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BACKGROUND: Population-based cancer registries (PBCRs) are the primary source of information for cancer surveillance and monitoring. Currently, there are 30 active PBCRs in Brazil. The objective of this study was to analyze the data quality of five gastrointestinal cancers (esophagus, stomach, colorectal, liver, and pancreas) according to the criteria of comparability, validity, completeness, and timeliness in Brazilian cancer registries. METHODS: This study included data from Brazilian PBCRs with more than ten years of historical data starting in the year 2000, regardless of the type of defined geographical coverage (state, metropolitan region, or capital), totaling 16 registries. Brazilian PBCRs were evaluated based on four international data quality criteria: comparability, validity (accuracy), completeness, and timeliness. All cancer cases were analyzed, except for nonmelanoma skin cancer cases (C44) and five gastrointestinal tumors (esophageal cancer, stomach cancer, colorectal cancer, liver cancer, and pancreatic cancer) per cancer registry and sex, according to the available period. RESULTS: The 16 Brazilian PBCRs represent 17% of the population (36 million inhabitants in 2021) according to data from 2000 to 2018. There was a variation in the incidence in the historical series ranging from 12 to 19 years. The proportion of morphologically verified (MV%) cases varied from 74.3% (Manaus) to 94.8% (Aracaju), and the proportion of incidentally reported death certificate only (DCO%) cases varied from 3.0% (São Paulo) to 23.9% (Espírito Santo). High-lethality malignant neoplasms, such as liver and pancreas, had DCO percentages greater than 30% in most cancer registries. The sixteen registries have more than a 48-month delay in data release compared to the 2022 calendar year. CONCLUSION: The studied Brazilian cancer registries met international comparability criteria; however, half of the registries showed indices below the expected levels for validity and completeness criteria for high-lethality tumors such as liver and pancreas tumors, in addition to a long delay in data availability and disclosure. Significant efforts are necessary to ensure the operational and stability of the PBCR in Brazil, which continues to be a tool for monitoring cancer incidence and assessing national cancer control policies.

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Background: Children (aged 0-14 years) living with HIV often experience lower rates of HIV diagnosis, treatment, and viral load suppression. In Haiti, only 63% of children living with HIV know their HIV status (compared to 85% overall), 63% are on treatment (compared to 85% overall), and 48% are virally suppressed (compared to 73% overall). Electronic medical records (EMRs) can improve HIV care and patient outcomes, but these benefits are largely dependent on providers having access to quality and nonmissing data. Objective: We sought to understand the associations between EMR data missingness and interruption in antiretroviral therapy treatment by age group (pediatric vs adult). Methods: We assessed associations between patient intake record data missingness and interruption in treatment (IIT) status at 6 and 12 months post antiretroviral therapy initiation using patient-level data drawn from iSanté, the most widely used EMR in Haiti. Missingness was assessed for tuberculosis diagnosis, World Health Organization HIV stage, and weight using a composite score indicator (ie, the number of indicators of interest missing). Risk ratios were estimated using marginal parameters from multilevel modified Poisson models with robust error variances and random intercepts for the facility to account for clustering. Results: Data were drawn from 50 facilities and comprised 31,457 patient records from people living with HIV, of which 1306 (4.2%) were pediatric cases. Pediatric patients were more likely than adult patients to experience IIT (n=431, 33% vs n=7477, 23.4% at 6 months; P<.001). Additionally, pediatric patient records had higher data missingness, with 581 (44.5%) pediatric records missing at least 1 indicator of interest, compared to 7812 (25.9%) adult records (P<.001). Among pediatric patients, each additional indicator missing was associated with a 1.34 times greater likelihood of experiencing IIT at 6 months (95% CI 1.08-1.66; P=.008) and 1.24 times greater likelihood of experiencing IIT at 12 months (95% CI 1.05-1.46; P=.01). These relationships were not statistically significant for adult patients. Compared to pediatric patients with 0 missing indicators, pediatric patients with 1, 2, or 3 missing indicators were 1.59 (95% CI 1.26-2.01; P<.001), 1.74 (95% CI 1.02-2.97; P=.04), and 2.25 (95% CI 1.43-3.56; P=.001) times more likely to experience IIT at 6 months, respectively. Among adult patients, compared to patients with 0 indicators missing, having all 3 indicators missing was associated with being 1.32 times more likely to experience IIT at 6 months (95% CI 1.03-1.70; P=.03), while there was no association with IIT status for other levels of missingness. Conclusions: These findings suggest that both EMR data quality and quality of care are lower for children living with HIV in Haiti. This underscores the need for further research into the mechanisms by which EMR data quality impacts the quality of care and patient outcomes among this population. Efforts to improve both EMR data quality and quality of care should consider prioritizing pediatric patients.

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Data quality monitoring plays a crucial role in multicenter prospective registries. By maintaining high data accuracy, completeness, and consistency, researchers can improve the overall quality and reliability of the registry data, enabling meaningful conclusions and supporting evidence-based decisions. The purpose of the present study was to evaluate data quality metrics (completeness, accuracy, and temporal plausibility) of a Multicenter Registry of Cardiac Implantable Electronic Devices (CIEDs) and to perform a direct data audit of a random sample of records to assess the agreement levels with the source documents. The CIED Registry was a prospective, multicenter, real-world observational study carried out from January 2020 to December 2022 in five designated centers across Sao Paulo, Brazil. We assessed the data quality of the CIED Registry by using two distinct approaches:•Dynamic data monitoring using features of the REDCap (Research Electronic Data Capture) software, including data reports and data quality rules•Direct data audit in which information from a random sample of 10 % of cases from the coordinating center was compared with original source documents Our findings suggest that the methodological approach applied to the CIED Registry resulted in high data completeness, accuracy, temporal plausibility, and excellent agreement levels with the source documents.

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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. 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.

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Among the main factors that negatively influence the decision-making process, it is possible to highlight the low quality, availability, and integration of population health data. This study aims to highlight the difficulty of research based on tuberculosis data available in Brazil. The FAIR methodology is a solution for standardizing data and sharing information about the disease. All the main actors involved, including those who generate data and administrators of information systems, should be encouraged to know their strengths and weaknesses. Continuously fostering strategies to promote data quality is, therefore, a strong stimulus for strengthening national health information systems and can potentially benefit from recommendations on how to overcome the inherent limitations of these information systems. Data quality management in Brazilian tuberculosis information systems is still not carried out organized and systematically. According to the FAIR principles, the evaluation demonstrates only 37.75% of compliance.

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Aim: Integrating sex and gender into health research is critical to contributing to an ethical and more responsible science to address significant knowledge gaps, resulting in higher-quality evidence for all. Subject and methods: Using the Essential Metrics for Assessing Sex and Gender Integration in Health Research Proposals Involving Human Participants, we evaluate the quality of the integration of sex and gender in the 350 scientific articles produced by 144 health studies funded by the Department of Science and Technology of the Brazilian Ministry of Health between 2004 and 2016. Results: The results show that clinical research articles are the type of studies that most frequently report on sex differences, while population and public health research articles most frequently report on gender differences. Analysis of the quality of sex and gender integration reveals low levels of qualification in the items of the literature review and research objectives (section 1) and participant recruitment and retention (section 2). However, the data collection tools, data analysis, and knowledge translation (section 3) items were rated as excellent and good. Conclusion: Funding agencies and public institutions should recognize the importance of the integration of sex and gender at all stages of the research process, for instance, through awareness and training for researchers and reviewers, clear requirements, and the possibility to use metrics in the evaluations process.

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BACKGROUND: During the COVID-19 pandemic, governments and researchers have used routine health data to estimate potential declines in the delivery and uptake of essential health services. This research relies on the data being high quality and, crucially, on the data quality not changing because of the pandemic. In this paper, we investigated those assumptions and assessed data quality before and during COVID-19. METHODS: We obtained routine health data from the DHIS2 platforms in Ethiopia, Haiti, Lao People's Democratic Republic, Nepal, and South Africa (KwaZulu-Natal province) for a range of 40 indicators on essential health services and institutional deaths. We extracted data over 24 months (January 2019-December 2020) including pre-pandemic data and the first 9 months of the pandemic. We assessed four dimensions of data quality: reporting completeness, presence of outliers, internal consistency, and external consistency. RESULTS: We found high reporting completeness across countries and services and few declines in reporting at the onset of the pandemic. Positive outliers represented fewer than 1% of facility-month observations across services. Assessment of internal consistency across vaccine indicators found similar reporting of vaccines in all countries. Comparing cesarean section rates in the HMIS to those from population-representative surveys, we found high external consistency in all countries analyzed. CONCLUSIONS: While efforts remain to improve the quality of these data, our results show that several indicators in the HMIS can be reliably used to monitor service provision over time in these five countries.

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Monitoring systems are ubiquitous in many environmental science fields due to the technological advances in the last decades, which contributed to the migration from conventional to automated observing networks. However, the cost of acquisition and operation of sensor networks is still a limiting factor for their wide use. Under this scenario, low-cost and affordable open-source sensors and systems emerge as an alternative to research-grade instruments. To fulfill the quality requirements defined by international organizations, sensor calibration has to be performed and shall be considered as a basic requirement. Best monitoring practices including established quality control procedures should be implemented for gathering environmental data. With a focus on data gathering, this paper reviews basic concepts on open source technologies, calibration methods, quality control procedures, applications and trends, and possibilities for improving the hardware of low-cost and affordable systems.

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Vector-borne diseases are among the most burdensome infectious diseases worldwide with high burden to health systems in developing regions in the tropics. For many of these diseases, vector control to reduce human biting rates or arthropod populations remains the primary strategy for prevention. New vector control interventions intended to be marketed through public health channels must be assessed by the World Health Organization for public health value using data generated from large-scale trials integrating epidemiological endpoints of human health impact. Such phase III trials typically follow large numbers of study subjects to meet necessary power requirements for detecting significant differences between treatment arms, thereby generating substantive and complex datasets. Data is often gathered directly in the field, in resource-poor settings, leading to challenges in efficient data reporting and/or quality assurance. With advancing technology, mobile data collection (MDC) systems have been implemented in many studies to overcome these challenges. Here we describe the development and implementation of a MDC system during a randomized-cluster, placebo-controlled clinical trial evaluating the protective efficacy of a spatial repellent intervention in reducing human infection with Aedes-borne viruses (ABV) in the urban setting of Iquitos, Peru, as well as the data management system that supported it. We discuss the benefits, remaining capacity gaps and the key lessons learned from using a MDC system in this context in detail.

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There is a general belief that the quality of Twitter data streams is generally low and unpredictable, making, in some way, unreliable to take decisions based on such data. The work presented here addresses this problem from a Data Quality (DQ) perspective, adapting the traditional methods used in relational databases, based on quality dimensions and metrics, to capture the characteristics of Twitter data streams in particular, and of Big Data in a more general sense. Therefore, as a first contribution, this paper re-defines the classic DQ dimensions and metrics for the scenario under study. Second, the paper introduces a software tool that allows capturing Twitter data streams in real time, computing their DQ and displaying the results through a wide variety of graphics. As a third contribution of this paper, using the aforementioned machinery, a thorough analysis of the DQ of Twitter streams is performed, based on four dimensions: Readability, Completeness, Usefulness, and Trustworthiness. These dimensions are studied for several different cases, namely unfiltered data streams, data streams filtered using a collection of keywords, and classifying tweets referring to different topics, studying the DQ for each topic. Further, although it is well known that the number of geolocalized tweets is very low, the paper studies the DQ of tweets with respect to the place from where they are posted. Last but not least, the tool allows changing the weights of each quality dimension considered in the computation of the overall data quality of a tweet. This allows defining weights that fit different analysis contexts and/or different user profiles. Interestingly, this study reveals that the quality of Twitter streams is higher than what would have been expected.

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Although the quality of citizen science (CS) data is often a concern, evidence for high-quality CS data increases in the scientific literature. This study aimed to assess the data reliability of a structured CS protocol for monitoring stingless bees' flight activity. We tested (1) data accuracy for replication among volunteers and for expert validation and (2) precision, comparing dispersion between citizen scientists and expert data. Two distinct activity dimensions were considered: (a) perception of flight activity and (b) flight activity counts (entrances, exits, and pollen load). No significant differences were found among groups regarding entrances and exits. However, replicator citizen scientists presented a higher chance of perceiving pollen than original data collectors and experts, likely a false positive. For those videos in which there was an agreement about pollen presence, the effective pollen counts were similar (with higher dispersion for citizen scientists), indicating the reliability of CS-collected data. The quality of the videos, a potential source of variance, did not influence the results. Increasing practical training could be an alternative to improve pollen data quality. Our study shows that CS provides reliable data for monitoring bee activity and highlights the relevance of a multi-dimensional approach for assessing CS data quality.

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Objetivo: Este artigo descreve um trabalho de pesquisa sobre a aplicação de um modelo adaptado de avaliação da Qualidade da Informação (QI) do Prontuário Eletrônico do Paciente (PEP) do Hospital de Clínicas de Itajubá com o objetivo de propor melhorias na qualidade dos dados. Método: Foi aplicado o modelo adaptado de avaliação da QI que contém passos e instruções para avaliação da informação, impacto no negócio e assim desenvolver os planos de melhorias para as informações do PEP. Resultados: Os resultados demonstram que as dimensões da QI Reputação, Acessibilidade e Valor agregado são as que impactam o processo de decisão clínica. Através da identificação destas dimensões foi realizada a investigação das causas raiz e desenvolvido os planos de melhorias da QI. Conclusão: O caminho metodológico permitiu desenvolver um projeto de Qualidade de Informação tendo como resultado as ações necessárias para melhoria contínua da informação.

Objective: This article describes a research project on the application of an adapted Data Quality Assessment model of the Electronic Health Records (EHR) of the Hospital de Clínicas de Itajubá in order to propose improvements in data quality. Method: The adapted IQ evaluation model was applied, which contains steps and instructions for assessing information, impact on business and thus developing improvement plans for EHR information. Results: The results demonstrate that the dimensions of data Quality Reputation, Accessibility and Added Value are what impact the making decision process. Through the identification of these dimensions, root causes were investigated and IQ improvement plans were developed. Conclusion: The methodological path allowed the development of an Information Quality project, resulting in the necessary actions for continuous information improvement.

Objetivo: Este articulo describe un proyecto de investigación sobre la aplicación de un modelo de Evaluación de la Calidad de la Información del Registro electrónico de pacientes (REP) del Hospital de Clínicas Itajubá para proponer mejoras en la calidad de los datos. Método: Se aplicó el modelo de evaluación Calidad de la Información adaptado, que contiene pasos e instrucciones para asesorar información, impacto en los negocios y, por lo tanto, desarrollar planes de mejora para la información REP. Resultados: Los resultados demuestran que las dimensiones de reputación, accesibilidad y valor agregado son las que impactan el proceso de decisión clínica. A través de la identificación de estas dimensiones, se investigaron las causas raíz y se desarrollaron planes de mejora del coeficiente intelectual. Conclusión: La ruta metodológica permitió el desarrollo de un proyecto de calidad de la información, lo que resultó en las acciones necesarias para la mejora contínua de la información.

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INTRODUCTION: Early diagnosis of paucibacillary tuberculosis represents a challenge, even with direct tissue examination. Digital pathology allows the digital analysis of tissues to identify microorganisms. We aim to develop a program to detect and quantify typical and atypical mycobacteria in paraffin-embedded Ziehl-Neelsen-stained tissues. MATERIAL AND METHODS: Program development: The building of the program, named Pat-Scan, included pathology, systems engineering, and scientific applications. The iScan Coreo Au scanner® was used, and 9 variables were adjusted. Ten Ziehl-Neelsen-stained samples were fragmented into 2000 images and analyzed to validate the reproducibility of the bacilli images in the tissue, as detected by the software. RESULTS: Pat-Scan included software and a scanner that were used to detect and quantify bacilli in paraffin-embedded Ziehl-Neelsen-stained tissues. All samples containing mycobacteria were successfully analyzed by the scanner, and the bacilli could be detected; these results were validated by expert pathologists by microscopy examination, and the presence of bacilli was confirmed in all cases. CONCLUSIONS: Pat-Scan allowed the identification and quantification of mycobacteria in paraffin-embedded Ziehl-Neelsen-stained tissues, offering a reproducible diagnostic method that reduces the time for diagnosis and does not affect precision. Further validation is needed for application in the clinical setting.

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Resumo Introdução O debate em torno do quesito de óbito no Censo Demográfico brasileiro foi retomado pela proximidade do Censo Demográfico de 2020. Há certa vantagem em obter informações de óbito por meio do Censo, mas é importante garantir a qualidade dessa informação. Objetivo Analisar a qualidade da declaração de idade para os dados de óbito do Censo Demográfico de 2010. Método Foram utilizadas as informações acerca dos óbitos nos domicílios, coletadas no questionário do universo do Censo Demográfico de 2010 do IBGE. A análise foi realizada a partir dos índices de Whipple e Myers. Resultados Para o Brasil como um todo, os resultados observados atestam uma boa qualidade dos dados de declaração de idade dos óbitos. No entanto, quando é estratificada a análise ao âmbito de unidades federativas, algumas distorções foram verificadas, sobretudo nas unidades pertencentes às regiões Norte e Centro-Oeste. Conclusão O uso dos dados de mortalidade para as análises em âmbito macro, do país como um todo, não requer ajustes para adequar as qualidades das informações, assim como para as análises em termos das grandes regiões.

Abstract Background The debate on deaths in the Brazilian population census has been resumed by the proximity of the next 2020 census. There are some advantages in obtaining death information through the census, but it is important to ensure the quality of this information. Objective To analyze the quality of the age declaration for the 2010 demographic census death data. Method Information on household deaths collected from the 2010 IBGE demographic census questionnaire was used. The analysis was performed from the Whipple and Myers indices. Results For Brazil as a whole, the observed results attest to a good quality of the death declaration data. However, when the analysis at the state level is stratified, some distortions were found, especially in the North and Midwest areas. Conclusion The use of mortality data for macro-level analyzes of the country as a whole does not require adjustments to suit the quality of the information, as well as for analysis in terms of large regions.

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A violência policial letal é um problema de saúde pública. Embora o Sistema de Informações sobre Mortalidade (SIM) seja o registro mais confiável sobre mortes por agressão, o mesmo não acontece nos casos de violência policial letal, que apresenta um alto grau de subnotificação quando comparado aos dados da Secretaria de Segurança Pública de São Paulo (SSP-SP). O presente estudo tem como objetivo estimar a subnotificação nas duas fontes oficiais de informação (SIM e SSP-SP), identificando as categorias da CID-10 utilizadas nos casos de violência policial letal incorretamente classificadas e calcular as taxas de mortalidade nos anos de 2014 e 2015 no Município de São Paulo, Brasil. Por meio da vinculação dos dados do SIM e da SSP-SP, descrevemos o uso das causas básicas de morte nos casos de violência policial letal, estimamos a subnotificação no SIM e na SSP-SP com a metodologia captura-recaptura e as taxas de mortalidade no município. A partir da vinculação das duas bases de dados, nota-se que a maior parte dos óbitos por violência policial letal foi classificada incorretamente (53%) em outras causas básicas de morte no SIM. Observa-se que tanto o SIM como a SSP-SP subnotificam as mortes cometidas por policiais em magnitudes distintas (53,2% no SIM e 7,9% na SSP-SP). A reclassificação dos óbitos a partir da vinculação adicionou ganho por parte do SIM, que passou a ter a mesma taxa média de mortalidade do que a SSP-SP (3,44/100 mil), diminuindo a subnotificação em comparação com o cenário inicial. O registro correto da morte é o primeiro passo para o direito à justiça e à verdade. Registrar com qualidade é garantir o direito à informação, sendo este não um fim, mas apenas o começo na tarefa da prevenção. O compartilhamento de dados e o trabalho intersetorial se faz urgente.

Deadly police force is a public health problem. Although the Mortality Information System (SIM) is the most reliable record of deaths from violence, the same is not true for cases of deadly police force, which displays a high degree of underreporting when compared to data from the São Paulo Department of Law Enforcement (SSP-SP). The current study aimed to estimate underreporting in the two official data sources (SIM and SSP-SP), identifying the ICD-10 categories used in cases of incorrectly classified deadly police force and mortality rates in the years 2014 and 2015 in the city of São Paulo, Brazil. Using linkage of data from the SIM and SSP-SP databases, we describe the use of underlying causes of death in cases of deadly police force, estimating underreporting in the SIM and the SSP-SP with the capture-recapture methodology and mortality rates in the city. Based on the database linkage, most of the deaths from deadly police force were classified incorrectly (53%) as other underlying causes of death in the SIM. Both the SIM and SSP-SP underreported the deaths committed by police officers, with different magnitudes (53.2% in the SIM and 7.9% in the SSP-SP). Reclassification of the deaths via linkage added a gain in the SIM, which now had the same mean mortality rate as the SSP-SP (3.44/100,000), thereby decreasing the underreporting in comparison to the initial scenario. Correct recording of death is the first step to the ensuring the right to justice and truth. Recording with quality means to guarantee the right to information, which is not an end per se, but the start in the task of prevention. Data-sharing and inter-sector work are urgently needed.

La violencia policial letal es un problema de salud pública. A pesar de que el Sistema de Información de la Mortalidad (SIM) sea el registro más fiable sobre muertes por agresión, este no se produce en los casos de violencia policial letal, que presenta un alto grado de subnotificación, cuando se compara con los datos de la Secretaria de Seguridad Pública de São Paulo (SSP-SP). Este estudio tiene como objetivo estimar la subnotificación en las dos fuentes oficiales de información (SIM y SSP-SP), identificando las categorías de la CID-10 utilizadas en los casos de violencia policial letal incorrectamente clasificados, así como calcular las tasas de mortalidad durante los años de 2014 y 2015 en el municipio de São Paulo, Brasil. Mediante la vinculación de los datos del SIM y de la SSP-SP, describimos el uso de las causas básicas de muerte en los casos de violencia policial letal, estimamos la subnotificación en el SIM y en la SSP-SP, con la metodología capture-recapture y las tasas de mortalidad en el municipio. A partir de la vinculación de las dos bases de datos, se nota que la mayor parte de los óbitos de violencia policial letal se clasificaron incorrectamente (53%) en otras causas básicas de muerte en el SIM. Se observa que tanto el SIM, como la SSP-SP, subnotifican las muertes cometidas por policías, en magnitudes distintas (53,2% en el SIM y 7,9% en la SSP-SP). La reclasificación de los óbitos a partir de la vinculación benefició al SIM, que pasó a tener la misma tasa media de mortalidad que la SSP-SP (3,44/100 mil), disminuyendo la subnotificación, en comparación con el escenario inicial. El registro correcto de la muerte es el primer paso para el derecho a la justicia y a la verdad. Registrar con calidad es garantizar el derecho a la información, siendo este no un fin, sino solo el comienzo de la tarea de prevención. El intercambio de datos y el trabajo intersectorial es algo urgente.

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Resumo Introdução Informação de qualidade é condição necessária para a análise objetiva da situação de saúde, para a tomada de decisões baseadas em evidências e para a programação de ações públicas que almejem o desenvolvimento de boas condições de saúde para a população em geral. Objetivo Avaliar a qualidade do preenchimento das notificações compulsórias de violência no Brasil, com ênfase na dimensão completude dos dados. Método Estudo descritivo com dados do Sistema de Informação de Agravos de Notificação (Sinan) no período de 2011 a 2014. Calcularam-se os percentuais de incompletude com base nos campos sem informação (ignorados/em branco) e a média anual da incompletude para variáveis essenciais e obrigatórias. Resultados O percentual médio global de incompletude das variáveis analisadas foi classificado como ruim (22,4%). O percentual médio de incompletude por blocos variou de regular para as variáveis de notificação individual (14,4%) e identificação da vítima (14,6%) a ruim para as variáveis sobre conclusão (30,8%) e encaminhamento (32,9%). Conclusão Os dados de notificação de violência apresentaram qualidade de preenchimento ruim, apesar do aumento no número de notificações no período analisado. Recomenda-se monitoramento dos dados e capacitação de profissionais no correto preenchimento das notificações.

Abstract Background Quality information is a necessary condition for the objective analysis of the health situation, for making evidence-based decisions and for the programming of public actions that aim at the development of good health conditions for the general population. Objective To evaluate the quality of the filling of compulsory notifications of violence in Brazil, with emphasis on the completeness of the data. Method Descriptive study with data from the National Disease Notification Information System (Sinan) for the period 2011 to 2014 was carried out. Percentages of incompleteness were calculated on the basis of uninformed fields (ignored/blank) and the annual average percentage of incompleteness for essential and mandatory variables. Results The overall average percentage of incompleteness of the analyzed variables was classified as Bad (22.4%). The average percentage of incompleteness by blocks ranged from regular for variables on reporting (14.4%) and victim identification (14.6%) to Bad for variables on ending (30.8%) and referral (32.9%). Conclusion The data of notification of violence presented Bad quality of completion, despite the increase in the number of notifications. It is recommended to monitor the data and to train professionals in the correct completion of notifications.

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BACKGROUND: Registered causes in vital statistics classified as garbage codes (GC) are considered indicators of quality of cause-of-death data. Our aim was to describe temporal changes in this quality in Brazil, and the leading GCs according to levels assembled for the Global Burden of Disease (GBD) study. We also assessed socioeconomic differences in the burden of different levels of GCs at a regional level. METHODS: We extracted data from the Brazilian Mortality Information System from 1996 to 2016. All three- and four-digit ICD-10 codes considered GC were selected and classified into four categories, according to the GBD study proposal. GC levels 1 and 2 are the most damaging unusable codes, or major GCs. Proportionate distribution of deaths by GC levels according selected variables were performed. Age-standardized mortality rates after correction of underreporting of deaths were calculated to investigate temporal relationships as was the linear association adjusted for completeness between GC rates in states and the Sociodemographic Index (SDI) from the GBD study, for 1996-2005 and 2006-2016. We classified Brazilian states into three classes of development by applying tertiles cutoffs in the SDI state-level estimates. RESULTS: Age-standardized mortality rates due to GCs in Brazil decreased from 1996 to 2016, particularly level 1 GCs. The most important GC groups were ill-defined causes (level 1) in 1996, and pneumonia unspecified (level 4) in 2016. At state level, there was a significant inverse association between SDI and the rate of level 1-2 GCs in 1996-2005, but both SDI and completeness had a non-expected significant direct association with levels 3-4. In 2006-2016, states with higher SDIs tended to have lower rates of all types of GCs. Mortality rates due to major GCs decreased in all three SDI classes in 1996-2016, but GC levels 3-4 decreased only in the high SDI category. States classified in the low or medium SDI groups were responsible for the most important decline of major GCs. CONCLUSION: Occurrence of major GCs are associated with socioeconomic determinants over time in Brazil. Their reduction with decreasing disparity in rates between socioeconomic groups indicates progress in reducing inequalities and strengthening cause-of-death statistics in the country.

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Was there quality in the Chinese epidemiological surveillance system during the COVID-19 pandemic? Using data of World Health Organization's situation reports (until situation report 55), an objective analysis was realized to answer this important question. Fulfillment of Benford's law (first digit law) is a rapid tool to suggest good data quality. Results suggest that China had an acceptable quality in its epidemiological surveillance system. Furthermore, more detailed and complete analyses could complement the evaluation of the Chinese surveillance system.

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Chromatin organization and epigenetic marks play a critical role in stem cell pluripotency and differentiation. Chromatin digestion by micrococcal nuclease (MNase) followed by high-throughput sequencing (MNase-seq) is the most widely used genome-wide method for studying nucleosome organization, that is, the first level of DNA packaging into chromatin. Combined with chromatin immunoprecipitation (ChIP), MNase-ChIP-seq represents a high-resolution method for investigating both chromatin organization and the distribution of epigenetic marks and histone variants. The plot2DO package presented here is a flexible tool for evaluating the quality of MNase-seq and MNase-ChIP-seq data, and for visualizing the distribution of nucleosomes near the functional regions of the genome. The plot2DO package is open-source software, and it is freely available from https://github.com/rchereji/plot2DO under the MIT license.

Assuntos

RESUMO

The validity of data provided by population-based cancer registries (PBCRs) is a key aspect in cancer surveillance. Tracing back cases initially reported by death certificate or death-certificate-notified (DCN) cases, improves data quality and has an especially significant impact on survival estimates. The present study performed in the Mendoza PBCR describes the trace-back procedure of cancer cases notified by death certificate for selected cancers (liver, lung, and stomach cancers) with the aim of reducing the percentage of cases diagnosed by death certificate only (DCO). The study was performed in 2018 using cancers diagnosed between 2006 and 2012 in the framework of a survival project (SURVCAN-3). Among the 822 cases that have been traced back, only 32.1% had an identified source of information. Of these, 70.3% had medical records available for review. Of the reviewed medical records, 86.9% of cancer diagnoses were confirmed. The DCN and DCO cases were much higher among older age groups. With the trace-back, the overall percentage of DCO was reduced from 23.8% to 19.9%. We conclude that DCN trace-back could improve data quality by reducing DCO diagnoses, which directly impacts survival estimates. Trace-back should be performed routinely and in a timely manner.