Abstract: This paper proposes a better way to represent the architecture of LARIISA, an intelligent system for decision making in healthcare. The proposed representation weaves health and computational domains in a multidimensional architecture, which facilitates the visualization of specialized applications added to the LARIISA framework. New concepts as Big Data, Internet of Things and Linked Data are also introduced to the proposed architecture. Acquiring new data from different sources to the LARIISA database, and making use of it, will permit a more efficient decision-making process for the system.

Abstract: VITESSE is a low cost system to support users in two scenarios: home care and accidents (fainting, trampling, etc.). Initially, the system was based on the digital TV technology in scenarios of home care. Nowadays, the system adds new functions to support urgent and emergency care of individuals in mobility. In both cases, the key idea of VITESSE is to improve the time of consuming process, taking into account the real time and contextual information, in particular in the case of accidents of mobile users. Therefore, VITESSE is a context-aware system that makes use of the concept of Internet of Things (IoT) and ontologies in the process of generating inferences, increasing the efficiency of health care systems.

Abstract: The home care consists in a form of primary care performed by a lay caregiver, a specialist or a multidisciplinary team. This modality is applied in elderly people or patients in treatment of chronic disease who are not at risk of death. The aim of this work is to present a set of context-aware health applications in a prototype of software and hardware that will assist caregivers and/or patients in home care situations. For this, a Set-Top Box (STB) connected to a TV with access to the Internet is used as a way of user interaction, which may enter information about its current state. Furthermore, health sensors can be used to capture data continuously to feed the system. The raw data and information provided by the user are later used, allowing, then, an inference about the patient condition.

Abstract: Health care services can be scarce and expensive in some countries and especially in isolated regions. The lack of information can degrade health care services, for example, by ineffective resource allocation or failure in epidemiological prediction. This paper proposes an architecture for system of decision making and service provisioning in the health care context. It encompasses and integrates data produced by environmental sensors installed in the assisted homes, medical data sets, domainspecific and semantic enriched data sets, and all data generated and collected in applications installed on mobile phones, wearable devices, desktops, web servers, and smart television. LARIISA architecture is presented as a platform to manage, provide and launch services that monitor and analyze data to supply relevant information to decision makers and health care actors that participate in the health care supply chain

Many intrinsically related determinants of health and disease exist, including social and economic status, education, employment, housing, and physical and environmental exposures. These factors interact to cumulatively affect health and disease burden of individuals and populations, and to establish health inequities and disparities across and within countries. Biomedical models of health care decrease adverse consequences of disease, but are not enough to effectively improve individual and population health and advance health equity. Social determinants of health are especially important in Latin American countries, which are characterised by adverse colonial legacies, tremendous social injustice, huge socioeconomic disparities, and wide health inequities.

Abstract: Starting in the late 1980s, many Latin American countries began social sector reforms to alleviate poverty, reduce socioeconomic inequalities, improve health outcomes, and provide financial risk protection. In particular, starting in the 1990s, reforms aimed at strengthening health systems to reduce inequalities in health access and outcomes focused on expansion of universal health coverage, especially for poor citizens. In Latin America, health-system reforms have produced a distinct approach to universal health coverage, underpinned by the principles of equity, solidarity, and collective action to overcome social inequalities. In most of the countries studied, government financing enabled the introduction of supply-side interventions to expand insurance coverage for uninsured citizens—with defined and enlarged benefits packages—and to scale up delivery of health services. Countries such as Brazil and Cuba introduced tax-financed universal health systems. These changes were combined with demand-side interventions aimed at alleviating poverty (targeting many social determinants of health) and improving access of the most disadvantaged populations. Hence, the distinguishing features of health-system strengthening for universal health coverage and lessons from the Latin American experience are relevant for countries advancing universal health coverage.

Abstract: This paper presents improvements of LARIISA, a framework that makes use of context-aware information to support decision-making and governance in the public health area. More specifically, two relevant e-health applications are presented to illustrate the LARIISA system. The first one uses Bayesian networks in dengue scenarios. The second application uses ontology to manage home care scenarios. In both cases, the contributions related to the LARIISA framework include patient health diagnosis provided remotely, support for decision-making health systems, and context information for context-aware health systems.

Abstract: LARIISA is a framework that makes use of context-aware to support decision-making and governancein the public health area. This paper presents the CLARIISA, an evolution of LARIISA towards an intelligent classifier model for enhancing the decision making process. Two applications are shown to illustratethe upgrade on the LARIISA system. The first one uses the Bayesian networks on a dengue case. The second uses ontology to manage home care scenarios. In both cases, the contributions related to our framework include patient health diagnosis provided remotely, support for decision making health systems, and context information for context-aware health systems.

Abstract: Introduction: The Brazilian National Health System May Reduce Inequalities In Access To Health Services Through Strategies That Can Reach Those Most In Need With no Access To Care Services. Objective: To Identify Factors Associated With The Use Of Health Service By Children Aged 5 To 9 Years In The City Of Sobral, Ceará, Northeastern Brazil. Results: Only 558 (17.0%) Children Used Health Care Services In The 30 Days Preceding This Survey. Children With Any Health Condition (or = 3.90) Who Were Frequent Attenders Of Primary Care Strategy Of Organization (the Family Health Strategy, Fhs) (or = 1.81) And Living In The City's Urban Area (or = 1.51) Were More Likely To Use Health Services. Almost 80% Of Children Used Fhs as Their Referral Care Service. Children From Poorer Families And With Easier Access To Services Were More Likely To Be Fhs Users. Conclusion: The Study Showed That Access To Health Services Has Been Relatively Equitable Through The Fhs, a Point Of Entry To The Local Health System. Social Determinants Of Health; Health Service/utilization; Health Services Accessibility; Equity; Family Health; Child Health Services

Agradeço a oportunidade de participar dessa discussão que envolve tema tão relevante para o SUS. Oswaldo Tanaka nos brinda com um texto instigante e oportuno, face aos desafios apresentados para o estabelecimento de sistemas universais de saúde, principalmente no que diz respeito aos três domínios analisados: gestão, avaliação e tomada de decisão.