Sharing data responsibly
within health data ecosystems for greater societal impact
The pharmaceutical industry is committed to
responsibly sharing data in health data ecosystems to foster collaboration and
innovation that can have a sustainable impact on society. Aggregated health
data from population-level sources – including electronic health records,
wearable technologies, health insurance claims, health registries (or burden of
disease registries), clinical trials, drug consumption analyses, and other
research – can not only significantly boost innovation and medical progress but
can also lead to better policymaking and more efficient, sustainable healthcare
systems.
Drawing from over 100 years of experience with
responsibly handling sensitive data in clinical trials, the pharmaceutical
industry upholds robust data protection standards for all stakeholders
involved, including patients, academics, and public institutions. The pharmaceutical
industry supports both financial and non-financial incentives for structuring
and sharing data, such as reciprocity, equal exchange of value, and
intellectual property-based mechanisms for a functioning ecosystem. It fosters
the principle of providing qualified scientific researchers access to
anonymised participant-level data and full clinical study reports (CSRs) from clinical
trials to conduct legitimate scientific research.
Pharmaceutical industry’s
commitment to data sharing initiatives
One example of the pharmaceutical’s commitment
to responsible data sharing is its participation in the global effort of the US National
Academy of Medicine (NAM)
(formerly the Institute of Medicine) to develop principles for responsibly
sharing clinical trial data. Another initiative is HARMONY, a
private-public partnership that receives funding from industry and the EU’s
Horizon programme. The HARMONY project aims to leverage health data to deliver
information that will help to improve patient care, in particular in the field
of rare blood cancers, where data is scarce. Specifically, the project gathers,
integrates, and analyses anonymous patient data from a number of high-quality
sources. This helps specialists in the field to define clinical endpoints and
outcomes for these diseases that are recognised by all key stakeholders.
Another Innovative
Medicines Initiative 2 (IMI2)project is Big Data for Better Outcomes (BD4BO), which focuses on
maximising the potential of big data in order to improve health outcomes and
European healthcare systems. A fourth initiative, backed by funds from the
public and foundations, is UK Biobank, a large-scale biomedical
database and research resource containing in-depth genetic and health
information from half a million UK participants. The database is globally
accessible to approved researchers, both from academia and private industry,
who undertake research into the most common and life-threatening diseases. The
platform is based on reciprocity. The UK Biobank encourages researchers to
share their findings by publishing in open access scientific journals. Once
results are published, researchers are required to return their results to the
UK Biobank so they can be shared with other scientists, who can then test the
findings or use them to advance their own work.
Benefits of health data
ecosystems
Health data ecosystems hold many benefits, also
in regard to clinical trials. Not only do they allow those running clinical
trials to better find and match potential candidates who have the appropriate
profile, but health data ecosystems can also help simplify many processes used
in clinical trials. For example, the emerging concept of decentralised clinical
trials, where patients do not have to enter a hospital to participate in a
study, depend on patients’ ability to collect their health data electronically
and safely submit it to the organisation collecting the clinical data. Another
example of the use of health data ecosystems is the possibility to build
synthetic control arms. With access to longitudinal health data from different
sources, researchers can emulate in silico eligible populations and randomised trials,
including the generation of control groups from real-word evidence and
hybrid-design trials.1 This is particularly important for areas with
small samples, for example in rare diseases. Synthetic control arms can also
help alleviate the inherent ethical dilemmas of placebo treatments.
Switzerland’s untapped
potential
The benefits of a robust, national
health data ecosystem, however, currently remain untapped in Switzerland. The country
lags massively behind in terms of taking advantage of the potential of
digitalisation in its healthcare system. There are no regulatory incentives for
structuring and sharing health data, structured health data are scarce, and, if
existent, they are often locked up in silos, which is why there is little to no
primary and secondary usage. This is reflected in Switzerland’s very low
ranking in a European index measuring secondary use of health data that was
created by the non-profit, multipartner Open Data Institute (ODI) based in the UK (see Figure 1).2
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