Ensuring privacy and security of eHealth systems

The healthcare and pharmaceutical sectors typically generate and manage large volumes of sensitive data.

While the collection and storage of such data are crucial for scientific research, statistics and the efficient management of businesses involved, they also raise significant concerns about security, protection of privacy and anonymity within the e-Health systems. As a result, patients may be refrained from sharing their clinical data and trials, in so generating other considerable social and management costs.

For instance, the insufficient patient consent for data sharing may cause:

  • lower quality of scientific research and statistics, due to lack of updated and/or crossed data records;
  • inadequate understanding of costs and benefits of therapies and treatments, due to under-reporting;
  • delays in responding to particular diseases, such as epidemics.

TrustedChain® offers a disruptive solution to the problem of security and privacy in data storage and sharing through blockchain-based applications. Benefits are significant and they include:

Security and privacy-by-design.

Clinical data can be stored, managed, analysed and crossed for scientific, statistical or commercial purpose, while ensuring security and algorithm-enhanced privacy for all participants involved.

Streamlined management of patient identities and consent

Procedures to verify patient identities and obtain their consent for data sharing can be automated and tracked in a secure and more efficient fashion, resulting in a faster and cheaper workflow management.

Increased data sharing

The sharing of data can grow significantly as an effect of the increased trust of patients. With adequate interoperability between medical infrastructures and research institutions, TrustedChain® facilitates better exchange of clinical data: in turn, this leads to increased quality reporting and better scientific research, to the benefit of the entire industry and patients themselves.

Ad hoc data management

Database can be created for specific problem or purposes (e.g. for transplant) and updated in real-time, without disclosing personal information of patients.

Artificial Intelligence applications

The blockchain infrastructure can be integrated with AI systems, with several applications of interests, such as: automatic diagnosis, medical image processing, prediction of future pathologies, personalized management of care pathways and therapies, and the creation of a broader clinical picture of the patient, including for example data from wearable devices.

Creation of new markets

New economic incentives models can be engineered, so to create new patterns in the clinical trials data market which can benefit all relevant stakeholders.

This post is also available in: Italian