4° Encontro da Rede Referencistas - BIREME/OPAS/OMS

Objetivo 3. Assegurar uma vida saudável e promover o bem-estar para todas e todos, em todas as idades. Saiba mais: https://nacoesunidas.org/pos2015/ods3/ Plano Nacional de Saúde 2020-2023 http://portal.anvisa.gov.br/documents/281258/2890069/Plano+Nacional+de+Sa%C3%BAde+2020-2023/3282f7cf-a9d7-4053-8190-dc3c9c8c3113 Talky Beat de Twin Musicom está licenciada sob uma licença Creative Commons Attribution (https://creativecommons.org/licenses/...) Origem: http://www.twinmusicom.org/song/265/t... Artista: http://www.twinmusicom.org

1 Ano do Saúde sem Fake News: depoimento Professor Cristiano

1 Ano do Saúde sem Fake News: depoimento Cristina Belo

1 Ano do Saúde sem Fake News: depoimento Kathy Anne

1 Ano do Saúde sem Fake News: depoimento James Bispo

1 Ano do Saúde sem Fake News: depoimento Ester da Silva

1 Ano do Saúde sem Fake News: depoimento de Flávia

COVID-19: orientación y herramienta para hacer encuestas / COVID-19: guidance and tool for conducting surveys

Este documento ofrece orientación para los Estados Miembros de la Región de Europa de la OMS que deseen realizar estudios sobre las apreciaciones comportamentales relacionadas con la COVID-19. El brote pandémico de la COVID-19 está generando una carga abrumadora para los sistemas y las autoridades de salud, que deben responder con intervenciones, políticas y mensajes eficaces y apropiados.Una respuesta antipandémica o una fase de transición mal gestionadas e inoportunas pueden menoscabar los logros obtenidos de manera colectiva. La pandemia y sus restricciones pueden haber afectado el bienestar físico y mental, la cohesión social y la estabilidad económica, así como la resiliencia y la confianza de los individuos y las comunidades.

Entender la infodemia y la desinformación en la lucha contra la COVID-19 / Understanding the Infodemic and Misinformation in the fight against COVID-19 / Entenda a infodemia e a desinformação na luta contra a COVID-19

¿Qué es la infodemia? Según ha declarado la OMS, el brote de COVID-19 y la respuesta correspondiente han estado acompañados de una infodemia masiva, es decir, de una cantidad excesiva de información ‒en algunos casos correcta, en otros no‒ que dificulta que las personas encuentren fuentes confiables y orientación fidedigna cuando las necesitan. El término infodemia se refiere a un gran aumento del volumen de información relacionada con un tema particular, que puede volverse exponencial en un período corto debido a un incidente concreto como la pandemia actual. En esta situación aparecen en escena la desinformación y los rumores, junto con la manipulación de la información con intenciones dudosas. En la era de la información, este fenómeno se amplifica mediante las redes sociales, propagándose más lejos y más rápido, como un virus...

What is the Infodemic? As stated by the WHO, the COVID-19 outbreak and response has been accompanied by a massive infodemic: an overabundance of information ­ some accurate and some not ­ that makes it hard for people to find trustworthy sources and reliable guidance when they need it. Infodemic refers to a large increase in the volume of information associated with a specific topic and whose growth can occur exponentially in a short period of time due to a specific incident, such as the current pandemic. In this situation, misinformation and rumors appear on the scene, along with manipulation of information with doubtful intent. In the information age, this phenomenon is amplified through social networks, spreading farther and faster like a virus...

O que é infodemia? Conforme declarado pela OMS, o surto de COVID-19 e a resposta a ele têm sido acompanhados por uma enorme infodemia: um excesso de informações, algumas precisas e outras não, que tornam difícil encontrar fontes idôneas e orientações confiáveis quando se precisa. A palavra infodemia se refere a um grande aumento no volume de informações associadas a um assunto específico, que podem se multiplicar exponencialmente em pouco tempo devido a um evento específico, como a pandemia atual. Nessa situação, surgem rumores e desinformação, além da manipulação de informações com intenção duvidosa. Na era da informação, esse fenômeno é amplificado pelas redes sociais e se alastra mais rapidamente, como um vírus

CNES como instrumento de gestão e sua importância no planejamento das ações em saúde / CNES as a management tool and its importance for planning health actions

Este artigo objetiva descrever as várias maneiras como o Cadastro Nacional de Estabelecimentos de Saúde (CNES) foi aplicado como instrumento de gestão, utilizando a base de dados BVS, SciELO e LILACS. O CNES surgiu em 2001 para suprir as deficiências no cadastro dos Sistemas de Informação Ambulatorial e Hospitalar. Além de atender o proposto, atualmente o CNES é um documento público e sistema de informação oficial de cadastro de todos os estabelecimentos de saúde no país. Mostra-se confiável e com relevância de dados podendo desenvolver estudos no tocante à capacidade instalada e mão-de-obra assistencial. Contudo, é necessária a conscientização dos gestores em mantê-lo atualizado, pois é através do banco de dados do CNES que os governantes são instrumentalizados com informações capazes de subsidiar decisões baseadas em evidências para o planejamento das ações em saúde. (AU)

This paper aims to describe the various ways of how the National Registry of Health Facilities (CNES) was applied as a management tool, using BVS, SciELO and LILACS database. The CNES was arose in 2001 to fill the deficits on the register of Hospital and Outpatient Information Systems. Additionally of this purpose, currently the CNES is a public document and the official registry information system of all health facilities in the country. It shows itself to be reliable and with data relevance, being able to develop studies related to the installed capacity and health labor workforce. However, it is necessary the manager's concern about keeping it updated, since it is through the CNES database that governors are supplied with information able to support evidence-based decisions for planning health actions. (AU)

Privacy-Preserving Integration of Medical Data : A Practical Multiparty Private Set Intersection.

Medical data are often maintained by different organizations. However, detailed analyses sometimes require these datasets to be integrated without violating patient or commercial privacy. Multiparty Private Set Intersection (MPSI), which is an important privacy-preserving protocol, computes an intersection of multiple private datasets. This approach ensures that only designated parties can identify the intersection. In this paper, we propose a practical MPSI that satisfies the following requirements: The size of the datasets maintained by the different parties is independent of the others, and the computational complexity of the dataset held by each party is independent of the number of parties. Our MPSI is based on the use of an outsourcing provider, who has no knowledge of the data inputs or outputs. This reduces the computational complexity. The performance of the proposed MPSI is evaluated by implementing a prototype on a virtual private network to enable parallel computation in multiple threads. Our protocol is confirmed to be more efficient than comparable existing approaches.

Integration of healthcare and financial information: Evaluation in a public hospital using a comprehensive approach.

Public healthcare organisations are moving towards the use of new technologies to automate and improve their internal processes in order to increase the effectiveness and efficiency of their use of resources. The aim of this research is to tackle the systematic evaluation of an experience of integrating information in a healthcare organisation, paying attention to the implications that this entails. The results show that the integration of the information in the hospital results in higher levels of quality. This study contributes a vision of interrelated work, in which tasks are shared and aims are jointly established.

Qualitative analysis of vendor discussions on the procurement of Computerised Physician Order Entry and Clinical Decision Support systems in hospitals.

OBJECTIVES: We studied vendor perspectives about potentially transferable lessons for implementing organisations and national strategies surrounding the procurement of Computerised Physician Order Entry (CPOE)/Clinical Decision Support (CDS) systems in English hospitals. SETTING: Data were collected from digitally audio-recorded discussions from a series of CPOE/CDS vendor round-table discussions held in September 2014 in the UK. PARTICIPANTS: Nine participants, representing 6 key vendors operating in the UK, attended. The discussions were transcribed verbatim and thematically analysed. RESULTS: Vendors reported a range of challenges surrounding the procurement and contracting processes of CPOE/CDS systems, including hospitals' inability to adequately assess their own needs and then select a suitable product, rushed procurement and implementation processes that resulted in difficulties in meaningfully engaging with vendors, as well as challenges relating to contracting leading to ambiguities in implementation roles. Consequently, relationships between system vendors and hospitals were often strained, the vendors attributing this to a lack of hospital management's appreciation of the complexities associated with implementation efforts. Future anticipated challenges included issues surrounding the standardisation of data to enable their aggregation across systems for effective secondary uses, and implementation of data exchange with providers outside the hospital. CONCLUSIONS: Our results indicate that there are significant issues surrounding capacity to procure and optimise CPOE/CDS systems among UK hospitals. There is an urgent need to encourage more synergistic and collaborative working between providers and vendors and for a more centralised support for National Health Service hospitals, which draws on a wider body of experience, including a formalised procurement framework with value-based product specifications.

[An overview of the definition and implementation of the Brazilian National Policy on Health Data and Information Technology]. / Panorama de definição e implementação da Política Nacional de Informação e Informática em Saúde.

The This qualitative study aimed to analyze the development and implementation of the Brazilian National Policy on Health Data and Information Technology (NPIIH). We analyzed documents and applied an online questionnaire to the experts involved in developing the policy. The data were submitted to content analysis using the categorical thematic modality. The PNIIS is the target of debate and proposals at various levels. Provisions have appeared in parallel to regulate measures on health data and information technology. Community participation in developing this policy and the convergence of laws, standards, resolutions, and policy-making levels in a common and broadly acknowledged and enforced policy are challenges, in addition to linking the public and private sectors. The study concludes that the National Policy on Health Data and Information Technology is making gradual progress, predominantly in theoretical debates, revisions, and updates. There are numerous challenges for its implementation and a prevailing need for legitimation.

Design and Implementation of a Set-Top Box-Based Homecare System Using Hybrid Cloud.

INTRODUCTION: Telemedicine has become a prevalent topic in recent years, and several telemedicine systems have been proposed; however, such systems are an unsuitable fit for the daily requirements of users. MATERIALS AND METHODS: The system proposed in this study was developed as a set-top box integrated with the Android™ (Google, Mountain View, CA) operating system to provide a convenient and user-friendly interface. The proposed system can assist with family healthcare management, telemedicine service delivery, and information exchange among hospitals. To manage the system, a novel type of hybrid cloud architecture was also developed. RESULTS: Updated information is stored on a public cloud, enabling medical staff members to rapidly access information when diagnosing patients. In the long term, the stored data can be reduced to improve the efficiency of the database. CONCLUSIONS: The proposed design offers a robust architecture for storing data in a homecare system and can thus resolve network overload and congestion resulting from accumulating data, which are inherent problems in centralized architectures, thereby improving system efficiency.

Panorama de definição e implementação da Política Nacional de Informação e Informática em Saúde / An overview of the definition and implementation of the Brazilian National Policy on Health Data and Information Technology / Definición general y aplicación de la Política Nacional de Información e Informática en Salud

O Estudo de abordagem qualitativa que teve como objetivo analisar o contexto atual de definição e implementação da Política Nacional de Informação e Informática em Saúde (PNIIS). Realizaram-se pesquisa documental e aplicação de um formulário online aos envolvidos com a definição da PNIIS no cenário nacional. Os dados coletados foram analisados por meio da Análise de Conteúdo, modalidade Temático Categorial. Verificou-se que a PNIIS em construção é alvo de debates e proposições em diversas instâncias. Normativas emergem em paralelo para regulamentar ações de informação e informática em saúde. A participação da população na construção desta política e a convergência das leis, normas, resoluções e instâncias para a formulação de uma política comum, reconhecida, legitimada e implementada são desafios, bem como articulação entre o público e o privado. Conclui-se que o panorama da PNIIS no cenário nacional avança lentamente, predominantemente em debates teóricos, revisões e atualizações. Há muitos desafios para sua implementação e prevalece a necessidade de legitimação.

The This qualitative study aimed to analyze the development and implementation of the Brazilian National Policy on Health Data and Information Technology (NPIIH). We analyzed documents and applied an online questionnaire to the experts involved in developing the policy. The data were submitted to content analysis using the categorical thematic modality. The PNIIS is the target of debate and proposals at various levels. Provisions have appeared in parallel to regulate measures on health data and information technology. Community participation in developing this policy and the convergence of laws, standards, resolutions, and policy-making levels in a common and broadly acknowledged and enforced policy are challenges, in addition to linking the public and private sectors. The study concludes that the National Policy on Health Data and Information Technology is making gradual progress, predominantly in theoretical debates, revisions, and updates. There are numerous challenges for its implementation and a prevailing need for legitimation.

Este estudio cualitativo tuvo como objetivo analizar el contexto actual de la definición e implementación de la Política Nacional de Información e Informática en Salud (PNIIS). Hemos llevado a cabo la investigación documental y la aplicación de un formulario en línea para los que participan en la definición de PNIIS en la escena nacional. Los datos obtenidos fueron analizados mediante análisis de contenido, modalidad temática categórica. La PNIIS en construcción es objeto de debates y propuestas en varios casos. Las normas emergen en paralelo para regular las acciones de información y de la informática de la salud. La participación popular en la construcción de esta política y la convergencia de las leyes, reglamentos, resoluciones y órganos para la formulación de una política común, reconocida así como la interacción entre lo público y lo privado. Se concluye que las perspectivas para PNIIS en la escena nacional avanza lentamente, sobre todo en los debates teóricos, revisiones y actualizaciones. Hay muchos retos para su implementación, pero sigue siendo una necesidad legítima.

Brain Tumor Database, a free relational database for collection and analysis of brain tumor patient information.

In this study, we describe the development and utilization of a relational database designed to manage the clinical and radiological data of patients with brain tumors. The Brain Tumor Database was implemented using MySQL v.5.0, while the graphical user interface was created using PHP and HTML, thus making it easily accessible through a web browser. This web-based approach allows for multiple institutions to potentially access the database. The BT Database can record brain tumor patient information (e.g. clinical features, anatomical attributes, and radiological characteristics) and be used for clinical and research purposes. Analytic tools to automatically generate statistics and different plots are provided. The BT Database is a free and powerful user-friendly tool with a wide range of possible clinical and research applications in neurology and neurosurgery. The BT Database graphical user interface source code and manual are freely available at http://tumorsdatabase.altervista.org.

A bio-inspired memory model embedded with a causality reasoning function for structural fault location.

Structural health monitoring (SHM) is challenged by massive data storage pressure and structural fault location. In response to these issues, a bio-inspired memory model that is embedded with a causality reasoning function is proposed for fault location. First, the SHM data for processing are divided into three temporal memory areas to control data volume reasonably. Second, the inherent potential of the causal relationships in structural state monitoring is mined. Causality and dependence indices are also proposed to establish the mechanism of quantitative description of the reason and result events. Third, a mechanism of causality reasoning is developed for the reason and result events to locate faults in a SHM system. Finally, a deformation experiment conducted on a steel spring plate demonstrates that the proposed model can be applied to real-time acquisition, compact data storage, and system fault location in a SHM system. Moreover, the model is compared with some typical methods based on an experimental benchmark dataset.

Design and development of a medical big data processing system based on Hadoop.

Secondary use of medical big data is increasingly popular in healthcare services and clinical research. Understanding the logic behind medical big data demonstrates tendencies in hospital information technology and shows great significance for hospital information systems that are designing and expanding services. Big data has four characteristics--Volume, Variety, Velocity and Value (the 4 Vs)--that make traditional systems incapable of processing these data using standalones. Apache Hadoop MapReduce is a promising software framework for developing applications that process vast amounts of data in parallel with large clusters of commodity hardware in a reliable, fault-tolerant manner. With the Hadoop framework and MapReduce application program interface (API), we can more easily develop our own MapReduce applications to run on a Hadoop framework that can scale up from a single node to thousands of machines. This paper investigates a practical case of a Hadoop-based medical big data processing system. We developed this system to intelligently process medical big data and uncover some features of hospital information system user behaviors. This paper studies user behaviors regarding various data produced by different hospital information systems for daily work. In this paper, we also built a five-node Hadoop cluster to execute distributed MapReduce algorithms. Our distributed algorithms show promise in facilitating efficient data processing with medical big data in healthcare services and clinical research compared with single nodes. Additionally, with medical big data analytics, we can design our hospital information systems to be much more intelligent and easier to use by making personalized recommendations.

Managing personal health information in distributed research network environments.

BACKGROUND: Studying rare outcomes, new interventions and diverse populations often requires collaborations across multiple health research partners. However, transferring healthcare research data from one institution to another can increase the risk of data privacy and security breaches. METHODS: A working group of multi-site research programmers evaluated the need for tools to support data security and data privacy. The group determined that data privacy support tools should: 1) allow for a range of allowable Protected Health Information (PHI); 2) clearly identify what type of data should be protected under the Health Insurance Portability and Accountability Act (HIPAA); and 3) help analysts identify which protected health information data elements are allowable in a given project and how they should be protected during data transfer. Based on these requirements we developed two performance support tools to support data programmers and site analysts in exchanging research data. RESULTS: The first tool, a workplan template, guides the lead programmer through effectively communicating the details of multi-site programming, including how to run the program, what output the program will create, and whether the output is expected to contain protected health information. The second performance support tool is a checklist that site analysts can use to ensure that multi-site program output conforms to expectations and does not contain protected health information beyond what is allowed under the multi-site research agreements. CONCLUSIONS: Together the two tools create a formal multi-site programming workflow designed to reduce the chance of accidental PHI disclosure.