Conversational AI for Clinical Intake: A Feasibility and Acceptability Pilot Study

Objective To evaluate the feasibility, usability, and acceptability of a conversational artificial intelligence (CAI) agent designed to conduct pre-visit patient intake in a cardiovascular outpatient clinic. Patients and Methods This prospective quality-improvement pilot study was conducted from July to September 2025 at a tertiary center. Adult patients attending an outpatient arrhythmia clinic were invited to interact with an embodied CAI agent prior to clinician review. The agent guided patients through protocol-driven dialogue, dynamically adjusting questions collect medical history, treatment adherence, and current concerns, and generated a structured summary. Participants completed a survey assessing usability, comprehension, trust, communication impact, and intention to reuse. Participating clinicians also completed a feedback survey. Responses were recorded on 5-point Likert scales and summarized descriptively. Results Of 240 invited patients, 235 (97.9%) completed the CAI session and post-interaction survey. Majority found the system easy to use (93%) and understand (91%), most (82%) expressed comfort sharing health information. Most patients (79%) reported improvement in the quality of the patient–provider discussion on decision-making and majority (82%) indicated intention to reuse. All participating clinicians reported favorable impressions with no safety concerns noted, and estimated time savings between 1-10 minutes per visit. Conclusions Implementation of a CAI agent for outpatient intake was feasible and well received by both patients and clinicians, demonstrating strong usability, trust, and communication benefits. These results suggest that CAI may meaningfully enhance patient engagement and streamline clinical workflows, supporting broader adoption of these systems.