Bringing modern risk-prediction tools into primary care: recommendations from experts

What are risk prediction tools, and why are they important?

Risk prediction tools are designed to help GPs identify the patients who may be at higher risk of disease. Some of these tools are based on AI, and could help with earlier diagnosis, more personalised care, and preventing illness, which is why they feature in several national plans in England, including the 10 Year Health Plan and the Cancer Plan.

While many risk prediction tools are being developed, most of them are never used in GP practices, even after a lot of time, money, and effort has gone into developing and testing them. This is a problem: it wastes research investment and means patients miss out on the potential benefits.

Why aren’t risk prediction tools used by GP surgeries?

Unlike hospitals, GP surgeries don’t always have direct control over their own technology. Their IT systems are bought in by other NHS organisations, often leaving GPs with disjointed software, basic computers, and very little time to use new tools during short patient appointments.

Previous reports on digital and AI tools in the NHS have rarely looked at primary care. Where they have, they’ve looked mainly at population-level data and not at the risks or advantages of using tools to flag health risks for individual patients during their appointments.

Our research explains what needs to happen for risk prediction tools to move from research projects into everyday GP care. The work was funded by the NIHR Policy Research Unit on Cancer Awareness, Screening and Early Diagnosis.

How we carried out the research

We started out by reviewing UK policy reports (published between 2022 and 2025) alongside a broad review of academic research on technology barriers – the technical, infrastructure, system, and usability challenges that prevent digital and AI tools from being successfully adopted in everyday primary care.

We then held an in-person workshop with 22 experts, including family doctors, clinical informaticians (specialists who manage patient and clinical data systems to help hospitals, doctors, and nurses improve patient care), researchers, funders, regulators (NHS England and the MHRA), and medical software developers. This was followed by three online meetings and a feedback survey.

As part of this process,the experts reviewed five different technical routes for connecting these tools to GP computer systems, ranging from individual custom-built software to a shared system of standard, reusable tools.

What we found

To work well in GP settings, risk prediction tools need to be built to solve a real clinical problem and fit into existing GP systems without creating extra work. It should also be clear how they produce their results, so that clinicians and patients can trust them, and they need to be checked and updated regularly.

Four system changes needed for adoption

In the future, risk prediction tools could help GPs spot people who may be at higher risk of illness earlier, supporting earlier tests and diagnosis in some cases. But our research found that whether GPs can actually use these tools depends much less on the tools themselves, and much more the wider healthcare, academic, regulatory, and funding systems working together to support their use.

We identified four changes that could help:

1. Early joint working – different groups need to work together from the start.
2. Shared systems and infrastructure – a common, shared way of using and supporting risk prediction tools across the health system.
3. Clear and practical rules – clear and workable guidance for how tools are approved and used in the NHS.
4. Shared responsibility and long-term funding – a clear, shared agreement on responsibility if something goes wrong when the tools are used.

These changes will need to happen together, because if only one or two are addressed, it is unlikely that the tools will become part of routine care.