After the second in our series about artificial intelligence in healthcare exploring the ethical issues, we look now at the human resource implications.

Workforce numbers

We face a staffing crisis in healthcare globally, caused both by lack of resource, greater expectations and demand, and an ageing population.

It might seem counter-intuitive to state that, with more automation, there will be a need for more staff, but that is what the current debate is suggesting.

For example, The Topol Review, commissioned by the Secretary of State, sees things this way. For them, AI is a means to reduce the burden on the medical workforce and to aid productivity, but not to reduce the numbers of personnel required.

Prof Ian Cumming, the Chief Executive of Health Education England (HEE), in an interview with The Sunday Telegraph, identified a need to “increase the workforce by 50% in a decade unless action was taken to embrace technology”.

Elsewhere, HEE has also declared that if demand continues at the present levels and productivity does not improve, then by 2027, 190,000 more staff will need to be hired. These are very big and worrying numbers. Very few commentators are saying that automation and AI will drastically reduce workforce numbers.

New skills

To gain the full benefits of AI, there will be a need for new skills for clinicians, technicians, nurses, paramedics, and administrators, amongst others. Staff will either have to be retrained or different types of staff will need to be recruited.

New roles will emerge in areas such as robotics, electronic records, clinical bio-informatics and data entry, machine learning and diagnostics, as well as planning, programming, data governance and patient flows on the administrative side.

The human interface with the new robotic machines and other AI-powered systems is a complex one. This will necessitate the ‘upskilling’ of many current NHS staff, especially clinicians and diagnosticians.

Whole new specialisms will grow in importance, such as medical software technicians, clinical data scientist, and digital medical specialists. Each organisation will need leaders and managers to oversee this critical, but complex new area. The current emphasis is thus on establishing Chief Clinical Information Officers (CCIOs), digital leaders who should also have oversight of safety and governance.

The NHS is currently massively overstretched and in some areas potentially not as efficient and safe as it should be. Rather than reducing staff numbers through more intelligent automation, the real benefit will be to significantly improve productivity and speed of response. This will give staff more capacity to devote to their prime roles, spending more time with patients, rather than on administrative tasks. 

New training requirements

To get the best out of AI and new digital technology, there are two very different training and educational needs.

Firstly, to ensure that the NHS workforce, both clinical and non-clinical, understands how to utilise these new tools safely and effectively. In other words, what AI can and cannot do for them, be it in triage, diagnostics, treatment, patient data, record keeping, research or logistics.

The second and perhaps most difficult challenge will be to ensure that patients and the wider general public, young and old, whatever their IT skills, learn how to embrace the ‘digital’ way.

They will need to access automated systems, and engage with and accept advice, or even a diagnosis and prescription from a machine, or, in their eyes, a robot.

The recent survey by IPPR showed that when asked what the extra £20 billion promised the NHS over the next five years should be spent on, digital access was placed at the bottom of the priority list. There is a lot more to be done to engage the public and clearly, there are very big questions here, especially for children or those with mental health issues.

Extra pressures

The NHS workforce will need to develop in new directions. Working practices and workflows will change and new roles will need to be created. The impact of these changes cannot be underestimated.

Above all, to reap all the enormous benefits on offer will require a massive public engagement programme, requiring more resource, time and buy-in from NHS staff. And this just when the latter are already under immense pressure simply to do their day job with the tools at their disposal, and arguably have no capacity to ‘learn new tricks’.

Driving productivity

An obvious use of AI is in improving ‘back office’ functions for the NHS. Scheduling staff programmes, bed occupancy, theatre or outpatient bookings are simple tasks for machines. A learning machine will quickly adapt to changes, absences or last minute cancellations, but these tasks can lead to many errors when passed to overworked administrators.

AI may also offer productivity gains through automating other basic administrative tasks, such as finance, payroll, staff reports, EHRs and large-scale process optimisation.

Multiple benefits

The greater use of technology in healthcare may not be an instant panacea if one is looking for actual manpower savings, but it will clearly produce many other HR benefits.

Key amongst these will be an increase in productivity, lessening the burden on healthcare professionals by automating a wide range of tasks. In turn, this will free them up to concentrate on their main clinical tasks, offering more personalised care, pursuing medical research and many other fulfilling and patient centred tasks, rather than form filling.

Plus, with proper monitoring and governance, there should also be far fewer mistakes and errors. The net result will be greater retention of more contented and motivated staff, with less stress, less staff sickness and burn out, all inevitably leading to better and safer healthcare for all.

About Odgers Berndtson Healthcare Executive Search Practice

Odgers Berndtson Healthcare Executive Search Practice works with a wide range of service providers, payors, and governing bodies to secure highly-motivated leaders with the innovation and flair to transform the healthcare sector, both locally and globally.

Read the previous article produced by the Odgers Berndtson Healthcare Practice: ‘What every healthcare Leader should know about AI'.

Chris Stanford

Chris retired in March 2015 as Head of Global Healthcare, where he handled senior roles across Government, the commercial and not-for-profit sectors. Chris specialized in Academic Health Science Sy...

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