The COVID-19 pandemic had put pressure on various national healthcare systems, due to the lack of health professionals and exhaustion of those avaliable, as well as lack of interoperability and inability to restructure their IT systems. Therefore, the restructuring of institutions at all levels is essential, especially at the level of their information systems. Furthermore, the COVID-19 pandemic had arrived in Portugal at March 2020, with a breakout on the northern region. In order to quickly respond to the pandemic, the CHUP healthcare institution, known as a research center, has embraced the challenge of developing and integrating a new approach based on the openEHR standard to interoperate with the institution’s existing information and its systems. An openEHR clinical modelling methodology was outlined and adopted, followed by a survey of daily clinical and technical requirements. With the arrival of the virus in Portugal, the CHUP institution has undergone through constant changes in their working methodologies as well as their openEHR modelling. As a result, an openEHR patient care workflow for COVID-19 was developed.

The COVID-19 pandemic has reinforced the importance and impact of telemedicine and multichannel interactions in healthcare services provided to patients. Health professionals are in turn increasingly dependent on patient data collected through multichannel interactions to make their clinical decisions. This article intends to present a brief analysis from the viewpoint of health professionals regarding the use of technologies in telemedicine and multichannel interactions to support decision making, basing on the analysis of clinical data of patients collected in a telemedicine environment. These technologies have numerous advantages for healthcare professionals and patients, but there are also some obstacles and gaps inherent that need to be overcome. Furthermore, health professionals can perform a more detailed analysis of patient data before taking any decision, as this practice promotes data collection to facilitate the decision-making process of health professionals.

In the healthcare industry, the patient's nutrition is a key factor in their treatment process. Every user has their own specific nutritional needs and requirements. An appropriate nutrition policy can therefore help the patient's recovery process and alleviate possible symptoms. Food recommender systems are platforms that offer personalised suggestions of recipes to users. However, there is a lack of usage of recipe recommendation systems in the healthcare sector. Multiple challenges in representing the domain of food and the patient's needs make it complicated to implement these systems. The present project aims to develop a platform for an intelligent planning of the user's meals, based on their clinical conditions. The application of machine learning algorithms on nutrition, in healthcare services and continuous care is thus a key topic of research. This platform will be tested and deployed at the Social Canteen of Vila Verde (Cantina Social da Santa Casa da Misericórdia de Vila Verde). The development of this project will use the Design Science Research (DSR) investigation methodology, ensuring that the solution to the problem accomplishes all needs and requirements of the professionals, while elucidating new knowledge both for the institution and the scientific community.

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The processing of information in real-time (through the processing of complex events) has become an essential task for the optimal functioning of manufacturing plants. Only in this way can artificial intelligence, data extraction, and even business intelligence techniques be applied, and the data produced daily be used in a beneficent way, enhancing automation processes and improving service delivery. Therefore, professionals and researchers need a wide range of tools to extract, transform, and load data in real-time efficiently. Additionally, the same tool supports or at least facilitates the visualization of this data intuitively and interactively. The review presented in this document aims to provide an up-to-date review of the various tools available to perform these tasks. Of the selected tools, a brief description of how they work, as well as the advantages and disadvantages of their use, will be presented. Furthermore, a critical analysis of overall operation and performance will be presented. Finally, a hybrid architecture that aims to synergize all tools and technologies is presented and discussed.