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Background: The Brazilian Policy for Comprehensive Care for People with Rare Diseases was implemented in 2014; however, national epidemiological data on rare diseases (RDs) are scarce and mainly focused on specific disorders. To address this gap, University Hospitals, Reference Services for Neonatal Screening, and Reference Services for Rare Diseases, all of which are public health institutions, established the Brazilian Rare Diseases Network (RARAS) in 2020. The objective of this study was to perform a comprehensive nationwide epidemiological investigation of individuals with RDs in Brazil. This retrospective survey collected data from patients receiving care in 34 healthcare facilities affiliated with RARAS in 2018 and 2019., Results: The survey included 12,530 participants with a median age of 15.0 years, with women representing 50.5% of the cohort. Classification according to skin color demonstrated that 5044 (47.4%) participants were admixed. Most had a confirmed diagnosis (63.2%), with a predominance of phenylketonuria (PKU), cystic fibrosis (CF), and acromegaly. Common clinical manifestations included global developmental delay and seizures. The average duration of the diagnostic odyssey was 5.4 years (± 7.9 years). Among the confirmed diagnoses, 52.2% were etiological (biochemical: 42.5%; molecular: 30.9%), while 47.8% were clinical. Prenatal diagnoses accounted for 1.2%. Familial recurrence and consanguinity rates were 21.6% and 6.4%, respectively. Mainstay treatments included drug therapy (55.0%) and rehabilitation (15.6%). The Public Health System funded most diagnoses (84.2%) and treatments (86.7%). Hospitalizations were reported in 44.5% of cases, and the mortality rate was 1.5%, primarily due to motor neuron disease and CF., Conclusion: This study marks a pioneering national-level data collection effort for rare diseases in Brazil, offering novel insights to advance the understanding, management, and resource allocation for RDs. It unveils an average diagnostic odyssey of 5.4 years and a higher prevalence of PKU and CF, possibly associated with the specialized services network, which included newborn screening services., (© 2024. The Author(s).)

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. At the same time, scientific research is constantly evolving to improve data quality through better reproducibility and empowerment of researchers and offers patient groups tools for secured data sharing and privacy compliance., Objective: Through an integrative literature review, the aim of this work was to identify and evaluate digital health technology interventions designed to support the conducting of health research based on data quality., Methods: A search was conducted in 6 electronic scientific databases in January 2022: PubMed, SCOPUS, Web of Science, Institute of Electrical and Electronics Engineers Digital Library, Cumulative Index of Nursing and Allied Health Literature, and Latin American and Caribbean Health Sciences Literature. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist and flowchart were used to visualize the search strategy results in the databases., Results: After analyzing and extracting the outcomes of interest, 33 papers were included in the review. The studies covered the period of 2017-2021 and were conducted in 22 countries. Key findings revealed variability and a lack of consensus in assessing data quality domains and metrics. Data quality factors included the research environment, application time, and development steps. Strategies for improving data quality involved using business intelligence models, statistical analyses, data mining techniques, and qualitative approaches., Conclusions: The main barriers to health data quality are technical, motivational, economical, political, legal, ethical, organizational, human resources, and methodological. The data quality process and techniques, from precollection to gathering, postcollection, and analysis, are critical for the final result of a study or the quality of processes and decision-making in a health care organization. The findings highlight the need for standardized practices and collaborative efforts to enhance data quality in health research. Finally, context guides decisions regarding data quality strategies and techniques., International Registered Report Identifier (irrid): RR2-10.1101/2022.05.31.22275804., (©Filipe Andrade Bernardi, Domingos Alves, Nathalia Crepaldi, Diego Bettiol Yamada, Vinícius Costa Lima, Rui Rijo. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 31.10.2023.)

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. Therefore, with a detailed audit, we centralized this information on the evolution of the disease, allowing for territorial and temporal monitoring. The daily publication of numbers about COVID-19 allowed anyone to follow the current scenario in several Brazilian cities. With about 1,7 million accesses, the Portal offers clarity and an easy understanding of the pandemic data in the country., (© 2021 The Author(s). Published by Elsevier B.V.)

Objective: to identify indicators that can be used in the management of Mental Health Services., Method: an integrative review in which we adopted the Population, Concept, and Context strategy to formulate the following Guiding Question: "Which indicators can be used for the management of mental health services?"., Results: a total of 22 articles were included and divided into two main groups: countries with initial high income (54%) as well as low- and middle-income countries (46%). We identified 5 studies that had experienced the use of indicators, 5 studies that had reported partial implementation, 9 studies that did not report use or implementation, 1 study on the indicator selection process, 1 as an implementation pilot, and a final study with a discussion for implementation. High-income countries also find it difficult to implement mental health indicators. The main difficulties in adopting the use of indicators are lack of basic mental health services, financial resources, legislation, political interest, and guidelines for its management., Conclusion: it is unusual to find a descriptive comparison of quality monitoring programs at the system level in the technical-scientific literature related to mental health indicators.

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. RARASnet proposes to map, analyze, and communicate all the data regarding the infrastructure of the centers and the patients' progress or needs. The focus of the proposed study is to provide all the technical infrastructure and analysis, following the World Health Organization and the Brazilian Ministry of Health guidelines., Methods: To build this digitized system, we will provide a security framework to assure the privacy and protection of each patient when collecting data. Systems development life cycle methodologies will also be applied to align software development, infrastructure operation, and quality assurance. After data collection of all information designed by the specialists, the computational analysis, modeling, and results will be communicated in scientific research papers and a digital health observatory., Results: The project has several activities, and it is in an initial stage. Initially, a survey was given to all health care centers to understand the technical aspects of each network member, such as the existence of computers, technical support staff, and digitized systems. In this survey, we detected that 59% (23/39) of participating health units have electronic medical records, while 41% (16/39) have paper records. Therefore, we will have different strategies to access the data from each center in the data collection phase. Later, we will standardize and analyze the clinical and epidemiological data and use these data to develop a national network for monitoring rare diseases and a digital health observatory to make the information available. The project had its financing approved in December 2019. Retrospective data collection started in October 2020, and we expect to finish in January 2021. During the third quarter of 2020, we enrolled 40 health institutions from all regions of Brazil., Conclusions: The nature of rare disease diagnosis is complex and diverse, and many problems will be faced in the evolution of the project. However, decisions based on data analysis are the best option for the improvement of the rare disease network in Brazil. The creation of RARASnet, along with all the digitized infrastructure, can improve the accessibility of information and standardization of rare diseases in the country., International Registered Report Identifier (irrid): DERR1-10.2196/24826., (©Domingos Alves, Diego Bettiol Yamada, Filipe Andrade Bernardi, Isabelle Carvalho, Márcio Eloi Colombo Filho, Mariane Barros Neiva, Vinícius Costa Lima, Têmis Maria Félix. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 22.01.2021.)