AB236. SOH26AB_0102. Artificial intelligence in emergency medicine: an evaluation of patient perceptions and expectations
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AB236. SOH26AB_0102. Artificial intelligence in emergency medicine: an evaluation of patient perceptions and expectations

Daria Toncheva1, Abhi Narsiman1,2, Clodagh Canavan1,3, Niamh Smyth1,4, Gerard Hill1, Laura Fleming1, Rayna Chandavarkar1, Areeya Ranatunga1, Michael Quirke5, Caitriona Cahir6, Arnold D. K. Hill1,7, Nuala Healy1,2,8

1Department of Surgery, Royal College of Surgeons in Ireland, Dublin, Ireland; 2Department of Surgery, University Hospital Galway, Galway, Ireland; 3Department of Surgery, University Hospital Waterford, Waterford, Ireland; 4Department of Surgery, Connolly Hospital Blanchardstown, Dublin, Ireland; 5Department of Radiology, Beaumont Hospital, Dublin, Ireland; 6Data Science Centre, Royal College of Surgeons in Ireland, Dublin, Ireland; 7Department of Surgery, Beaumont Hospital, Dublin, Ireland; 8Department of Emergency Medicine, Beaumont Hospital, Dublin, Ireland


Background: The role of artificial intelligence (AI) in healthcare is growing exponentially, with applications in triage, diagnostic imaging, and data interpretation. However, a limited understanding of how patients perceive AI remains, particularly in the emergency department (ED). As the central stakeholders, patient perspectives are crucial for the successful implementation of these technologies. This study aimed to evaluate patient attitudes and concerns regarding AI.

Methods: Following audit approval (Clinical Audit; CA2025-106), a cross-sectional survey was conducted in Beaumont Hospital, Dublin. From June to August 2025, over 1,700 patients were approached, and 1,325 consented (76% response rate). The questionnaire gathered information on prior AI knowledge, perceived benefits and risks, comfort level regarding the use of AI in clinical tasks, and opinions concerning accountability. Quantitative data were analysed descriptively, while qualitative responses underwent content analysis.

Results: The median age of respondents was 40–49 years old, 82% held a Leaving Certificate or higher, and 72% reported little to no prior knowledge of AI. Almost all patients (94%) wanted to be informed if AI was involved in their care. Although comfort levels varied depending on the task, 85% of patients wanted clinicians to retain final decision-making power, and 49.7% felt that accountability lies solely with doctors.

Conclusions: Patients in the ED generally support the use of AI and feel it has the potential to save time and money. Importantly, comfort and acceptance were highest when AI was used as an adjunct rather than a replacement for clinicians. Integration strategies should ensure transparency, maintain clinical oversight, and align with patient expectations.

Keywords: Artificial intelligence (AI); accountability; clinical decision-making; emergency department (ED); patient perceptions


Acknowledgments

None.


Footnote

Funding: None.

Conflicts of Interest: The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.


doi: 10.21037/map-26-ab236
Cite this abstract as: Toncheva D, Narsiman A, Canavan C, Smyth N, Hill G, Fleming L, Chandavarkar R, Ranatunga A, Quirke M, Cahir C, Hill ADK, Healy N. AB236. SOH26AB_0102. Artificial intelligence in emergency medicine: an evaluation of patient perceptions and expectations. Mesentery Peritoneum 2026;10:AB236.

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