Translating the AI Opportunities Action Plan into patient benefits

Translating the AI Opportunities Action Plan into patient benefits
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To release the full benefits of AI for patients, the government must focus on building the right foundations, writes Pritesh Mistry, fellow (digital technologies) at The King’s Fund

The government’s recently published AI Opportunities Action Plan is a cross-sector plan with the ambition to position Britain as a leader shaping the AI revolution.

While it doesn’t explicitly discuss the health and care system, there are likely to be implications and opportunities which require scrutiny and consideration. The plan emphasises laying the groundwork for AI by investing in infrastructure, computing, energy solutions, and high-quality data assets.

It advocates for building an AI skilled workforce, improving safety and assurance by bolstering regulators, and maximising potential impact through a process of scanning for AI with high potential, conducting pilots and scaling the most promising tools.

Strong foundations are essential for any technological ecosystem, a skilled workforce is needed to leverage tools, and AI needs to be scaled to maximise benefit.

Data is essential for effective AI tools so it’s heartening to see the plan recommend the creation of a National Data Library, starting with developing five high-impact datasets. The plan recognises that the healthcare system has existing datasets, which can be built upon for improvements – such as the biomedical database ‘UK Biobank’.

The health and care system unfortunately carries scars from historic data sharing missteps, such as care.data, so this means it must recognise and learn from lessons. This can be done by taking iterative approaches allowing for stepwise progress aligned with the trust and readiness of stakeholders, starting by using low-risk de-identified data.

Instead of creating monolithic, top-down data systems that are prone to delays and costly overruns, a modular approach should be adopted. Building data foundations incrementally means the pace can be adapted to real-world conditions and developed alongside activity to build public trust.

The instinct to quickly implement AI needs to be avoided in favour of a more strategic and long-term approach

The NHS has long grappled with siloed and inaccessible data. National datasets require unlocking the data which has long been held in proprietary systems so that data can flow seamlessly across systems and stakeholders.

To achieve effective data sharing, suppliers much enable data flow while technical solutions will be crucial as will a cultural shift.

Providers, trusts, and professions must come together under a shared agreement that prioritises interoperability and collaboration. This needs leadership agreement with clear policies, which are supported by technical standards that facilitate data exchange.

The instinct to quickly implement AI needs to be avoided in favour of a more strategic and long-term approach. This means starting with tools for data improvement and cleaning to build strong foundations and then identifying tools like AI scribes which could improve data collection while supporting staff.

This would secure the basics and align with the intention to strategically shape data collection and support UK innovation.

The plan rightly emphasises improving trust and safety through regulation and safety assurance, with agreed commitments to fund regulators.

Regulators must be equipped to oversee emerging technologies as well as to anticipate challenges and enforce compliance.

The UK’s Medicine and Healthcare product’s Regulatory Agency’s progress in establishing sandbox environments for testing AI applications shows good initial standing for healthcare, and allows for robust evaluation of new technologies in controlled settings. But transparent benchmarking approaches continue to be missing, despite being equally necessary to build public confidence and support procurement.

The success of the AI Opportunities Action Plan relies heavily on a skilled workforce.  Yet, the NHS and social care sector face a significant skills gap in digital, data, and AI capabilities, and stills lacks a digital workforce plan.

The plan’s emphasis on training is a step in the right direction, but it falls short of addressing the scale of the challenge for health and care.

Workforce development needs to include upskilling existing staff such as those responsible for information governance, data protection, clinical safety as well as baseline knowledge and skills of frontline staff. Without robust education and training initiatives, at best the potential of AI will remain unrealised, but at worse could elevate risks of harm.

One of the NHS’s strengths lies in its ability to test and pilot innovative technologies. However, the system struggles to scale successful pilots and stymies innovation.

The plan’s scan-pilot-scale approach must address this by developing the necessary infrastructure and platforms, investing in implementation (training, onboarding, and upskilling staff), post deployment monitoring, and continuous improvement. The focus must shift from isolated pilots to systemic implementation that deliver measurable improvements in care outcomes and efficiency.

The AI Opportunities Action Plan offers a promising vision for Britain’s leadership in AI, with clear implications for healthcare and social care.

However, its impact will depend on the leadership ability to think holistically, focusing on technology, trust, and workforce readiness.

If done right, there is significant potential for benefits to the NHS and social care, as well as contributing towards industry and economic growth. The key is to do today what is possible, while continuously building toward the ideal—a healthcare system that is smarter and safer for all.

Pritesh Mistry is fellow (digital technologies) at The King’s Fund. He focuses on how digital tools and technologies can improve health and care and is particularly passionate about using evidence-based digital technology as an enabler to improve quality of care and outcomes while critically assessing buzzwords and technology as a silver bullet.

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