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

Postoperative Follow-up Via Artificial Intelligence-Based Application Versus Automated Messaging Application in Patients Receiving Continuous Regional Analgesia: A Comparative Study

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 Overview

• Status: Not yet recruiting
• Conditions: Anesthesia; Regional Anesthesia Success; Regional Anesthesia; Anesthesia , Analgesia
• Intervention / Treatment: Other: AI-driven follow-up platform; Other: Satisfaction; Other: Adherence to the follow-up protocol; Other: Response rates from postoperative days one through three

• Study Type: Interventional
• Enrollment (Estimated): 166
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Felipe Yañez Herrera; Phone Number: +56988129267; Email: feliyanezherrera@gmail.com
• Study Contact Backup: Name: Pontificia Universidad Catolica de Chile

Study Locations

• Chile
  • Santiago, Chile
    • Region Metropolitana de Chile
    • Contact: Felipe Yañez Herrera; Phone Number: +5698129267; Email: feliyanezherrera@gmail.com

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• Patients aged between 18 and 75 years.
• Physical status classification ASA I or II.
• Scheduled for ambulatory surgical programs at UC Christus Health Network centers (Hospital Clínico, Clínica San Carlos de Apoquindo, or Centro Médico Santa Lucía).
• Patients receiving postoperative pain management via continuous peripheral nerve block (CPNB) with a perineural catheter and disposable infusion pump.
• Ownership and documented proficiency in operating a smartphone to access the mobile application.
• Provision of written informed consent.

Exclusion Criteria:

• Inability to understand or follow the digital monitoring protocol.
• Patients not meeting the age or ASA physical status requirements.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Health Services Research
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: AI-App; Artificial Intelligence-driven application	Other: AI-driven follow-up platform; 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.; Other: Satisfaction; Register patient satisfaction, adherence to the follow-up protocol, and response rates from postoperative days one through three; Other: Adherence to the follow-up protocol; Register patient satisfaction, adherence to the follow-up protocol, and response rates from postoperative days one through three; Other: 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
Active Comparator: Control-App; Standard automated messaging application	Other: Satisfaction; Register patient satisfaction, adherence to the follow-up protocol, and response rates from postoperative days one through three; Other: Adherence to the follow-up protocol; Register patient satisfaction, adherence to the follow-up protocol, and response rates from postoperative days one through three; Other: 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

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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.	From registration to the end of the 3-day outpatient postoperative follow-up

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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.	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.	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.	From registration to the end of the 3-day outpatient postoperative follow-up

Collaborators and Investigators

• Sponsor: Pontificia Universidad Catolica de Chile
• Investigators: Principal Investigator: Felipe Yañez Herrera, Pontificia Universidad Catolica de Chile

Publications and helpful links

General Publications

• 9. Semple J, Sharpe S, Murnaghan M, Theodoropoulos J, Metcalfe K Using a Mobile App for Monitoring Post-Operative Quality of Recovery of Patients at Home: A Feasibility Study JMIR Mhealth Uhealth 2015;3(1):e18 URL: https://mhealth.jmir.org/2015/1/e18 DOI: 10.2196/mhealth.3929
• 8. Poonam Pai, B. H., & Lai, Y. H. (2022). Regional anesthesia and pain medicine. Regional Anesthesia and Pain Medicine, 47(2), 144-145. doi:https://doi.org/10.1136/rapm-2021-102939
• 7. Implementation of an Automated Text Message-Based System for Tracking Patient-Reported Outcomes in Spine Surgery: An Overview of the Concept and Our Early Experience Author links open overlay panelAlexander Perdomo-Pantoja, Safwan Alomari, Daniel Lubelski, Ann Liu, Trevor DeMordaunt, Ali Bydon, Timothy F. Witham, Nicholas Theodore
• 6. Miller HN, Voils CI, Cronin KA, Jeanes E, Hawley J, Porter LS, Adler RR, Sharp W, Pabich S, Gavin KL, Lewis MA, Johnson HM, Yancy WS Jr, Gray KE, Shaw RJ. A Method to Deliver Automated and Tailored Intervention Content: 24-month Clinical Trial. JMIR Form Res. 2022 Sep 6;6(9):e38262. doi: 10.2196/38262. PMID: 36066936; PMCID: PMC9490532
• 5. Gessner D, Hunter OO, Kou A, Mariano ER. Automated text messaging follow-up for patients who receive peripheral nerve blocks. Reg Anesth Pain Med. 2021 Jun;46(6):524-528. doi: 10.1136/rapm-2021-102472. Epub 2021 Mar 1. PMID: 33649155.
• 4. Van der Velde M, Valkenet K, Geleijn E, Kruisselbrink M, Marsman M, Janssen LM, Ruurda JP, van der Peet DL, Aarden JJ, Veenhof C, van der Leeden M. Usability and Preliminary Effectiveness of a Preoperative mHealth App for People Undergoing Major Surgery: Pilot Randomized Controlled Trial. JMIR Mhealth Uhealth. 2021 Jan 7;9(1):e23402. doi: 10.2196/23402. PMID: 33410758; PMCID: PMC7819776.
• 3. Highland KB, Tran J, Edwards H, Bedocs P, Suen J, Buckenmaier CC. Feasibility of App-Based Postsurgical Assessment of Pain, Pain Impact, and Regional Anesthesia Effects: A Pilot Randomized Controlled Trial. Pain Med. 2019 Aug 1;20(8):1592-1599. doi: 10.1093/pm/pny288. PMID: 30726985.
• 2. Usability Measurement of Mobile Applications with System Usability Scale (SUS) - Aycan Kaya, Reha Ozturk and Cigdem Altin Gumussoy
• 1. Gavyn Ooi1 & Eric S. Schwenk2 & Marc C. Torjman2 & Kent Berg2. A Randomized Trial of Manual Phone Calls Versus Automated Text Messages for Peripheral Nerve Block Follow-Ups

Study record dates

Study Major Dates

• Study Start (Estimated): April 1, 2026
• Primary Completion (Estimated): July 1, 2026
• Study Completion (Estimated): July 1, 2027

Study Registration Dates

• First Submitted: March 24, 2026
• First Submitted That Met QC Criteria: April 1, 2026
• First Posted (Actual): April 3, 2026

Study Record Updates

• Last Update Posted (Actual): April 3, 2026
• Last Update Submitted That Met QC Criteria: April 1, 2026
• Last Verified: March 1, 2026

More Information

Terms related to this study

• Keywords: Anesthesia; Regional Anesthesia; Continuous Nerve Block; Ambulatory; Outpatient follow-up
• Additional Relevant MeSH Terms: Neurologic Manifestations; Nervous System Diseases; Neurobehavioral Manifestations; Perceptual Disorders; Pathological Conditions, Signs and Symptoms; Signs and Symptoms; Agnosia; Organization and Administration; Health Services Administration; Delivery of Health Care; Health Care Quality, Access, and Evaluation; Patient Care Management; Personnel Management; Work Engagement; Physician Engagement
• Other Study ID Numbers: 250312009

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No