Author: Nick Richmond
25 January 2024
Our daily lives are being transformed by transactional activity and repetitive tasks, moving away from people to digital and technological solutions. From Banking and Retail to booking holidays and entertainment, the digital age has become so ubiquitous that we question when something is unavailable through an online solution. In healthcare, the Topol Report (2019) remains relevant today in terms of looking at the impact of digital technologies on the NHS workforce and wider health services. The report group judged which innovations would first mainstream and how the NHS might manage the workforce transition to do so effectively.
The impact of the pandemic on the way we work accelerated the adoption of many digital technologies faster than was ever predicted by Topol, especially the use of virtual meetings and clinical consultations and the adoption of the development of AI programmes to enhance clinical decision-making into practice. These changes have been accepted by clinicians and patients alike, providing an unforeseen behavioural change that no one could have planned and releasing an unprecedented race for further development of safe digital deployment.

This new reliance on digital solutions requires both material investment and a far larger, skilled data, analytics, and digital technology workforce to manage the change. Topol estimated this to be around an additional 10,000 people required over the next 10 to 15 years, a number recently affirmed by a NHSE workforce planning exercise. This expansion is not affordable under the current NHS financial envelope, so how can workforce planning assist in the question?
If we look at industry comparisons to how technology, particularly AI, may impact general routine tasks. We can expect a quantum leap in the way our back office and clinical administration functions operate over the next decade. Rapid Process Automation already provides solutions for labour-intensive activities such as HR recruitment, including automating advertising, shortlisting, and final selection processes. In Accounts, a significant level of daily activity can be automated in this way, with much more to be achieved. How might we manage this transition and shift such jobs from the back office into the data and technology-intensive roles? Staff working in these departments now already have the base skills of numeracy and ability to manage detail at scale – so a transition workforce planning exercise needs to include both new recruitment of very specialist skills and provide for reskilling the current workforce when the new digital solution is ready for implementation. This allows us to retain displaced staff with a level of retraining, saving in recruitment costs and retaining staff already employed with NHS values.
The implications for our clinical workforce will also change over time, with some more affected than others. The AI competency framework developed with key partners by Health Education England provides a helpful indication of which groups will be impacted first and what skills differing professions might require over the next decade. This will aid workforce planning not just from a numbers position but also in terms of what skills will be required. Concerns about image recognition replacing radiologists are misplaced because although AI-generated image recognition can identify and label a scan, we will still require human clinical judgement to check, verify and provide a definitive diagnosis. Training for these new skills will be essential.
So, as the health system starts to accelerate the adoption of new digital solutions, our workforce planning will need to anticipate these changes so we can proactively retrain and retain rather than lose skilled back office and front-line clinical staff. This will make it easier to afford and change whilst minimising the risk of skills shortages.

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