Will big data gathered from our own bodies allow future healthcare to be self-administered? What are the psychological and ethical implications of trusting big datasets?

The potential value of harnessing big data in healthcare is the ability to provide a personalised service featuring precise assessment of health risks, early diagnosis, and more effective drug prescriptions. We explore how this could affect the space between wellness and sickness in the form of self-administered preventative care.

The growing trend in people searching the internet to probe their symptoms, or tracking their own physiological data with an array of devices, demonstrates that people are looking for ways to manage their health before seeking local medical support. How might we interact with a system that gathers and analyses our big bio-data, and offer treatment with minimal effort at home?

We have designed a system where data indicators from our bodies (hormone levels, blood sugar, blood pressure, nutrient levels, infections, etc.) could be stored along with our genetic information and analysed to provide early warnings of potential problems. The system includes a personalised care kit with medication and supplements that are acquired via subscription and self-administered for the prevention and treatment of conditions,
which are not fully explained to the patient.

We are most interested in the experience and psychology of using such a system. We propose that access to these data could eventually become overwhelming and stressful, and that with growing trust in the system some users would choose to know less and less about what they consume. Would wellness be improved if we can self-medicate without having to know what ails us? If we place increasing
levels of trust in the algorithms that analyse big data, then what is lost as we “upgrade”?

Maritta Nemsadze, Zhixin Zhao, Ran Xie, Ran Lu, Elysia Evers Wilson.

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