Clinical Intelligent Management System Pragmatic RCT

NCT06893068 | Recruiting

• 1 other identifier: 2024-22
• Study Type: interventional
• Target: 204
• Locations: 1 country
• Sites: 1

Brief Summary

This study aims to evaluate the effectiveness of a clinical intelligent management system, based on a multimodal foundational model, in improving the quality of primary care at a community health service center. Using a prospective, randomized controlled, single-blind study design, the trial will include primary care physicians and adult patients seeking care at the Tiantongyuanbei Community Health Service Center and Shanghai Health and Medical Center. Physicians in the intervention group will utilize the intelligent management system with AR glasses to aid in diagnosis and treatment, while patients will engage with the system's patient interface to access health education, follow-up reminders, and AI-powered home consultation features. In contrast, physicians in the control group will provide routine diagnoses and treatments, with their patients receiving standard health education and follow-up care. The trial was designed with the assistance of a digital twin-based clinical research system (termed X Town). By comprehensively evaluating diagnostic quality, physicians' clinical abilities, patient-reported outcomes, and system appraisals, this study will assess the effectiveness of the clinical intelligent management system in enhancing the quality of primary care and patient management.

Conditions

Primary Care Diseases

Outcome Measures

Primary Outcomes (1)

• Comprehensive Assessment of clinical performance

  Primary Care Quaility Assessment Scales (range: 0 to 100 for each case; the higher scores means the better performance)

  From enrollment to the end of treatment at 3 months of all recruited cases

Secondary Outcomes (1)

• AI-System's appraisal

  At the end of 3 months

Study Arms (2)

AI-assist group

EXPERIMENTAL

Physicians in the intervention group will employ the intelligent management system with AR glasses to assist in diagnosis and treatment, while patients will interact with the system's patient interface to access health education, follow-up reminders, and AI-powered home consultation features.

Device: AI-based clinical intelligent management system

Traditional group

NO INTERVENTION

Physicians in the control group will conduct routine diagnoses and treatments, while patients will receive standard health education and follow-up care.

Interventions

AI-based clinical intelligent management system DEVICE

The clinical intelligent management system, integrated with AR glasses and powered by a multimodal foundational model, is designed to improve the quality of outpatient care at community health service centers.

AI-assist group

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Age ≥18 years
• Receiving care at a community health service center
• Able to understand and comply with the study procedures
• Agrees to participate in the study and signs the informed consent form

You may not qualify if:

• Patients with severe mental illness
• Patients unable to independently complete the questionnaire
• Patients expected to be unable to complete follow-ups within three months

Sponsors & Collaborators

• Tsinghua University: lead

Study Sites (1)

Shanghai Health and Medical Center

Wuxi, Jiangsu, 214065, China

RECRUITING

Study Officials

• Tien Yin Wong

  Tsinghua University

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Jing Gu

CONTACT

86+(510)82335104; g950324@163.com

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: OUTCOMES ASSESSOR
• Purpose: SUPPORTIVE CARE
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: February 12, 2025
• First Posted: March 25, 2025
• Study Start: April 13, 2025
• Primary Completion: June 30, 2025
• Study Completion: July 31, 2025
• Last Updated: May 16, 2025

Record last verified: 2025-05

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)