Health Data & Innovation Ecosystem in Life Sciences: Future Steps on a National Level

Antti KiveläDirector, Sitra

McGinnis, et al., Health Affairs; 21(2), 2002

Health Care

Environmental & social

factors

Genetics

Behaviour & lifestyle

Several Factors Combine

Together to Affect Our

Health

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Sitra • Antti Kivelä • 25.5.2015

Other data sources,

e.g. environmen

tal data 3

The Potential of Big Data in Health Care:

Towards improved value and preventive

care

EHR

Research data

PHR, inclbehavioral

data

Genomic data

Better health outcomes &

more personalized care

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More info in Finnish: http://www.slideshare.net/SitraHyvinvointi/8-omahoitokokeilua-terveyden-tulevaisuudesta

The Concept of Virtual

Clinic

Sitra • Antti Kivelä • 25.5.2015

National Genome Strategy

5

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• The value of health and well-being information utilization consists of 4 phases:

Structure of Health and Well-being Information Value Chain

Data Creation

“My Kanta” / personal online service for medical details

EHR database

Bio-banks

Integrated and analysed data

Standard interfaces

Customized interfaces

Ecosystem and Partner Network

• Public Research Institutes

• Private Research Institutes

• Pharmaceutical Industry

• Healthcare

Information Enrichment and Increased Customer Value

Revenue Stream

Utilization of Information

KanTa

Genome-database

Other data sources

Value Added Services

Data anonymization

IndividualBenefit

1 3

4

Data Gathering and Refining

2

Individual

• Individual

Analytic services

End-user applications

Services containing anonymized data

And so on.

Audit Trail and Securing Information Reliability

• National Centres of Expertise

4

National Operator for Health and Well-

being Information

7Sitra • Antti Kivelä • 25.5.2015

National service operator is responsible for gathering big bata on health and well-being information while ensuring the reliability of the data

The Role of a National Data Operator in the Value

Chain

Data Integration Support ServicesData Structuring

National Operator

• Co-operation with data owners in order to enable data transfer from administrative and technical perspective

• Continuous data gathering from different data sources using appointed interfaces and methods

• Integration of gathered data• Integrating audit trail into

data content

• Data structuring• Ensuring data quality• Creating integrated data

structure• Creating technical

architecture for providing services

• Enabling the utilization of Big Data and it’s datasets

• Defining, documenting and providing basic services e.g. standard interfaces together with the ecosystem

• “Made to order” customized interfaces

• Data anonymization depending on usage purpose

• Guidance and support on utilization of basic services