Artificial Intelligence vs. Automated Messaging for Continuous Regional Analgesia Follow-up

Effective postoperative analgesia is critical for patient recovery, satisfaction, and the reduction of hospital stay duration. Continuous peripheral nerve blocks (CPNB) via catheter placement represent a cornerstone in achieving these objectives. Traditionally, follow-up for these patients has relied on standardized telephone protocols conducted by trained personnel. Original previous research in 2024 demonstrated that an automated text-messaging platform was feasible and maintained high patient satisfaction, it resulted in a significantly higher rate of unscheduled patient-initiated inquiries (28.3% vs. 6.4%) compared to traditional phone calls, likely due to a lack of adaptive response capabilities.

Objective: This study aims to evaluate an enhanced technological iteration of our follow-up platform. By integrating an Artificial Intelligence (AI) interface trained on specialized clinical protocols, the new system is designed to provide automated, personalized and adaptive recommendations to patients.

Methods and Intervention: The study will compare the effectiveness of this AI-driven platform against the previous version of the non-adaptive automated messaging system. The primary outcome is to compare the number of patient-initiated inquiries (re-consultations). Secondary outcomes include patient satisfaction, adherence to the follow-up protocol, and response rates from postoperative days one through three.

Impact: The investigators hypothesize that the integration of AI will optimize human resources and improve patient autonomy without compromising safety or satisfaction, ultimately providing a scalable model for postoperative regional analgesia monitoring.