This prospective, single-center randomized clinical trial evaluates the technical efficacy, accuracy, and operational performance of an automated conversational artificial intelligence (AI) voice agent for postoperative follow-up after arthroscopic shoulder instability surgery. The study examines whether SMS pre-notification improves survey completion during the first automated outbound call and assesses the accuracy of AI-captured patient-reported outcomes compared with blinded human review.
Participants who underwent arthroscopic shoulder instability surgery at least one year prior were contacted using an automated AI voice agent to collect standardized postoperative outcomes. Patients were randomized 1:1 to receive an SMS pre-notification prior to the first automated call or no pre-notification. The AI agent conducted structured interviews and classified call outcomes using a prespecified taxonomy. A hybrid protocol combining automated outbound calls, inbound callbacks, and targeted human follow-up was implemented to maximize data capture while minimizing resource use. All completed calls were independently audited by a blinded human reviewer to assess agreement with AI-extracted outcomes.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
SUPPORTIVE_CARE
Masking
DOUBLE
Enrollment
310
Participants received an SMS text message approximately 2 hours before the first automated outbound call.
Participants received no SMS prior to the first automated outbound call.
ICR Clinique Kantys Centre
Nice, France
Survey completion during the first automated outbound call
Proportion of participants who completed the automated survey during the first outbound call attempt.
Time frame: 1 week
Survey completion within the first attempt window (including inbound callbacks)
Completion during or following the first outbound call, including patient-initiated inbound callbacks.
Time frame: 1 week
Call outcome distribution
Classification of call outcomes using a prespecified taxonomy
Time frame: 1 week
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