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Life Data: the challenges of health data APIs

The developments in personalised medicine, bioinformatics and data-driven preventive healthcare mean that each person individually and the society as a whole can achieve the benefits of healthier, longer and happier life by collecting, sharing and using our data. That include medical, lifestyle, environmental; the food we eat, the air we breathe, our heartbeat history, hormonal biomarkers, genetic makeup, past treatments and illnesses – anything that can be measured, and ideally done so consistently during prolonged periods of time.

Right now, the absence of infrastructure is equally painful both for researchers and innovators who are unable to access the required information, and people who are missing on the opportunities to benefit from opening up their data. Unsurprisingly, the security and privacy is the number one concern: according to some estimates, the health data breaches are already costing the market operators $4bln and this grows exponentially.

Open Banking, a set of guiding principles and standards that are being implemented in the financial industry with the aim to foster product and UX innovation, protect the customer and give them more control over their data. By analogy with it, opening up health data and creating an infrastructure of protected, secure and controllable exchange may create a fertile ground for appearances of a wealth of new products, breakthroughs in research and simply give people tools to take control over of their data allowing them to use it for their own good.

APIs are at the core of structured programmatic data exchange on the Web today. The Open Health API approach seems to be a straightforward answer to the health data challenges, however at a more detailed review there may be critical limitations:

  1. Hard to standardise: Unlike bank transactions, health data is very heterogeneous and diverse in terms of type, volume, sources, parameters. Moreover, it is often required that complex and multi-dimensional meta data is also attached to each dataset, for example to trace data provenance and validate the method of a particular medical test.
  2. Control, not confusion: Permission-based sharing systems rely on explicit user’s consent, and considering the complexity and variety of data points, users often can get misled or simply don’t have capacity to investigate what information they should allow for sharing and how this may impact their privacy and security.
  3. In order to work, the standards have to be imposed on and adopted by all market players. Such top-down regulatory initiative, considering the complexities mentioned above, can take years to happen.

To summarise, the technological infrastructure required for creating an efficient health data sharing ecosystem poses a unique challenge. It needs to be addressed by developing protocols that do not need to rely on centralised regulations and would put the user at the heard of data ownership. Such systems could rely on federated data access, distributed ledger technologies, Dynamic Consent and public-private encryption to resolve the challenges and leverage the opportunities offered by the current scientific progress.

Keywords: open health data, healthtech, API

About Skein Group: Skein brings together digital technology businesses that develop innovative solutions for the data economy.

About the Life Data project: a research project that develops infrastructural requirements for health investment systems.

About Svitlana Surodina. The CEO of Skein group. Passionate about data and technology and the ways to use them for improving and extending human life.

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