Health and our environment: is collecting data through new technologies actually helping us?

Health-related data accumulation promises to help reduce uncertainty in health decisions, speed up diagnosis, tailor treatments to individual patients, and ‘save lives’. In fact, health related data is the fastest growing sector in the ‘datasphere’: electronic health records, de-centralised clinical trials, remote care kits (for example, ‘at home’ glucose or blood pressure kits), digital imaging records – these all require the collection and analysis of data.

Health data doesn’t stop at the clinic: many everyday activities are framed in terms of our health: step counts, use of social media, sleep patterns, even our location (GPS) data are framed as relevant to how physically and/or mentally healthy we are or should be. We download apps to monitor our gym habits, exercise routines, ovulation cycles and mental health. Researchers make predictions about our health by analysing this data, businesses are selling genetic tests that promise to tell us about our health risks, and companies are marketing smart toilets, smart socks and other smart devices to help monitor our health. In all accounts, society has been ‘healthitised’.

Does collecting data help us to improve our health?

The collection and analysis of health data brings benefits. In fact, it’s the crux of evidence-based medicine. Data collection is also integral to the scientific endeavour – without data, there is no health research.

However, the recent speed of data accumulation means that we are tempted to believe that the only way to achieve a healthy future is through evermore data and data analytics. This has, at least in part, been driven by the private sector: the pace of commercial innovation means that data infrastructures (use of the cloud, various apps, etc.) are being developed even before we know we need or want them. Once there, we use them – and then we want more of them. This then narrows our views of what ‘being healthy’ means. We view the promotion of better health outcomes as being equated with monitoring, analysing and assessing as many of our everyday lives as possible.

Consider an app that helps you monitor your mental health and provides resources and access to chatbots to help you. These resources have been useful to some degree – however, you feel that they can only work so far. You seek help from your health professional. Mental health services are overwhelmed and so your doctor puts you on a waiting list, with waits of over a year. You finally get an appointment, but you must travel to reach it and it costs quite a lot of money. You have a video consultation instead, but your wifi isn’t great and the health professional – also busy and overworked – prescribes some medication and suggests a follow up. A year passes and there has been no follow up.

Now consider an app that measures the air quality near your house so you can monitor and assess where and how you walk to work. Imagine that the air quality is so poor where you live that even though the app gives you readings saying that the quality is below national standards, whichever way you choose, makes no difference. You can’t move home because you can’t afford it.

What is the cost to the environment and others’ health when collecting all this data?

It’s not just that the collection and analysis of health data may bring little benefit to some – it can also contribute to environmental and health harms. These harms are associated with the manufacture, use and disposal of supporting digital infrastructures. The digital sector is predicted to contribute between 2.1% and 3.9% of all emissions, a figure similar to the aviation industry. Furthermore, digital infrastructures rely on minerals for manufacture. Mining minerals is not inherently bad and can be a source of livelihood for many, but history reveals that if not conducted with due consideration, it can lead to the destruction of local environments and an accumulation of waste. Adverse health impacts are also directly tied to poor mining practices.

Added to this, the digital sector produces a massive amount of electronic waste (e-waste), and because this waste contains hazardous materials such as lead, cadmium, mercury and nickel, it is a major challenge for disposal. Only about one-fifth of e-waste are formally collected and recycled, though this figure is higher for developed countries. Uncertainty revolves around what happens to the remainder – most likely it is disposed in dumps and landfills with other waste, or traded through illegal markets.

On the other hand, E-waste dumps, which are predominantly found in low-to-middle income countries, can be a source of livelihood for many, who rely on the disposed waste to recycle precious minerals. This recycling, however, is often through unregulated methods (open burning, incineration, acid stripping of metals, and acid baths), which generate hazardous and carcinogenic by-products that have been detected in workers and their families at levels vastly exceeding recommended dosages.

Where to next?

Collecting and analysing data is improving health outcomes for many. But the recent drive for data accumulation hides the questions: health benefits for whom? And who misses out? Behind technological solutions problems arise. It’s more than just a lack of access to benefits, but also that health harms may be experienced by those least likely to benefit.

Such harms have received little attention because they occur gradually and out of sight. We need ethical frameworks to bring them into our moral gaze. Concepts such as environmental justice are useful here, but also those related to colonialism, sustainability and responsibility. How to apply these concepts is yet to be decided. Watch this space.