P-177 Is AI the future of ART? Key barriers and drivers to AI adoption in clinical practice from the views of 144 fertility professionals
Authors: Bajwa S , Ferrand T , Saravelos S , Jacques C , Boivin J , He C , Chambost J , Hickman C 
Published: June 2023

Study question

What are the barriers, needs and views of fertility professionals towards using AI based decision tools in clinical practice?

Summary answer

There is an overall positive view towards using AI. The low implementation of AI in clinical practice is resultant of insufficient experience, knowledge and validation.

What is known already

Increased use of AI in fertility is aimed at improving clinical decisions and lab techniques by fertility professionals and improving standards of care experienced by patients. Despite the increasing presence of AI in peer-reviewed publications, the real views of fertility professionals regarding AI tools in fertility care are still unknown. Especially, with regards to whether any barriers in implementing these tools are experienced by fertility professionals or whether all required needs are met. This is the first comprehensive study that specifically focuses on understanding the views, needs and barriers faced by fertility professionals regarding utilising AI in fertility clinical practice.

Study design, size, duration

A structured questionnaire was distributed to 1419 fertility professionals. Respondents received the questionnaire online. In person interactions were also made at the ESHRE conference (2022) to encourage participation. Fertility professionals were identified from the ESHRE members list, with an equal distribution between countries as represented by the number of IVF cycles in those countries. With 144 responses from 37 countries, the response rate was 10%. Responses were collected between 13th May and 14th July 2022.

Participants/materials, setting, methods

The questionnaire consisted of 28 questions, split into 4 sections: (i) the demographics of the participant, (ii) their knowledge of AI, (iii) current use and (iv) unmet needs towards AI in clinical practice. Perceptions were graded (1:Strongly Against, 2:Against, 3:Neutral, 4:For, 5:Strongly For).

Main results and the role of chance

Respondents expressed positive views towards AI in clinical practice as highlighted by fertility professionals having felt more positive towards using ‘AI’ (average score = 3.9) compared to using ‘decision support tools’ (3.7,p = 0.002). Most participants had positive/neutral views regarding ‘patient confidence towards them when implementing AI decision tools in treatment plans’ (77%,n = 125). 78% of participants were intrigued in finding out more about the possible implementation of AI in clinical practice. Contrastingly, only 53% believed that AI could help reduce their clinical burden in decision making (1:7%,2:13%,3:37%,4:40%,5:13%). Age, source of funding and occupation did not affect perceptions. Furthermore, inexperience and lack of knowledge of AI tools were major barriers experienced: 14/29 participants that disagreed with whether utilising AI could reduce clinical burden, had never even used AI tools in the first place. Similarly, 11% indicated discomfort in using AI tools in clinical practice, of whom 79% self-described as having poor knowledge of AI. Evidence and data with improved live birth rate was identified by most respondents (120/144) as the most critical/important unmet need by fertility professionals. The preferred manner of implementation was directly to the equipment used in clinical practice (50%).

Limitations, reasons for caution

Despite attempts to have invitees’ global distribution matching global cycle numbers, the actual respondents did not reflect the proportion of IVF cycles in each country due to an increased response rate from UK, France and Europe and a reduced response rate from China and Asia.

Wider implications of the findings

This is the first study to assess perceptions of fertility professionals towards the use of AI in fertility care, highlighting the need to increase education of fertility professionals and validation standards to support fertility professionals in the responsible use of this new type of technology.

Trial registration number

N/A