Introduction Digital health technologies including artificial intelligence (AI) have made tremendous progress in ophthalmology with abilities comparable to expert humans demonstrated in fields like diabetic retinopathy screening. Healthcare systems worldwide face significant challenges in improving or even maintaining the quality of care and general population health. Real-world implementation of technological advancements will be necessary to achieve these aims.

There are several obstacles to the adoption of new technology in healthcare. One of the main challenges of using digital health technologies in hospitals is the implementation of these systems into routine clinical practice. Technological advancements alone are unlikely to ensure positive changes; individuals’ attitudes and behaviour must change as well as the way they work. The COVID-19 pandemic resulted in the rapid adoption of technologies to enable an effective response to the challenges posed in delivering healthcare. Despite these changes, adoption of AI and automation into routine clinical practice remains limited.

Aims and objectives of the research project or activity This research aimed to explore the main barriers to the integration of automation and AI into healthcare, from the perspective of ophthalmic leads at NHS trusts. Both clinical and non-clinical managers are key decision makers about the technology used in their department.This study seeks to understand current attitudes about using AI technologies within their ophthalmology service for the purposes of service improvement. The knowledge and attitudes of staff towards technology have been identified as a potential barrier to adoption. Reports suggest some NHS staff are sceptical of new technologies or discouraged by the potential complexity of adoption. We sought to understand the views of managers who are directly involved in facilitating technological implementation, and to discover barriers to adoption that need to be addressed to facilitate the successful implementation of AI technologies into routine care.

Method or approach Data was collected by emailing a survey to managers in ophthalmology departments across the United Kingdom (UK). The email was distributed by the Joint Clinical Lead of the National Eye Care Recovery and Transformation Programme to a combination of clinical and non-clinical leaders at all UK NHS sites in March 2021. It included 29 questions, most of which were centred around their views and experiences surrounding the integration of technology and artificial intelligence (AI) into the department. Participants were asked to consent to amalgamated anonymised results being shared.

Findings A total of 43 respondents held various roles including 12 clinical directors (28%), 19 service managers (44%), 7 matrons (16%) and 3 lead consultants (7%). The survey included respondents from multiple NHS trusts across the UK (1 Wales, 1 Scotland, 1 Northern Ireland, 21 England, 19 not stated). 36/43 (86%) respondents led ophthalmic services exclusively. Respondents had a mean of 8.5 years experience in management positions .

On a scale between 1-to-100 when asked ‘how familiar are you with digital health technologies’ the mean response was 48. 13/42 (31%) respondents were aware of a person or team within their trusts appointed to support AI- related projects. 79% of respondents said they were always, almost always or sometimes encouraged by their organisation to pursue digital innovation. 55% reported that they have never or almost never been involved in preparing or reviewing business cases for digital health projects. Whilst 65% agreed that the introduction of technology made their work more interesting, 67% reported that it made their work more demanding. Despite this, all responders believe that AI can be useful for the needs of their department, and none have had previous bad experiences with AI.

Key messages Regardless of the approach that is taken, those in leadership positions within ophthalmology departments must find a way to increase the time spent on digital health projects, as this will remove a significant barrier to the integration of new technologies, and the capacity that this creates.

The main perceived barriers to adoption of AI solutions in the departments were lack of time to investigate and implement solutions, concerns about the cost of setting up and maintaining AI as well as governance and patient safety concerns.