Effectiveness of eHealth on the Self-management of Health Status and QOL Among CAD Patients

Effectiveness of eHealth on the Self-management, Physiological Health and Quality of Life Among Coronary Artery Disease Patients

This article uses the smart medical case management tracking system, combined with various terminal devices to fully record the measured data (pulse, blood pressure) for case home care tracking to prevent the occurrence and deterioration of the disease. Therefore, with the promotion of the eHealth medical staff and members of the family can instantly grasp the health of the body and cultivate the habits of self-health management and enhance the quality of care. Therefore, we hope to use the Smart Health Cloud as an interventional measure to improve the care of patients with coronary artery disease, improve self-management ability and quality of life.

Study Overview

• Status: Completed
• Conditions: Coronary Artery Disease; Quality of Life; eHealth; Self-management
• Intervention / Treatment: Combination product: eHealth

Detailed Description

The World Health Organization points out that cardiovascular disease is the number one killer of global deaths, killing 17.1 million people worldwide each year, accounting for 31% of the world's total deaths. Heart disease is the second leading cause of death in China. Coronary artery disease (CAD) is the majority, and coronary artery disease is the most common cardiovascular disease. Good self-management can reduce disease risk factors and improve related prognosis. It is also an important issue in health promotion around the world. This article uses the smart medical case management tracking system, combined with various terminal devices to fully record the measured data (pulse, blood pressure) for case home care tracking to prevent the occurrence and deterioration of the disease. Therefore, with the promotion of the eHealth medical staff and members of the family can instantly grasp the health of the body and cultivate the habits of self-health management and enhance the quality of care. Therefore, we hope to use the Smart Health Cloud as an interventional measure to improve the care of patients with coronary artery disease, improve self-management ability and quality of life.

• Study Type: Interventional
• Enrollment (Actual): 60
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Taiwan
  • Taipei city, Taiwan
    • TSGH

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

Inclusion Criteria:

• A patient who is 20 years of age or older and has a Coronary computed tomography angiography >50% vascular stenosis, has been PTCA、stent or CABG
• Taiwanese, understand Chinese

Exclusion Criteria:

• Those who can't express their wishes clearly (such as Azheimer's disease, mental dysfunction)
• mental disorder
• infectious diseases
• Patients who participate in other research projects

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Health Services Research
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: eHealth; Provide home physiology measurement services, including automatic uploading of measured blood pressure values to the cloud, serial back-end education platform to provide numerical anomaly alarms and health care notifications, monthly measurement data reports, combined with mobile APP management system for immediate enquiry . In addition to the electric visit to the patient's health education guidance, the content includes: 1. Encourage the walking exercise to perform 2. Ask the walking exercise execution progress, please return the daily value of the case to facilitate the record 3. Answer the relevant questions asked during the intervention.	Combination product: eHealth; The study was randomized (wait-list-control), and it was estimated that 60 subjects were randomly assigned to the immediate treatment group and the wait-list-control group. The two groups were tested for baseline before intervention in the eHealth. After the first questionnaire evaluation, the experimental group was involved in the eHealth for three months, and after three months, the experimental group and the waiting intervention control group were post-tested. To assess the effectiveness of the two groups before and after the eHealth . Control group that waits for intervention in the fourth month from the beginning of the fourth month to the end of the sixth month
Experimental: wait list control; wait list control for 3 months and then Provide home physiology measurement services, including automatic uploading of measured blood pressure values to the cloud, serial back-end education platform to provide numerical anomaly alarms and health care notifications, monthly measurement data reports, combined with mobile APP management system for immediate enquiry . In addition to the electric visit to the patient's health education guidance, the content includes: 1. Encourage the walking exercise to perform 2. Ask the walking exercise execution progress, please return the daily value of the case to facilitate the record 3. Answer the relevant questions asked during the intervention.	Combination product: eHealth; The study was randomized (wait-list-control), and it was estimated that 60 subjects were randomly assigned to the immediate treatment group and the wait-list-control group. The two groups were tested for baseline before intervention in the eHealth. After the first questionnaire evaluation, the experimental group was involved in the eHealth for three months, and after three months, the experimental group and the waiting intervention control group were post-tested. To assess the effectiveness of the two groups before and after the eHealth . Control group that waits for intervention in the fourth month from the beginning of the fourth month to the end of the sixth month

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
physiological indicators-HDL-C(T1)	HDL-C, the unit is mg/dL	T1-baseline
physiological indicators-HDL-C(T2)	HDL-C, the unit is mg/dL	T2-three months later
physiological indicators-HDL-C(T3)	HDL-C, the unit is mg/dL	T3-six months later
physiological indicators-LDL-C(T1)	LDL-C, the unit is mg/dL	T1-baseline
physiological indicators-LDL-C(T2)	LDL-C, the unit is mg/dL	T2-three months later
physiological indicators-LDL-C(T3)	LDL-C, the unit is mg/dL	T3-six months later
physiological indicators-Total Cholesterol(T1)	Total Cholesterol, the unit is mg/dL	T1-baseline
physiological indicators-Total Cholesterol(T2)	Total Cholesterol, the unit is mg/dL	T2-three months later
physiological indicators-Total Cholesterol(T3)	Total Cholesterol, the unit is mg/dL	T3-six months later
physiological indicators-Triglyceride(T1)	Triglyceride, the unit is mg/dL	T1-baseline
physiological indicators-Triglyceride(T2)	Triglyceride, the unit is mg/dL	T2-three months later
physiological indicators-Triglyceride(T3)	Triglyceride, the unit is mg/dL	T3-six months later
physiological indicators-GLU(T1)	GLU, the unit is mg/dL	T1-baseline
physiological indicators-GLU(T2)	GLU, the unit is mg/dL	T2-three months later
physiological indicators-GLU(T3)	GLU, the unit is mg/dL	T3-six months later
physiological indicators-HbA1C(T1)	HbA1C, the unit is %	T1-baseline
physiological indicators-HbA1C(T2)	HbA1C, the unit is %	T2-three months later
physiological indicators-HbA1C(T3)	HbA1C, the unit is %	T3-six months later

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
self-management-T1	use The partners in Health scale. total of 12 questions,The scoring method uses the nine-point Likert Scales score. The score of 0 is divided into self-management performance, and the score of 8 indicates that self-management is good. The total score is 96 points. The higher the score, the better the self-management.	T1-baseline
self-management-T2	use The partners in Health scale. total of 12 questions,The scoring method uses the nine-point Likert Scales score. The score of 0 is divided into self-management performance, and the score of 8 indicates that self-management is good. The total score is 96 points. The higher the score, the better the self-management.	T2-three months later
self-management-T3	use The partners in Health scale. total of 12 questions,The scoring method uses the nine-point Likert Scales score. The score of 0 is divided into self-management performance, and the score of 8 indicates that self-management is good. The total score is 96 points. The higher the score, the better the self-management.	T3-six months later

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Quality of life scale-T1	use WHOQOL-BREF Taiwan Version. total of 28 questions,The scoring method uses the five-point Likert Scales score The questionnaire has a total of 28 questions, with at least one point for each question and a maximum of five points. The higher the score, the better the quality of life.	T1-baseline
Quality of life scale-T2	use WHOQOL-BREF Taiwan Version. total of 28 questions,The scoring method uses the five-point Likert Scales score The questionnaire has a total of 28 questions, with at least one point for each question and a maximum of five points. The higher the score, the better the quality of life.	T2-three months later
Quality of life scale-T3	use WHOQOL-BREF Taiwan Version. total of 28 questions,The scoring method uses the five-point Likert Scales score The questionnaire has a total of 28 questions, with at least one point for each question and a maximum of five points. The higher the score, the better the quality of life.	T3-six months later
Modified Health care machine rating scale	There are three questions in the satisfaction survey. Use category options to measure usage satisfaction	T2-three months later

Collaborators and Investigators

• Sponsor: National Defense Medical Center, Taiwan

Study record dates

Study Major Dates

• Study Start (Actual): September 18, 2019
• Primary Completion (Actual): July 15, 2020
• Study Completion (Actual): October 5, 2020

Study Registration Dates

• First Submitted: October 22, 2019
• First Submitted That Met QC Criteria: October 29, 2019
• First Posted (Actual): October 31, 2019

Study Record Updates

• Last Update Posted (Actual): March 3, 2021
• Last Update Submitted That Met QC Criteria: March 1, 2021
• Last Verified: March 1, 2021

More Information

Terms related to this study

• Keywords: Coronary artery disease; Quality of Life; self-management; artificial intelligence; Remote Care
• Additional Relevant MeSH Terms: Heart Diseases; Cardiovascular Diseases; Vascular Diseases; Arteriosclerosis; Arterial Occlusive Diseases; Coronary Artery Disease; Myocardial Ischemia; Coronary Disease
• Other Study ID Numbers: 2-108-05-132

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