Clinicians' Perspectives on Pre-Anaesthetic Assessment and Their Attitudes Towards AI-Supported Models: Protocol for...

Pre-anaesthetic assessment is essential for safe perioperative care but is resource-intensive and applied variably in clinical practice. Increasing surgical demand and workforce constraints have prompted interest in alternative models, including digital approaches and AI-supported clinical decision support tools. However, limited knowledge exists on clinicians' perspectives, values, and perceived information requirements in relation to pre-anaesthetic assessment, including which information they consider essential prior to anaesthesia.

This international, cross-sectional survey aims to explore clinicians' perspectives on pre-anaesthetic assessment practices and their attitudes towards AI-supported clinical decision support tools. The survey will be conducted in two phases, beginning with Nordic centres before broader international expansion, using two linked instruments: an organisational survey completed once by a local site investigator at each site, and an individual survey completed by anaesthesia personnel recruited via site-based convenience sampling. The primary outcome is clinicians' perspectives on pre-anaesthetic assessment, comprising perceived importance, information not readily available from chart review considered essential prior to anaesthesia, and use in subsequent anaesthetic management; secondary outcomes include airway assessment practices and attitudes towards AI-supported tools, including willingness to adopt them. Exploratory outcomes include organisational workflows and time-use in pre-anaesthetic assessment. Responses will be summarised descriptively across clinician and organisational subgroups.

This survey will provide an international overview of clinicians' perspectives on pre-anaesthetic assessment and its role in clinical decision-making. The findings may contribute to the development of more efficient, stratified, and clinically aligned assessment models while recognising that implementation of digital and AI-supported approaches will also depend on organisational, technical, ethical, legal, and patient-related factors.