NCT06949462

Effectiveness of Large Language Model for Anaesthesia and Procedural Consent

Evaluating the Effectiveness of Large Language Models in Anaesthesia and Procedural Consent: A Comparative Analysis With Traditional Patient Consent Methods

• Status: Not Yet Recruiting
• Phase: N/A
• Study type: Interventional
• Enrollment: 120 (estimated)
• Sponsor: Singapore General Hospital · Academic / Other
• Sex: All
• Age: 21 Years – 99 Years
• Healthy volunteers: Accepted

Summary

Patient understanding of anaesthesia risks remains inconsistent due to time constraints, language barriers, and variable clinician communication styles. Traditional verbal consent may not consistently ensure comprehension or reduce preoperative anxiety. PEAR (Patient Education of Anesthesia Risks) is a multilingual, AI-driven chatbot developed to enhance patient education and improve the quality of anaesthesia risk counselling. Study Objective: To compare PEAR's performance in delivering anaesthesia risk consent against the standard face-to-face verbal method.

Detailed description

This study evaluates the effectiveness of PEAR (Patient Education of Anaesthesia Risks), a conversational AI-based chatbot designed to deliver anaesthesia risk education to patients in a personalized, interactive, and multilingual format. The goal is to support informed consent by improving patient comprehension, satisfaction, and reducing anxiety, while also streamlining clinician workflow. Participants undergoing elective surgery will be randomly assigned to either receive anaesthesia counselling via PEAR before their consultation with the anaesthetist (intervention group) or undergo the standard face-to-face verbal consent process (control group). The PEAR chatbot is accessed through a secure digital interface and presents information aligned with institutional anaesthesia protocols. The study will be conducted at hospitals within the SingHealth cluster in Singapore. Following the consent process, patients will complete a short quiz to assess understanding, a survey to evaluate satisfaction, and an anxiety scale. Clinicians will record time taken and perceived workload. All patients will still meet their anaesthetist, ensuring clinical oversight is maintained. This study does not alter standard care but evaluates a digital adjunct to enhance it. Data will be collected electronically, anonymised, and stored securely. Insights from this trial may inform the wider implementation of digital tools in perioperative patient education.

Conditions

• Consent Forms
• Anesthesia
• Artificial Intelligence (AI)

Interventions

Type	Name	Description
OTHER	PEAR	Participants in the intervention arm will receive anaesthesia risk counselling through the PEAR (Patient Education of Anaesthesia Risks) chatbot prior to their face-to-face consultation with an anaesthetist. PEAR is a multilingual, AI-powered conversational tool designed to provide personalized, interactive education on anaesthesia-related procedures, risks, and safety information. The chatbot delivers content aligned with institutional guidelines and allows patients to explore topics at their own pace, ask questions in natural language, and revisit information as needed. After completing the chatbot interaction, patients proceed with their standard preoperative consultation, where any further questions are addressed by the anaesthetist. This approach is designed to enhance patient understanding, reduce anxiety, and optimize the in-person consultation by preparing patients in advance.

Timeline

• Start date: 2025-07-01
• Primary completion: 2026-07-01
• Completion: 2026-07-01
• First posted: 2025-04-29
• Last updated: 2025-05-01

Locations

1 site across 1 country: Singapore