This summer, National Health Service (NHS) England rolled out HPV self-sampling in a bid to increase uptake of cervical screening. While this is great news for patients, there has been little discussion of the implications of this evolving screening pathway for the labs that do the analysis.
Now, new UK evidence, published in BMJ Open, suggests AI-assisted digital cytology could significantly reduce specialist slide-review time, while enabling cases to be shared between labs, supporting remote access to expertise, and allowing scientists to focus on more complex work.
We asked experts Alison Cropper and Amandeep Chohan how self-sampling and digital cytology could work together, and what this could mean for laboratory workflows, workforce pressures, and future service consolidation.
HPV self-sampling is intended to make cervical screening more accessible, but what does this change mean for laboratories further along the screening pathway?
Alison Cropper: Self-sampling is a positive step if it helps more women take part in screening, but laboratories need to consider what it means for the whole pathway. Over time, it could change both cytology volumes and the types of samples we see. That makes it important to plan digital cytology and self-sampling together rather than as separate developments.
As self-sampling changes how women enter the cervical screening pathway, where could digital cytology and AI-assisted slide review fit into the evolving model?
Amandeep Chohan: Self-sampling has an important role in reaching women who might otherwise not participate in screening. However, clinician-taken samples remain the gold standard because the sample is collected directly from the cervix by a trained healthcare professional, helping ensure high-quality samples and supporting cytology where further assessment is needed.
Digital cytology and AI-assisted review can support laboratories by identifying the most relevant cells for expert review and helping specialists use their time more effectively. The aim should be to use each technology where it adds the most value, while keeping accuracy and quality at the center of screening.
What could those time savings mean in practice for laboratory teams and how they use their expertise?
Alison Cropper: The recent BMJ Open study is useful because it puts some numbers behind what we have seen in practice. Using the current NHS cervical screening pathway, the research estimated that AI-assisted digital cytology could substantially reduce slide review time by around 69 percent. This estimates productivity gains of 76 percent in primary screening and 64 percent in consultant review.
The biggest opportunity is making better use of a highly specialist workforce. AI could support the initial screen, allowing scientists to spend more time on interpretation, complex cases, quality assurance, and training – the things that become squeezed when services are under pressure. It could also help laboratories manage workload more effectively and return results to women more quickly.
Amandeep Chohan: The important point is that the specialist still makes the decision. AI-assisted cytology helps identify the cells that need closer review. Then biomedical scientists and cytopathologists can focus their time where their expertise is most valuable. If that translates into the time savings suggested by the study, it could give laboratories much more flexibility in how they use scarce specialist capacity.
How could a digital workflow change the way cervical cytology services are organized, and help laboratories manage workforce pressures?
Alison Cropper: It could make services much more flexible. As screening continues to evolve and more women are reached, laboratories will need to manage changing workloads with a shrinking workforce. As services consolidate, experienced staff do not always move with them, and recruiting at a consultant level is increasingly difficult.
Digital working means the work can potentially move to the specialist instead. It could also allow cases to be redistributed between laboratories when one service is under pressure because of vacancies, sickness, or retirement, helping the network make better use of expertise that is available.
What changes to laboratory practices would be needed to make digital cytology work safely at scale?
Amandeep Chohan: It requires more than installing new technology. From our discussions with laboratory and service leads, we know that successful adoption also depends on suitable digital infrastructure, secure image storage and sharing, integration with existing systems, and clear processes for training, validation, and quality assurance.
Governance is also important, particularly if cases are shared between organizations. The role is to listen to what services need and support implementation in a way that works around existing laboratory workflows and the people using the technology.
What would an effective future laboratory model for cervical screening services look like?
Alison Cropper: I would like to see a nationally consistent, digitally enabled service where AI supports primary screening and specialists focus their expertise where it adds most value. Laboratories should be able to share cases and expertise, with consistent training and quality standards. Importantly, adoption should be program-wide, so access does not depend on what individual trusts can afford.
The BMJ Open study adds useful UK evidence on the potential of digital cytology. The next step is to evaluate that evidence quickly and establish a clear route to implementation.
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