To Investigate Whether a Continuous Intelligent and Automated Mobile Education System Can Improve Knowledge, Self-care, Emotional Stress, Self-efficacy and Quality of Life in Patients With Heart Failure

Study background

Heart failure is a complex disease syndrome, and patients often suffer from multiple chronic diseases. Faced with the problem of disease symptoms, if patients do not have sufficient care knowledge, patients often mistakenly think that it is related to aging, and may even delay medical treatment, resulting in the need for hospitalization when it worsens. Emergency treatment may even deal with respiratory failure in severe cases. Such repeated hospitalizations will affect the quality of life and lead to poor disease prognosis for patients. Heart failure treatment guidelines have recommended that in addition to the use of standard drugs for disease treatment, systematic and structured disease education should be provided continuously during hospitalization and after discharge to help patients effectively implement disease self-management and improve the quality of disease care, quality of life and life satisfaction. Interventional studies and comprehensive literature review data have also confirmed that disease education provided by nursing staff can significantly improve the knowledge, behavior, self-efficacy, quality of life, and reduce re-hospitalization of heart failure patients. Due to the high fluctuations in the course of heart failure and the interlocking influence of multiple comorbidities, disease care information should be provided not only during hospitalization, but also during the period of discharge and at home after the acute phase. Facing complex and ever-changing disease troubles often lead to overwhelming anxiety and negative emotional stress. For heart failure patients, it is necessary to provide individualized and continuous disease care information from hospitalization, discharge to home during the chronic stage of the disease. Educational navigation helps patients have good self-efficacy to perform self-disease management at home, and then learn to coexist with the disease and obtain a better quality of life with the disease.

In recent years, during the epidemic of Coronavirus disease 2019 (COVID-19), in order to prevent the spread of the virus, disease prevention and control organizations have recommended care and management strategies for chronic diseases through remote and other mobile health care Internet platforms. Care services should be provided to maintain the continuity of nursing education in the case of zero contact. In a survey study, it was found that information sharing through social networks during the epidemic was positively helpful for patients' self-care. It can be seen that it is acceptable to use portable mobile phones for educational interaction on heart failure. Unfortunately, most of the current applications still monitor patients' physiological parameters such as blood pressure, pulse, weight, heart rhythm and other data. Mobile devices are mainly used to predict disease risk, and the provision of care information mainly uses SMS notifications to remind return visits, or simple data responses based on the results of physiological parameters. However, these require long-term measurement data to generate feedback. Since learning is a kind of interpersonal interaction, when providing disease information, if text is simply sent through text messages, patients with insufficient knowledge and literacy may not be able to identify the key points that really need to be learned. In addition, it is fixed and not personalized. The education system cannot produce substantial effects.

In the ever-changing medical environment of the epidemic, how to enable heart failure patients to continue to receive complete disease care education from hospitalization, discharge to home is a difficult problem. Because investigators have spent two years in the past working to develop an APP software platform. This platform has an automated import system, a combination of personalized educational video software, video-specific examination questions, and learning evaluation. It measures the function of the mechanism, but it still lacks intelligent performance. In addition, our heart failure center has 15 years of clinical care resources and has completed hundreds of educational videos and a tracking database of long-term patient phone interviews. Investigators hope to use cluster analysis to classify the original data. In order to explore the needs of patients at different times and achieve intelligent docking of needs and educational videos, investigators plan to develop an automated and intelligent educational assistance system for heart failure on the mobile device "Line" platform, hoping to use the assistance system in mobile devices. The intervention continues to extend heart failure disease education from the hospital to the home follow-up period, so that patients can have a sufficient disease learning process, acquire effective self-care abilities, and thereby improve their quality of life. It is also hoped that the system developed through this research can help nursing staff meet the different care needs of patients in different disease stages despite busy clinical work. Make education personal and continuous, and reduce the number of nursing work hours while still maintaining educational quality, becoming the best clinical auxiliary tool that can be replicated in education on various diseases.

The main themes of the study