HealthManagement, Volume 19 - Issue 4, 2019
Jaana Sinipuro
Project Director, Sitra, the Finnish Innovation Fund, Finland
The citizen’s perspective and data protection issues must be taken strongly into consideration in the planning of operations and operational practices for a national one-stop shop for healthcare data. The new actor must be able to work transparently. For instance, an information security audit provides a holistic picture about the current state of data processing in an organisation and an assessment about the realisation of data protection, data security and privacy protection. It is essential that the new actor will, at the very least, conduct an information security audit of its operations and ensure the data is handled in a secure manner.
However, for a data-driven economy to succeed there are also several dimensions on trust that are critical at the enterprise level as stated in a recent survey conducted by KPMG in October 2016 on data and analytics (KPMG 2016). When an enterprise plans for its strategy on analytics, the KPMG report recommends that they build a systematic approach that spans the lifecycle of analytics and focuses on four key anchors of trust: quality, effectiveness, integrity and resilience.
These are crucial dimensions even when planning for one-stop shop for data. For winning the trust from the researchers and companies aiming to use the data, we need to ensure transparency and an audit trail to the data sources, and maintain good quality of data management tools and processes.
The same applies for enriching data sets with personal data for more tailored digital services. An international survey reveals that people’s lack of trust presents an obstacle to the growth of digital business. The progress enabled by artificial intelligence is also at risk if access to data is compromised or transparency is not ensured.
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John Bullivant
Chairman, Good Governance Institute Advisory Group, UK
There are three types of data: personal, collective and identification.
Personal data must be treated as part of the individual’s
body and integrity. It belongs to them and must only
be taken and used with consent. It must be treated with
respect and collected, used and disposed of in that spirit.
Collective data is something else. We as a society need that
data to understand and learn more about the human condition
and how to protect and support our common good. In
both cases we must be able to trust those who have access
to the data. Trust is easily lost and hard to rebuild. The data
will inevitably be lost, stolen and abused so those charged
with its safe keeping must develop agility in responding to
these failures with integrity and transparency. The third type
of data is more difficult; it is that concerned with identification:
fingerprints, DNA, facial recognition etc, often collected
for public protection and collective security reasons but
the question of trust remains. There is also a fourth: social
media and the mistakes we all make in casually releasing too
much information. Good Governance requires us to tackle
all of these from the first principle that all data about me is
mine forever and only I can determine who uses it and to
what ends. We may have to compromise that principle but
we must do so thoughtfully and transparently.
You might also like: Enhancing precision medicine: sharing and reusing data
Marina Gafanovich
Internist, NewYork-Presbyterian, USA