Publications by authors named "Filipe Andrade Bernardi"

Background: Rare diseases (RDs) have gained attention in public policy due to their complexity and low prevalence and the challenges they present in health care settings. Comprehensive care for people with RDs requires strengthening of services, programs, and care levels. It is imperative to make digital health tools available to support epidemiological surveillance, facilitate patient follow-up, and enhance the education and awareness of health care professionals (HCPs) regarding these conditions.

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Article Synopsis
  • - The Brazilian Rare Diseases Network (RARAS) was established in 2020 to conduct a nationwide epidemiological survey on rare diseases (RDs) in Brazil, addressing the lack of comprehensive national data since the Comprehensive Care Policy for RDs began in 2014.
  • - A total of 12,530 patients were surveyed, with a median age of 15 years; significant findings included that 63.2% had confirmed diagnoses, primarily of phenylketonuria, cystic fibrosis, and acromegaly, and average diagnostic delays lasting 5.4 years.
  • - The majority of diagnoses and treatments were funded by the Public Health System, with notable rates of hospitalization (44.5%) and a mortality rate
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Background: Decision-making and strategies to improve service delivery must be supported by reliable health data to generate consistent evidence on health status. The data quality management process must ensure the reliability of collected data. Consequently, various methodologies to improve the quality of services are applied in the health field.

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Background: The minimum data set (MDS) is a collection of data elements to be grouped using a standard approach to allow the use of data for clinical and research purposes. Health data are typically voluminous, complex, and sometimes too ambiguous to generate indicators that can provide knowledge and information on health. This complexity extends further to the rare disease (RD) domain.

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Clinical research outcomes depend on the correct definition of the research protocol, the data collection strategy, and the data management plan. Furthermore, researchers often need to work within challenging contexts, as is the case in tuberculosis services, where human and technological resources for research may be scarce. Electronic Data Capture Systems mitigate such risks and enable a reliable environment to conduct health research and promote result dissemination and data reusability.

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Purpose: The Orofacial Myofunctional Evaluation with Scores (OMES) protocol has been validated and used in clinical practice and research. The goals of this study were to develop, analyze and improve a version of OMES for the Web and to investigate the relationship between the usability judgments and the prior experience of the evaluators and whether using the interface promotes learning, as shown by the task completion time (TCT).

Methods: Study steps: 1) inspection of the prototype by the team; 2) evaluation of usability by three experienced speech-language pathologists (SLPs); and 3) evaluation of its usability by 12 SLPs with varying levels of experience in the use of OMES.

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The Brazilian Policy of Comprehensive Care for People with Rare Diseases (BPCCPRD) was established by the Ministry of Health to reduce morbidity and mortality and improve the quality of life of people with rare diseases (RD). Several laboratory tests, most using molecular genetic technologies, have been incorporated by the Brazilian Public Health System, and 18 specialised centres have so far been established at university hospitals (UH) in the capitals of the Southern, Southeastern and Northeastern regions. However, whether the available human and technological resources in these services are appropriate and sufficient to achieve the goals of care established by the BPCCPRD is unknown.

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Extracting information and discovering patterns from a massive dataset is a hard task. In an epidemic scenario, this data has to be integrated providing organization, agility, transparency and, above all, it has to be free of any type of censorship or bias. The aim of this paper is to analyze how coronavirus contamination has evolved in Brazil applying unsupervised analysis algorithms to extract information and find characteristics between them.

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Brazil is a large developing country that requires attention to regionalized behaviors regarding the dissemination of COVID-19. To deal with this complexity, the COVID-19 Brazil observatory was developed. The Portal aims to monitor and analyze data from different sources.

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Background: Tuberculosis (TB) is an infectious disease and is among the top 10 causes of death in the world, and Brazil is part of the top 30 high TB burden countries. Data collection is an essential practice in health studies, and the adoption of electronic data capture (EDC) systems can positively increase the experience of data acquisition and analysis. Also, data-sharing capabilities are crucial to the construction of efficient and effective evidence-based decision-making tools for managerial and operational actions in TB services.

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Background: A rare disease is a medical condition with low prevalence in the general population, but these can collectively affect up to 10% of the population. Thus, rare diseases have a significant impact on the health care system, and health professionals must be familiar with their diagnosis, management, and treatment.

Objective: This paper aims to provide health indicators regarding the rare diseases in Brazil and to create a network of reference centers with health professionals from different regions of the country.

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Introduction: Five months after the first confirmed case of COVID-19 in Brazil, the country has the second highest number of cases in the world. Without any scientifically proven drug or vaccine available combined with COVID-19's high transmissivity, slowing down the spread of the infection is a challenge. In an attempt to save the economy, the Brazilian government is slowly beginning to allow non-essential services to reopen for in-person customers.

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Background: Interoperability of health information systems is a challenge due to the heterogeneity of existing systems at both the technological and semantic levels of their data. The lack of existing data about interoperability disrupts intra-unit and inter-unit medical operations as well as creates challenges in conducting studies on existing data. The goal is to exchange data while providing the same meaning for data from different sources.

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