Artificial intelligence and clinical informatics in UK ophthalmology training: a national cross-sectional survey

BACKGROUND: Artificial intelligence (AI) and clinical informatics (CI) are strategic priorities for UK ophthalmology, with the Royal College of Ophthalmologists identifying education and training as central to safe implementation. However, formal CI/AI training is not currently embedded within the Ophthalmic Specialty Training (OST) curriculum. This study aimed to evaluate trainees' baseline knowledge, access to training and perceived educational needs to inform future curriculum development. METHODS: We conducted a national cross-sectional online survey of UK ophthalmology trainees between January and June 2025. A bespoke questionnaire was developed in accordance with the CHERRIES framework and informed by national policy and the NHS England DART-Ed digital competency framework. Content validity was strengthened through expert review by members of the Royal College of Ophthalmologists Informatics Working Group. The anonymised survey assessed baseline knowledge, perceived clinical relevance, access to training, educational preferences and career intentions. Quantitative data were analysed descriptively and free-text responses underwent inductive thematic analysis. RESULTS: Seventy-one trainees responded, representing all UK training deaneries and all training grades. Most reported only basic or no knowledge of CI (76%) or AI (76%), with limited access to deanery-level training. Support for formal education was high (CI 70%; AI 80%). Nearly half (49%) wished to incorporate CI/AI into future consultant roles. Trainees favoured blended, clinically relevant training models combining online learning, regional teaching and supervised project work. Qualitative themes emphasised foundational literacy, governance and safety, practical application and flexible delivery. CONCLUSIONS: UK ophthalmology trainees demonstrate majority support for structured CI/AI education, with over 70% supporting formal training in both domains, despite limited current provision. These findings support integration of digital competencies within the OST curriculum, aligned with national frameworks, to prepare the future workforce for safe and effective AI-enabled ophthalmic care.

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Publication Details

Journal
BMC Medical Education
Published
2026-05-21
DOI
https://doi.org/10.1186/s12909-026-09391-5
Primary Topic
Retinal Imaging and Analysis
Type
article
Field-Weighted Citation Impact
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article

Artificial intelligence and clinical informatics in UK ophthalmology training: a national cross-sectional survey

A. Abraham, Rishi Ramessur, Thomas Nash, Peter Thomas
BMC Medical Education
Retinal Imaging and Analysis
article

Artificial intelligence and clinical informatics in UK ophthalmology training: a national cross-sectional survey

A. Abraham, Rishi Ramessur, Thomas Nash, Peter Thomas
article en

Abstract

BACKGROUND: Artificial intelligence (AI) and clinical informatics (CI) are strategic priorities for UK ophthalmology, with the Royal College of Ophthalmologists identifying education and training as central to safe implementation. However, formal CI/AI training is not currently embedded within the Ophthalmic Specialty Training (OST) curriculum. This study aimed to evaluate trainees' baseline knowledge, access to training and perceived educational needs to inform future curriculum development. METHODS: We conducted a national cross-sectional online survey of UK ophthalmology trainees between January and June 2025. A bespoke questionnaire was developed in accordance with the CHERRIES framework and informed by national policy and the NHS England DART-Ed digital competency framework. Content validity was strengthened through expert review by members of the Royal College of Ophthalmologists Informatics Working Group. The anonymised survey assessed baseline knowledge, perceived clinical relevance, access to training, educational preferences and career intentions. Quantitative data were analysed descriptively and free-text responses underwent inductive thematic analysis. RESULTS: Seventy-one trainees responded, representing all UK training deaneries and all training grades. Most reported only basic or no knowledge of CI (76%) or AI (76%), with limited access to deanery-level training. Support for formal education was high (CI 70%; AI 80%). Nearly half (49%) wished to incorporate CI/AI into future consultant roles. Trainees favoured blended, clinically relevant training models combining online learning, regional teaching and supervised project work. Qualitative themes emphasised foundational literacy, governance and safety, practical application and flexible delivery. CONCLUSIONS: UK ophthalmology trainees demonstrate majority support for structured CI/AI education, with over 70% supporting formal training in both domains, despite limited current provision. These findings support integration of digital competencies within the OST curriculum, aligned with national frameworks, to prepare the future workforce for safe and effective AI-enabled ophthalmic care.

BMC Medical Education
Moorfields Eye Hospital NHS Foundation Trust (GB), University Hospitals Bristol NHS Foundation Trust (GB), Bristol Eye Hospital (GB), UCL Biomedical Research Centre (GB), Moorfields Eye Hospital (GB), University Hospitals Bristol and Weston NHS Foundation Trust (GB), University College London (GB), University of Edinburgh (GB)
Quality Education
Openalex Percentile: Top 7%
Retinal Imaging and Analysis
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