ReviewEpilepsia open2026
The future of epilepsy care in the United Kingdom: A roadmap for technology-enabled transformation.
Review in Epilepsia open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Epilepsy is recognized to be a significant cause of premature mortality, socio-economic distress and poor quality of life in economically developed countries. Despite clear clinical guidelines, epilepsy care is marked by delayed diagnosis, fragmented management, high emergency admission rates, and pronounced health inequalities affecting rural populations, ethnic minority groups, and people with intellectual disabilities. Diagnostic pathways remain inefficient, with prolonged waits for electroencephalography (EEG), low sensitivity of routine investigations, and repeated inconclusive testing. Long-term management continues to depend on infrequent hospital visits and unreliable patient recall, contributing to suboptimal seizure control, avoidable morbidity, and preventable mortality. In the United Kingdom, epilepsy affects over 630 000 people, accounts for approximately £2 billion in annual healthcare costs and exemplifies these systemic failures. Current hospital-centric care models are failing to meet their complex, often lifelong, needs. In its recent 2025 "Fit for the Future" 10-year plan, the UK government mandates three fundamental shifts in healthcare: from hospital to community, analogue to digital, and sickness to prevention. Epilepsy diagnosis and care exemplify the potential for this comprehensive triumvirate transformation, with emerging technologies including point-of-care EEG systems, AI-powered diagnostics, wearable devices, and digital therapeutics offering unprecedented opportunities to deliver specialist-level care in community settings and reduce illness burden. However, successful implementation requires addressing digital exclusion risks for vulnerable populations. We propose that technology-enabled community epilepsy care can serve as a blueprint for the UK's National Health Service (NHS) transformation while delivering immediate benefits for patients, families, and healthcare systems. The convergence of clinical need, technological capability, and policy imperative creates a unique opportunity to move beyond incremental improvements to fundamental system redesign that ensures equitable access to high-quality epilepsy care across all communities. Such a model, if delivered, could be an exemplar for other chronic conditions both in the United Kingdom and globally. PLAIN LANGUAGE SUMMARY: Current epilepsy care in the United Kingdom often involves long waits and relies on infrequent hospital visits, which is not ideal for a lifelong condition. New technologies, such as wearable devices and AI-powered tools, offer a chance to change this. By moving care from hospitals into the community, we can provide faster diagnosis, continuous monitoring, and more personalised support. This will help improve the lives of the 630 000 people with epilepsy in the UK, ensuring they receive better, more accessible, and more equitable care.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.