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The Office for National Statistics estimates around 1.5 million jobs in England are at high risk of having some of their duties automated in the future, while the World Economic Forum says nearly half of companies expect automation to lead to a reduction in their full-time workforce by 2022. 

Reports like this understandably generate anxiety about what technological progress means for people’s livelihoods. And while automation – where a machine executes a task with minimal human input – has been with us since the Industrial Revolution, recent advances in artificial intelligence (AI) and robotics are pushing the boundaries of what can be automated, not just in relation to manual work but complex cognitive tasks too, including in health care services.

All of this raises big questions. That is why in our newsletter this month we are exploring the different impacts of automation, AI and data-driven technologies on health and health care. We’d like to hear your views on these issues too – in our newsletter poll.

The effects on our health

Given that the potential impact of automation on the labour market is vast, and that work is a key determinant of health, automation could have significant implications for population health. This would be even more marked if it negatively affects those already disadvantaged in the labour market, exacerbating the risks of unemployment with all the impacts this can have on individuals’ and families’ health and wellbeing. 

Yannish Naik explores this in his blog, suggesting that the government needs to pre-empt these potential outcomes to ensure automation is harnessed for the benefit of all society. This includes providing support for re-training and connecting those affected with new employment opportunities, as well as ensuring that future generations are equipped with the skills they will need to succeed in the changing labour market. 

Using automation to support health care professionals

While studies show that much work in health care is less susceptible to automation than in other sectors of the economy, there are nevertheless several ways automation is having and could have an impact. In this interview about his recent research on the potential of automation in primary care, Matt Willis outlines seven areas where automation could be used to cut through the burden of admin work in general practice: letter writing, phone calls, paperwork, clinical documentation, e-referrals and bookings, communication between primary and secondary care, and communication inside the practice.

As he highlights, in many cases automation in health care will be about supporting professionals, rather than replacing them. The challenge will be shifting and rethinking the work that people do and redesigning roles so they are more sustainable, more meaningful and allow people to do more ‘value adding’ work – in other words, the things that humans are best at. For example, the GP receptionist role could become less focused on clerical work and more on patient interaction, including acting as patient advocates or care navigators. The supporting role automation could play is particularly important given staff shortages in the NHS, and workloads that many health care professionals feel are unmanageable.  

Our chart takes a look at which heath care jobs are most likely to be affected by automation.

Understanding the challenges to harness the potential

As well as the impact of automation on work, these technologies are also creating opportunities to improve health care quality, especially through AI and data analytics. Examples of this include using technology to analyse scans and detect problems that humans might not notice, or helping doctors make triage decisions by quickly identifying high-risk patients needing urgent care. This potential is recognised in the NHS Long Term Plan, and by NHSX, the new organisation in charge of digital transformation in the NHS, which have set ambitions for the use of new technologies in the NHS – underlined by the recent commitment of £250m to set up a new artificial intelligence lab.

But along with the many opportunities that these technologies bring, there are also real challenges to applying them in health care. Some of these relate to the use of data. As Sarah Deeny and Emma Vestesson write, new uses of data analytics like risk prediction tools hold huge potential for improving the prevention, detection and treatment of illness. But we also need to understand the unintended consequences of these techniques – such as their ability to create false alarms or to identify information that could be used to discriminate unfairly between patients – and how to mitigate them.

Human interaction is central to health care

Other challenges relate to the use of AI and robotics in patient-facing contexts, which we’re exploring in research underway at the Health Foundation. 

Human interaction is central to health care. Activities such as caring for and communicating with patients need a high degree of social and emotional intelligence – things that cannot be computerised. Treating patients with dignity and respect often requires human presence. Providing person-centred care relies on a relationship between a patient and a clinician. Indeed, there are examples of tasks which on the face of it, may seem like good candidates for automation but in fact hold value precisely because they’re carried out by people. 

For example, as robotic technology advances, some of the work of healthcare assistants may become easier to automate, such as monitoring vital signs, serving meals or helping patients move around. But it's often the contact healthcare assistants have with patients through doing these tasks that allows them to pick up on patient needs and provide emotional support.

Adoption – an adaptive and technical challenge

A third, more practical set of challenges relate to implementation. Successfully embedding and using new technologies very often requires redesigning roles and pathways and developing new ways of working – types of change that need to be iteratively developed and tested by staff and patients. Adopting technology is an adaptive as much as a technical challenge, and system leaders will need to support teams with the time, resources and quality improvement skills needed to do this.

If deployed wisely, automation, AI and data-driven technologies could hold huge promise for improving our health and prosperity. But as we can see, harnessing this promise will need a keen awareness of the challenges as well as the opportunities – to ensure we make the right decisions about these technologies along the way.

Tim Horton (@timjhorton) is Assistant Director (Insight & Analysis) and Tom Hardie (@tlhardie1) is Improvement Fellow at the Health Foundation. 

This content originally featured in our email newsletter, which explores perspectives and expert opinion on a different health or health care topic each month.

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