This research aims to create a remote system to reduce the Hospital load for patients with chronic diseases at Home or Recover Centers. A framework of shared Artificial intelligence services is proposed to provide a secure environment for remote patient monitoring. A literature review using the PRISMA methodology provides a knowledge systematization. A new data fusion process with data, image, text, and voice allows for improving remote patient data collected. We apply Design Science Research with CRISP-DM approach to handling the data process. We are developing specific modules to fuse and handle image, voice, text and data. Our model is being validated and applied in a real case from a Portuguese hospital using Alzheimer’s patients. In our research work, we propose a framework for secure information sharing among patients’ data and improving health care services. This approach allows the creation of big data systems in a fusion of image, text, voice, and data. The quick development of AI and associated technologies would assist healthcare providers in enhancing patient value and streamlining operational procedures. In this study, we examined how AI technology with data fusion for chronic patients allows professional hospital visits and reduces their workload. Effective management of these opportunities and challenges requires the joint knowledge and tenacity of all healthcare industry players.