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AI Chatbot-Enabled ePRO Monitoring and Nurse-Led Self-Management for Early-Stage Cardiovascular-Kidney-Metabolic Syndrome
Sponsor: Taipei Medical University
Summary
This randomized controlled trial will evaluate the effectiveness of an AI chatbot-enabled electronic patient-reported outcome (ePRO) monitoring and nurse-led self-management intervention for adults with early-stage cardiovascular-kidney-metabolic (CKM) syndrome. A total of 80 participants will be randomly assigned to either the intervention or control group and followed for 6 months. Participants in the intervention group will complete weekly ePRO assessments through an AI-enabled platform and receive individualized feedback, self-management support, and nurse-led clinical follow-up when indicated. Participants in the control group will receive usual care and complete weekly ePRO assessments through a non-AI platform without automated feedback or structured nurse-led support. Outcomes will be assessed at baseline, 3 months, and 6 months and will include patient-reported health outcomes, patient activation, health literacy, healthcare utilization, and changes in CKM syndrome stage.
Official title: AI Chatbot-Enabled ePRO Monitoring and Nurse-Led Self-Management for Early-Stage Cardiovascular-Kidney-Metabolic Syndrome: A Randomized Controlled Trial
Key Details
Gender
All
Age Range
40 Years - Any
Study Type
INTERVENTIONAL
Enrollment
80
Start Date
2026-10-01
Completion Date
2029-07-31
Last Updated
2026-10-05
Healthy Volunteers
No
Conditions
Interventions
AI chatbot-enabled nurse-led program.
Participants in the intervention group will receive a six-month nurse-led, AI chatbot-enabled symptom monitoring and self-management program integrating weekly ePRO assessments. The intervention begins with a structured nurse-led intake session including CKM assessment, symptom review, goal setting, and training on chatbot use. Participants complete weekly PROMIS-29 v2.1 assessments via a smartphone-based chatbot, which provides automated, rule-based feedback, self-management guidance, and motivational prompts. A risk-stratification algorithm generates alerts when symptom deterioration is detected. Nurses review alerts daily and provide follow-up via messaging, teleconsultation, or referral depending on severity, with same-day escalation for high-risk symptoms.
Usual Care
Usual care based on standard outpatient follow-up, without access to the AI chatbot or nurse-led coordination
Locations (1)
Taipei Medical University
Taipei, No. 250號, Wuxing St, Xinyi District, Taipei City, 110, Taiwan