Strong Kidney Initiative Trial for Dialysis Care Quality

NCT ID: NCT05240573

Last Updated: 2023-05-06

Basic Information

• Recruitment Status: ACTIVE_NOT_RECRUITING
• Clinical Phase: NA
• Total Enrollment: 1200 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2023-05-01
• Study Completion Date: 2025-11-30

Brief Summary

Chronic kidney disease (CKD) is an important global health issue that imposes a substantial healthcare burden in both developing and developed economies. The global prevalence of CKD-related mortality was estimated from 9.6 per 100,000 in 1990 to 11.1 per 100,000 in 2010, and the global prevalence of end-stage kidney disease (ESRD) was estimated from 75.9 per 100,000 in 2005 to 100.7 per 100,000 in 2010. In Taiwan, a long-lasting epidemic of CKD has created critical economic and social challenges in its health care system. Over the past 20 years, the annual incidence and prevalence of ESRD in Taiwan have surged from 126 to 361 per million and from 382 to 2,584 per million, respectively. National Health Insurance Bureau in Taiwan has spent a huge budget to support healthcare for ESRD patients requiring maintenance dialysis therapy without observing significant improvement in ESRD prevention and management.

The main challenge in effectively preventing and managing ESRD is to obtain the full-spectrum data, such as lifestyle, diet, over-the-counter medication use, Chinese herbal medication use, and the occurrence of unaware outpatient acute kidney injury, on patients with CKD. This unmeasured information regarding patient's daily life is crucial because patients spend most of their time outside the hospital, even for patients receiving hemodialysis 3-4 times per week spend only 10% of their daily life in the healthcare facility. With the digital transformation of the healthcare system and the blockchain technology brought by the advances in data storage, data transfer, data safety, and computing power, collecting and exchanging comprehensive data becomes possible.

The investigators will establish a full-spectrum kidney database by re-organizing all kidney-related clinical data that were generated in China Medical University Healthcare System (CMUH) and Asia University Healthcare System (AUH), integrating data collected in the dialysis outpatient clinic at CMUH and AUH, such as gait data, grip data, and skin image, combining daily life data such as diet, exercise, and sleeping condition collected from the Strong Kidney Initiative APP (SKI APP) or wearable devices. The investigators will then use the SKI APP and blockchain technology to provide digital service to dialysis patients and to prospectively collect daily life data. The digital service would include the visualization of real-time kidney data, kidney care recommendations, and innovative artificial intelligence-based services for kidney health prediction and suggestion.

This proposed clinical trial aims to evaluate the clinical effectiveness of SKI digital services regarding the outcomes of the rate of emergency department (ED) visits, inpatient admission rate, kidney function improvement, mortality, and healthcare utilization in dialysis patients in 12 months. The clinical trial will be conducted on the patients who regularly receive hemodialysis care from the CMUH and AUH Healthcare Systems. Patients assigned to the intervention arm will be provided the SKI APP and related digital services and patients assigned to the control arm will be provided the ordinary CMUH dialysis care APP. The investigators will provide an education program for the APP and monitor the utilization of APP. The investigators hypothesize that patients receiving the SKI APP will have lower ED and inpatient admission rates, better kidney function maintenance, lower mortality, and decreased healthcare utilization. The results of the SKI trial will provide solid evidence regarding the real-world effectiveness of a comprehensive intelligent kidney care digital service using blockchain technology.

Conditions

Hemodialysis Complication

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: HEALTH_SERVICES_RESEARCH
• Blinding Strategy: NONE

Study Groups

SKI App

Group Type: EXPERIMENTAL

SKI App

Intervention Type: OTHER

The intervention for the SKI App digital service will include the visualization of real-time kidney data, the kidney care recommendation, and innovative artificial intelligence-based services for kidney health prediction and suggestion.

The intervention for the CMUH Dialysis Care App digital service will include simple records of blood pressure, medication records, and routine health education information.

CMUH Dialysis Care App

Group Type: ACTIVE_COMPARATOR

SKI App

Intervention Type: OTHER

The intervention for the SKI App digital service will include the visualization of real-time kidney data, the kidney care recommendation, and innovative artificial intelligence-based services for kidney health prediction and suggestion.

The intervention for the CMUH Dialysis Care App digital service will include simple records of blood pressure, medication records, and routine health education information.

Interventions

SKI App

The intervention for the SKI App digital service will include the visualization of real-time kidney data, the kidney care recommendation, and innovative artificial intelligence-based services for kidney health prediction and suggestion.

The intervention for the CMUH Dialysis Care App digital service will include simple records of blood pressure, medication records, and routine health education information.

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• Patients who receive hemodialysis care at CMUH and AUH Healthcare Systems and agree to participate in this trial.

Exclusion Criteria

• Patients who do not receive regular hemodialysis care at CMUH and AUH Healthcare Systems;
• Patients who do not have a mobile device;
• Patients who have the capacity/literacy of using an APP;
• Patients who do not agree to participate.

• Minimum Eligible Age: 20 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Ministry of Science and Technology, Taiwan

OTHER_GOV

Sponsor Role: collaborator

China Medical University Hospital

OTHER

Sponsor Role: lead

Responsible Party

Chin-Chi Kuo

Director of Big Data Center

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

China Medical University Hospital

Taichung, , Taiwan

Countries

Taiwan

Other Identifiers

CMUH109-REC3-156

Identifier Type: -

Identifier Source: org_study_id