment)
• Infodemiology, infoveillance

12. Personalized medicine
ENABLER
EHR Clinical
knowledge
CARE
Contextual
Knowledge
Digitized
self / PHR
INFLUENCE
ENABLER / DISINTERMEDIATION
DO

13. Based on this personalized profile …
• Find the most similar patients (or dynamic cohort) from entire population
• Analyze the attributes and outcomes for this cohort (across 30,000+ dimensions)
• Predict the probability of the desired outcome for patient in question
• Suggest a personalized care plan based on the unique needs of this patient
Desired
Outcomes
Historical Observation Window Prediction Window
This Patient’s Longitudinal Data Predicted Outcome For This Patient
Dynamic Cohort Longitudinal Data with Outcomes
Patient Similarity Analytics © JCrawfordIBM

14. Treatment Efficacy
Identifies the outcomes of drug treatments prescribed to groups of similar patients.
© JCrawfordIBM

15. So the clash of the titans is not (just) about
data..
• Google Health Kit
• Apple Health Kit
• Microsoft Health & HealthVault
• Truckloads of new smart devices (wearables,
implantables, ‘dissolvables’, ‘invisibles’) – for lifestyle and
healthcare use.
• Analytics and prediction based on your health data:
– At physician’s office
– On your smartphone

16. Influencing behaviour
ENABLER
EHR Clinical
knowledge
CARE
Contextual
Knowledge
Digitized
self / PHR
INFLUENCE
ENABLER / DISINTERMEDIATION
DO

17. Influencing behaviour
Consumerism
Games, Social networks
Healthy lifestyle, Chr Dis Mgmt
Azmo the dragon

18. And the final element!
ENABLER
EHR Clinical
knowledge
CARE
Contextual
Knowledge
Digitized
self / PHR
INFLUENCE
ENABLER / DISINTERMEDIATION
DO

19. Not always, not for everyone

20. Caution is however needed..
• Hacking attacks on remote devices
• Example of Melanoma Apps
• Access control breach

21. Health Data Landscape
• ‚Open‘ data (alltrials, care.data, number of pharma initiatives)
• Pharma 3.0 (E&Y report)
• US HIPAA/HITECH, Accountable Care, Meaningful Use
• mHealth (recent green paper by EC)
• EU Personal Data Protection Regulation proposal
• EU Cross-border Health care Directive (Art. 14)
• EU eHealth Network Guidelines & Multi-Annual Work Plan
• EU H2020 & AAL
• EU: eHN, eHGI, IHI, etc. epSOS, SHN, EXPAND, PARENT…

22. www.patientregistries.eu
PARENT – cross-border PAtient
REgistries iNiTiative
Incl. partners from Ireland:

23. www.patientregistries.eu
PARENT Joint Action tackles the unclear EU
Registry Landscape
• Where are the patient registries?
• Can we access their data? (for Public Health, Research)
• Do we understand the data in the same way?
• Processes to exchange data?
• Then provide tools to answer these Qs.

24. www.patientregistries.eu
Two key use cases are supported.
Use case 1:
• Help existing and new registries to be more
interoperable (Guidelines, best practices, CDS, SW)
• Assess Interoperability of these registries/data
sources (Assessment Tool)
Use case 2:
• Ability to identify registries/data sources (PARENT
Registry of Registries)
• Provide search & retrieval and maintenance of (RoR)
metadata from these registries
• Support exchange of data across registries (Query
broker)

25. www.patientregistries.eu
Knowledge Management Platform
PARENT Framework
Guidelines,
Recommendations,
Methodologies
Services, SW
tools
repository
Best
practices
Registry of
Registries,
Assessment Tool
Common
information
model,
ontologies,
vocabularies
Delivering PARENT

26. www.patientregistries.eu
Scenarios and use of PARENT results
• ESC: switch from their own RoR to PARENT RoR
• Arthroplasty: EAR collecting data from registries for safety
analysis
• MoH Slovenia (2014): use RoR for assessment of RD registries
• Valdoltra hospital Slovenia (2015): National registry for
arthroplasty using PARENT Framework
• Contributing to (2015): Irish Epidermolysis Bullosa Registry
and International Severe Acute Eczema registry

27. www.patientregistries.eu
Who benefits?
EC
JRCERN
MS
ERNERNRegistry
holders
Health
Auth.
Pharma
&Device
Industry
Insurers
Research
organizat
ions
Access
to data
Quality
of data
Reducing
barriers for
data re-use
Access to
data
Guidelines
Comparison
IT tools
Pharma
&Device
Industry
Research
organizati
ons
xxxxx
HTA
authorities
(MS and
EC)

28. www.patientregistries.eu
Future vision
• PARENT Guidelines and IOp assets
– Serve as a fundamental layer for secondary use of registry data: build
registries, search for data, retrieve data.
– Formally adopted by MS and EC initiatives (Safety, HTA, Post
marketing, etc.)
– Sustainable and further developed using a combination of biz models
(EC, MS, market)
• Patient focus (PROs, care&outcome benchmarking ->
future: patients request enrolment.

30. What prevents people from ageing well?
Navigating the health system pain points

31. Hospital Solutions: Developing services and
solutions spanning the care continuum and
grounded in our therapies
• Predictive analytics
• Patient screening
• Patient diagnostics
Disease
Management
• Remote monitoring
• Patient follow-up
and support
• Track disease progression
• Patient outreach
• Patient education
• Patient referral
Patient
Identification
Patient
Action
Patient
Management
• Core Medtronic therapies &
clinical support
• Care pathway management
• Process excellence
/ lean sigma
• CathLab managed services
Therapy
Delivery

32. Question 2- How can technology support people as they age?
Cardiocom: over 80.000 patients served daily in US
COPD pilot in UK:
• 24% reduction in GP appointments
• 62% of patients having more confidence to self-
manage
their COPD trigger symptoms.
• 97% patient satisfaction rate
• 94% service compliance rate
Now looking to scale up to a system wide deployment in
order to deliver wider benefits.

33. Conclusions

34. Lessons learnt:
• HC change: build platforms to connect all
stakeholders
• HC sustainability: Patients are a very valuable
resource
• Provide smart incentives tied to performance and
outcome indicators
• Data, registries: it’s a long-distance race.

35. To build future-proof healthcare:
• Empower patients (access to own data & context
knowledge for decision making)
• Use data smartly (context)
• Change design of health care system (patient at
the centre, stepped, coordinated care; IT tools;
process thinking)
• Open data (but cautiously)

36. www.patientregistries.eu
EU registries in future:
• Central authorities:
– Registry methodology and reusable IT assets (e.g. CDE)
– RoR
– Audits&benchmarking
• Shared data use model with the industry that drives..
• Sustainable funding (combo of gov. & industry)
• Patient as stakeholder: PROs/PROMs; integration with
PHR (and of course EHR)

37. Thank you for your attention!
matic.meglic@medtronic.com
@matic_meglic