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.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
SINGLE
Enrollment
166
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.
Register patient satisfaction, adherence to the follow-up protocol, and response rates from postoperative days one through three
Register patient satisfaction, adherence to the follow-up protocol, and response rates from postoperative days one through three
Register patient satisfaction, adherence to the follow-up protocol, and response rates from postoperative days one through three
Region Metropolitana de Chile
Santiago, Chile
Comparison of patient-initiated inquiry rates between AI-App and Control-App
Comparison of patient-initiated inquiry rates between the Artificial Intelligence-driven application (AI-App) and the standard automated messaging application (Control-App) during ambulatory postoperative follow-up.
Time frame: From registration to the end of the 3-day outpatient postoperative follow-up
Engage with the AI-driven app
Proportion of patients who successfully engage with the AI-driven application. This includes a cumulative analysis over the 3-day follow-up period and a granular day-to-day response analysis.
Time frame: From registration to the end of the 3-day outpatient postoperative follow-up
Assessment patient satisfaction
Assessment and comparison of patient satisfaction scores between the AI-driven application group and the traditional telephone follow-up group, utilizing a standardized satisfaction scale survey in Spanish "Questionnaire of Satisfaction and Perceived Quality in Hospital Health Care of the Department of Studies and Development of the Superintendency of Health" (PQA). In this instrument, the patient was asked to respond using a five-point Likert scale. The extremes of the scale were labelled 'very poor' to 'definitely yes' depending upon the question. Patient responses to each PQA Likert scale and visual analogue questions were scored from 1 to 5. The performance score was defined as the proportion of patients with an unsatisfactory patient response. A quality index was calculated for each PQA question by multiplying the importance score against the performance score.
Time frame: From registration to the end of the 3-day outpatient postoperative follow-up
Adherence between the Control-App and AI-App
Comparative analysis of patient adherence between the standard automated messaging application (Control-App) and the AI-driven application (AI-App). Adherence is defined as the successful completion of the response protocol during the three-day monitoring period.
Time frame: From registration to the end of the 3-day outpatient postoperative follow-up
Pontificia Universidad Catolica de Chile
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