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COLORECTUM+ Digital System for Postoperative Quality Improvement in Colorectal Cancer
Sponsor: RenJi Hospital
Summary
This is a single-center, prospective, interventional study. A total of 236 colorectal cancer patients who underwent surgery will be enrolled and followed for 52 weeks. The digital healthcare quality management system, based on the COLORECTUM+ model, will be used for post-treatment quality evaluation and continuous improvement. Patients will be managed using an Internet+ post-treatment healthcare management platform. The platform integrates AI technology for real-time symptom analysis and alerts. Patients will report symptoms and health data through the platform, which will generate alerts based on symptom severity to guide appropriate interventions. Follow-up assessments will include patient adherence, satisfaction, quality of life, and healthcare utilization. The study expects to demonstrate that the digital healthcare quality management system improves follow-up rates, enhances patient adherence, reduces unplanned hospital visits, and increases overall patient satisfaction. The findings aim to provide evidence for the implementation of digital management systems in colorectal cancer post-treatment care, potentially leading to improved long-term outcomes for patients.
Official title: Construction and Application of a Digital Postoperative Medical Quality Evaluation and Promotion System for Colorectal Cancer Based on the COLORECTUM+ Model
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
INTERVENTIONAL
Enrollment
236
Start Date
2024-12-01
Completion Date
2028-06-01
Last Updated
2026-07-28
Healthy Volunteers
No
Conditions
Interventions
Mobile application follow-up
Colorectal cancer patients enrolled in the 'Internet Plus' post-treatment management platform use the digital medical quality management system based on the 'COLORECTUM+' model for quality evaluation and continuous improvement. The platform integrates AI, using natural language processing and machine learning to analyze patient-reported symptoms, automatically assess severity, and generate alerts. Alerts are classified as yellow, orange, or red. Yellow indicates mild issues with self-care recommendations; consecutive yellow alerts prompt doctor contact within 24 hours. Orange indicates moderate severity, requiring doctor intervention within 24 hours. Red alerts signify serious symptoms or high-risk medication errors, prompting immediate notification of the doctor and emergency team. The system monitors symptom changes and updates alerts to support treatment optimization.
Locations (1)
Shanghai Jiao Tong University School of Medicine, Renji Hospital
Shanghai, China