Data Quality in Health Research: Integrative Literature Review.

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.

The Minimum Data Set for Rare Diseases: Systematic Review.

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. MDSs are essential for health surveillance as they help provide services and generate recommended population indicators. There is a bottleneck in international literature that reveals a global problem with data collection, recording, and structuring in RD. OBJECTIVE: This study aimed to identify and analyze the MDSs used for RD in health care networks worldwide and compare them with World Health Organization (WHO) guidelines. METHODS: The population, concept, and context methodology proposed by the Joanna Briggs Institute was used to define the research question of this systematic review. A total of 4 databases were reviewed, and all the processes were reported using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology. The data elements were analyzed, extracted, and organized into 10 categories according to WHO digital health guidelines. The quality assessment used the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist. RESULTS: We included 20 studies in our review, 70% (n=14) of which focused on a specific health domain and 30% (n=6) of which referred to RD in general. WHO recommends that health systems and networks use standard terminology to exchange data, information, knowledge, and intelligence in health. However, there was a lack of terminological standardization of the concepts in MDSs. Moreover, the selected studies did not follow the same standard structure for classifying the data from their MDSs. All studies presented MDSs with limitations or restrictions because they covered only a specific RD, or their scope of application was restricted to a specific context or geographic region. Data science methods and clinical experience were used to design, structure, and recommend a fundamental global MDS for RD patient records in health care networks. CONCLUSIONS: Our study highlights the difficulties in standardizing and categorizing findings from MDSs for RD because of the varying structures used in different studies. The fundamental RD MDS designed in this study comprehensively covers the data needs in the clinical and management sectors. These results can help public policy makers support other aspects of their policies. We highlight the potential of our results to help strategic decisions related to RD. TRIAL REGISTRATION: PROSPERO CRD42021221593; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=221593. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1016/j.procs.2021.12.034.

Tracking pregnant women displacements in Sao Paulo, Brazil: a complex systems approach to regionalization through the emergence of patterns.

BACKGROUND: The healthcare system can be understood as the dynamic result of the interaction of hospitals, patients, providers, and government configuring a complex network of reciprocal influences. In order to better understand such a complex system, the analysis must include characteristics that are feasible to be studied in order to redesign its functioning. The analysis of the emergent patterns of pregnant women flows crossing municipal borders for birth-related hospitalizations in a region of São Paulo, Brazil, allowed to examine the functionality of the regional division in the state using a complex systems approach and to propose answers to the dilemma of concentration vs. distribution of maternal care regional services in the context of the Brazilian Unified Health System (SUS). METHODS: Cross-sectional research of the areas of influence of hospitals using spatial interaction methods, recording the points of origin and destination of the patients and exploring the emergent patterns of displacement. RESULTS: The resulting functional region is broader than the limits established in the legal provisions, verifying that 85% of patients move to hospitals with high technology to perform normal deliveries and cesarean sections. The region has high independence rates and behaves as a "service exporter." Patients going to centrally located hospitals travel twice as long as patients who receive care in other municipalities even when the patients' conditions do not demand technologically sophisticated services. The effects of regulation and the agents' preferences reinforce the tendency to refer patients to centrally located hospitals. CONCLUSIONS: Displacement of patients during delivery may affect indicators of maternal and perinatal health. The emergent pattern of movements allowed examining the contradiction between wider deployments of services versus concentration of highly specialized resources in a few places. The study shows the potential of this type of analysis applied to other type of patients' flows, such as cancer or specialized surgery, as tools to guide the regionalization of the Brazilian Health System.

Progression of the first stage of spontaneous labour: A prospective cohort study in two sub-Saharan African countries.

BACKGROUND: Escalation in the global rates of labour interventions, particularly cesarean section and oxytocin augmentation, has renewed interest in a better understanding of natural labour progression. Methodological advancements in statistical and computational techniques addressing the limitations of pioneer studies have led to novel findings and triggered a re-evaluation of current labour practices. As part of the World Health Organization's Better Outcomes in Labour Difficulty (BOLD) project, which aimed to develop a new labour monitoring-to-action tool, we examined the patterns of labour progression as depicted by cervical dilatation over time in a cohort of women in Nigeria and Uganda who gave birth vaginally following a spontaneous labour onset. METHODS AND FINDINGS: This was a prospective, multicentre, cohort study of 5,606 women with singleton, vertex, term gestation who presented at ≤ 6 cm of cervical dilatation following a spontaneous labour onset that resulted in a vaginal birth with no adverse birth outcomes in 13 hospitals across Nigeria and Uganda. We independently applied survival analysis and multistate Markov models to estimate the duration of labour centimetre by centimetre until 10 cm and the cumulative duration of labour from the cervical dilatation at admission through 10 cm. Multistate Markov and nonlinear mixed models were separately used to construct average labour curves. All analyses were conducted according to three parity groups: parity = 0 (n = 2,166), parity = 1 (n = 1,488), and parity = 2+ (n = 1,952). We performed sensitivity analyses to assess the impact of oxytocin augmentation on labour progression by re-examining the progression patterns after excluding women with augmented labours. Labour was augmented with oxytocin in 40% of nulliparous and 28% of multiparous women. The median time to advance by 1 cm exceeded 1 hour until 5 cm was reached in both nulliparous and multiparous women. Based on a 95th percentile threshold, nulliparous women may take up to 7 hours to progress from 4 to 5 cm and over 3 hours to progress from 5 to 6 cm. Median cumulative duration of labour indicates that nulliparous women admitted at 4 cm, 5 cm, and 6 cm reached 10 cm within an expected time frame if the dilatation rate was ≥ 1 cm/hour, but their corresponding 95th percentiles show that labour could last up to 14, 11, and 9 hours, respectively. Substantial differences exist between actual plots of labour progression of individual women and the 'average labour curves' derived from study population-level data. Exclusion of women with augmented labours from the study population resulted in slightly faster labour progression patterns. CONCLUSIONS: Cervical dilatation during labour in the slowest-yet-normal women can progress more slowly than the widely accepted benchmark of 1 cm/hour, irrespective of parity. Interventions to expedite labour to conform to a cervical dilatation threshold of 1 cm/hour may be inappropriate, especially when applied before 5 cm in nulliparous and multiparous women. Averaged labour curves may not truly reflect the variability associated with labour progression, and their use for decision-making in labour management should be de-emphasized.

Towards a Clinical Trial Protocol to Evaluate Health Information Systems: Evaluation of a Computerized System for Monitoring Tuberculosis from a Patient Perspective in Brazil.

Assessment of health information systems consider different aspects of the system itself. They focus or on the professional who will use the software or on its usability or on the software engineering metrics or on financial and managerial issues. The existent approaches are very resources consuming, disconnected, and not standardized. As the software becomes more critical in the health organizations and in patients, becoming used as a medical device or a medicine, there is an urgency to identify tools and methods that can be applied in the development process. The present work is one of the steps of a broader study to identify standardized protocols to evaluate the health information systems as medicines and medical devices are evaluated by clinical trials. The goal of the present work was to evaluate the effect of the introduction of an information system for monitoring tuberculosis treatment (SISTB) in a Brazilian municipality from the patients' perspective. The Patient Satisfaction Questionnaire and the Hospital Consumer Assessment of Healthcare Providers and Systems were answered by the patients before and after the SISTB introduction, for comparison. Patients from an outpatient clinic, formed the control group, that is, at this site was not implanted the SISTB. Descriptive statistics and mixed effects model were used for data analysis. Eighty-eight interviews were conducted in the study. The questionnaire's results presented better averages after the system introduction but were not considered statistically significant. Therefore, it was not possible to associate system implantation with improved patient satisfaction. The HIS evaluation need be complete, the technical and managerial evaluation, the safety, the impact on the professionals and direct and/or indirect impact on patients are important. Developing the right tools and methods that can evaluate the software in its entirety, from the beginning of the development cycle with a normalized scale, are needed.

PRENACEL - a mHealth messaging system to complement antenatal care: a cluster randomized trial.

BACKGROUND: The aim of this study was to determine whether PRENACEL (a bi-directional, mobile-phone based, short text message service (SMS)) increases the coverage of recommended antenatal care (ANC) practices. METHODS: A parallel, cluster-randomized trial in which 20 public primary Health Care Units (PHCUs) were randomly allocated to the intervention (10 PHCUs) or control (10 PHCUs) group. The study population included pregnant women aged 18 or above with a gestational age of 20 weeks or less. Pregnant women receiving ANC in intervention PHCUs were invited through leaflets and posters to register in PRENACEL. Women who registered in PRENACEL received a weekly set of short text messages with health education and health promotion content related to pregnancy and childbirth and were also able to clarify ANC queries through SMS. All women received routine ANC. The primary outcome was the proportion of women with high ANC Score, a composite measure of coverage of recommended ANC practices. Chi-square or Fisher's exact tests and multivariate log-binomial regression were used to analyze the outcomes. RESULTS: A total of 1210 eligible women received ANC in the participating PHCUs and took part of this study (770 in the intervention group and 440 in the control group). 20.4% (157/770) of intervention-group women registered in PRENACEL, but only 116 read all messages (73.9% of women who registered in PRENACEL, 116/157). The adjusted intention-to-treat analysis suggested no difference between intervention and control groups in the primary outcome (Adjusted Relative Risk (AdjRR): 1.05 (95% Confidence Interval (CI): 1.00-1.09). Both crude and adjusted per-protocol analysis suggested a positive effect of PRENACEL (Crude RR (95% CI): 1.14 (1.06-1.22), AdjRR (95% CI): 1.12 (1.05-1.21). The multivariate analysis also suggests that the PRENACEL group (women who read all SMS) had higher mean ANC score [48.5 (±4.2) vs 45.2 (±8.7), p < 0.01], higher proportion of women with ≥6 ANC visits (96.9% vs. 84.8%, p = 0.01), and higher rates of syphilis testing (40.5% vs. 24.8%, p = 0.03) and HIV testing (46.6% vs. 25.7%, p < 0.01) during ANC. CONCLUSIONS: A bi-directional, mobile-phone based, short text message service is potentially useful to improve the coverage of recommended ANC practices, including syphilis and HIV testing. TRIAL REGISTRATION: Clinical trial registry: RBR-54zf73 , U1111-1163-7761.

Resumo: Introdução: O objetivo deste estudo foi determinar se o PRENACEL, um serviço bidirecional de mensagens curtas de texto (SMS) com base na telefonia celular, aumenta a cobertura das práticas recomendadas de cuidados pré-natais (PN). Métodos: um ensaio paralelo, aleatorizado por conglomerados, no qual 20 unidades básicas de saúde (UBS) foram alocadas aleatoriamente para o grupo de intervenção (10 UBS) ou controle (10 UBS). A população estudada incluiu gestantes com idade igual ou superior a 18 anos com idade gestacional de 20 semanas ou menos. As gestantes que receberam PN em UBS intervenção foram convidadas através de folhetos e cartazes para se inscreverem no PRENACEL. As mulheres que se registraram no PRENACEL receberam um conjunto semanal de SMS com conteúdo de educação e promoção da saúde relacionadas à gravidez e parto e também puderam esclarecer dúvidas relacionadas ao PN através de SMS. Todas as mulheres receberam PN de rotina. O desfecho primário foi a proporção de mulheres com um alto escore de PN, uma medida da cobertura das principais práticas recomendadas no PN. Resultados: um total de 1.210 mulheres participaram deste estudo (770 no grupo de intervenção e 440 no grupo de controle). 20,4% (157/770) das mulheres do grupo de intervenção demonstraram interesse e foram registradas no PRENACEL, mas apenas 116 leram as mensagens (73,9%, 116/157). A análise ajustada de intenção de tratamento sugeriu ausência de efeito da intervenção no desfecho primário (Risco Relativo (RR) ajustado: 1,05, Intervalo de Confiança (IC) de 95%: 1,00-1,09). A análise por protocolo sugeriu um efeito positivo do PRENACEL [RR bruto (IC 95%): 1,14 (1,06-1,22), RR ajustado (IC 95%): 1,12 (1,05-1,21)]. A análise multivariada sugeriu que as mulheres que leram os SMS apresentaram a maior média do escore de PN [48,5 (±4,2) vs 45,2 (±8,7), p < 0,01], maior proporção de mulheres com ≥6 consultas (96,9% vs. 84,8%, p = 0,01) e maiores taxas de teste de sífilis (40,5% vs. 24,8%, p = 0,03) e HIV (46,6% vs. 25,7%, p < 0,01) durante o PN. Conclusões: o sistema PRENACEL é potencialmente útil para melhorar a cobertura das práticas recomendadas de PN, incluindo testes de sífilis e HIV.

The development of a Simplified, Effective, Labour Monitoring-to-Action (SELMA) tool for Better Outcomes in Labour Difficulty (BOLD): study protocol.

BACKGROUND: The partograph is currently the main tool available to support decision-making of health professionals during labour. However, the rate of appropriate use of the partograph is disappointingly low. Apart from limitations that are associated with partograph use, evidence of positive impact on labour-related health outcomes is lacking. The main goal of this study is to develop a Simplified, Effective, Labour Monitoring-to-Action (SELMA) tool. The primary objectives are: to identify the essential elements of intrapartum monitoring that trigger the decision to use interventions aimed at preventing poor labour outcomes; to develop a simplified, monitoring-to-action algorithm for labour management; and to compare the diagnostic performance of SELMA and partograph algorithms as tools to identify women who are likely to develop poor labour-related outcomes. METHODS/DESIGN: A prospective cohort study will be conducted in eight health facilities in Nigeria and Uganda (four facilities from each country). All women admitted for vaginal birth will comprise the study population (estimated sample size: 7,812 women). Data will be collected on maternal characteristics on admission, labour events and pregnancy outcomes by trained research assistants at the participating health facilities. Prediction models will be developed to identify women at risk of intrapartum-related perinatal death or morbidity (primary outcomes) throughout the course of labour. These predictions models will be used to assemble a decision-support tool that will be able to suggest the best course of action to avert adverse outcomes during the course of labour. To develop this set of prediction models, we will use up-to-date techniques of prognostic research, including identification of important predictors, assigning of relative weights to each predictor, estimation of the predictive performance of the model through calibration and discrimination, and determination of its potential for application using internal validation techniques. DISCUSSION: This research offers an opportunity to revisit the theoretical basis of the partograph. It is envisioned that the final product would help providers overcome the challenging tasks of promptly interpreting complex labour information and deriving appropriate clinical actions, and thus increase efficiency of the care process, enhance providers' competence and ultimately improve labour outcomes. Please see related articles ' http://dx.doi.org/10.1186/s12978-015-0027-6 ' and ' http://dx.doi.org/10.1186/s12978-015-0028-5 '.

Development of a Mobile Application with Health Guidelines for TB Patients Care.

Health guidelines inform recommendations for different clinical practices or public health policies. They are a simple way to organize and retrieve relevant information that can impact patient care. Although these documents are easy to use, most are not user-friendly because they are difficult to access. Our work aims to present the developing approach for a decision-making tool based on health guidelines to assist health professionals in caring for patients with tuberculosis. This tool is being developed for use on mobile devices and as a web-based system, which will transform a passive and declarative health guideline document into an interactive tool that will provide data, information, and knowledge. User tests with functional prototypes developed for the Android platform show that this application has the potential to be applied in TB healthcare facilities in the future.

From Raw Data to FAIR Data: The FAIRification Workflow for Brazilian Tuberculosis Research.

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.

A Computational Infrastructure for Analyzing Tuberculosis Research Data in Brazil.

Tuberculosis (TB) is one of the infectious diseases that currently causes the most deaths, with 6.4 million new cases recorded in 2021. Although it is a curable disease, drug-resistant strains emerge due to a lack of hygiene and low-quality or inappropriate medications, among other factors. With this in mind, the World Health Organization initiated the End TB Strategy campaign to improve the health system in the fight against tuberculosis. For this, reliable and high-quality health data is necessary to create effective public policies. However, despite technological advancements such as emerging concepts like Big Data and the Internet of Things, generating health information faces several obstacles. Therefore, the present work aims to describe a pipeline for TB research in Brazil to contribute to obtaining high-quality data.

Local protection bubbles: an interpretation of the slowdown in the spread of coronavirus in the city of São Paulo, Brazil, in July 2020.

After four months of fighting the pandemic, the city of São Paulo, Brazil, entered a phase of relaxed social distancing measures in July 2020. Simultaneously, there was a decline in the social distancing rate and a reduction in the number of cases, fatalities, and hospital bed occupancy. To understand the pandemic dynamics in the city of São Paulo, we developed a multi-agent simulation model. Surprisingly, the counter-intuitive results of the model followed the city's reality. We argue that this phenomenon could be attributed to local bubbles of protection that emerged in the absence of contagion networks. These bubbles reduced the transmission rate of the virus, causing short and temporary reductions in the epidemic curve - but manifested as an unstable equilibrium. Our hypothesis aligns with the virus spread dynamics observed thus far, without the need for ad hoc assumptions regarding the natural thresholds of collective immunity or the heterogeneity of the population's transmission rate, which may lead to erroneous predictions. Our model was designed to be user-friendly and does not require any scientific or programming expertise to generate outcomes on virus transmission in a given location. Furthermore, as an input to start our simulation model, we developed the COVID-19 Protection Index as an alternative to the Human Development Index, which measures a given territory vulnerability to the coronavirus and includes characteristics of the health system and socioeconomic development, as well as the infrastructure of the city of São Paulo.

Availability of Genetic Tests in Public Health Services in Brazil: Data from the Brazilian Rare Diseases Network.

INTRODUCTION: The Brazilian Policy for Comprehensive Care for People with Rare Diseases (BPCCPRD) was published in 2014, accrediting several reference centers and incorporating many genetic tests for the diagnosis of rare diseases (RDs). The Brazilian Network of Rare Diseases (RARAS) comprises more than 40 institutions that offer diagnosis and treatment for RDs in Brazil. This network includes Reference Services for Rare Diseases (RDRS), Reference Services for Newborn Screening (NSRS), and University Hospitals distributed in all Brazilian regions. OBJECTIVE: The aim of the study was to map the availability and distribution of the BPCCPRD diagnostic procedures in the Brazilian Unified Health System through RARAS. METHOD: Data were collected through a questionnaire on the Research Electronic Data Capture platform, with 22 questions regarding the availability of procedures. Thirty-seven coordinators from RARAS participating centers received the questionnaire link for participation by email from August/2020 to March/2021. All participating institutions ethically approved this project. RESULTS: Of the 37 institutions, 23 (62.16%) offered cytogenetic tests, 20 (54.05%) offered molecular procedures, and 22 (59.46%) offered inborn errors of metabolism diagnostic tests. The Southern blot analysis, enzyme assays on cultured tissue and urinary organic acid tests had the highest outsourcing rate. On the other hand, the procedures most frequently performed on-site were bone marrow karyotype and long-term cultured karyotype. It was observed that 10 of the 37 centers (27%) did not provide access to investigated procedures (on-site or outsourced). The North and Midwest regions stood out in terms of the unavailability of such techniques in at least 40% of the evaluated institutions. DISCUSSION AND CONCLUSION: This study reveals large discrepancies in the supply of diagnostic procedures in the Brazilian territory. Moreover, there is a broad collaboration between services through the outsourcing of multiple diagnostic techniques to address this issue. Finally, this work corroborates the importance of mapping services for the diagnosis and treatment of individuals with RDs to propose actions for the better supply and distribution of these procedures.

Unsupervised analysis of COVID-19 pandemic evolution in brazilian states: Vaccination Scenario.

Brazil is one of the countries with the worst response against the pandemic scenario of coronavírus. At the beginning we were on average with 4000 deaths in a 24 hours period. In the course of this situation, large amounts of health and medicine datasets were being generated in real time, requiring effective ways to extract information and discover patterns that can help in the fight against this disease. And even more important is to monitor the progress of prophylactic measures and whether they are being effective in reducing the spread of the virus. Thus, the aim of this study is to analyze how the coronavirus has different ways to evolve in each Brazilian state with the influences of the vaccination process. To achieve this goal, the time series Clustering Technique based on a K-Means variation was applied, with the similarity metric Dynamic Time Warping (DTW). We produced this study using the data reported by the Ministry of Health in Brazil, referring to deaths per 100k inhabitants and all vaccination data available. Our results indicate an unevenly occurring vaccination and the need to identify other associated patterns with human development indices and other socio-economic indicators, being this the first analysis developed in the country, under the goals above.

REDbox: a comprehensive semantic framework for data collection and management in tuberculosis research.

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. The proposed solution is based on needs pinpointed by researchers, considering the need for an accommodating solution to conduct research in low-resource environments. The REDbox framework was developed to facilitate data collection, management, sharing, and availability in tuberculosis research and improve the user experience through user-friendly, web-based tools. REDbox combines elements of the REDCap and KoBoToolbox electronic data capture systems and semantics to deliver new valuable tools that meet the needs of tuberculosis researchers in Brazil. The framework was implemented in five cross-institutional, nationwide projects to evaluate the users' perceptions of the system's usefulness and the information and user experience. Seventeen responses (representing 40% of active users) to an anonymous survey distributed to active users indicated that REDbox was perceived to be helpful for the particular audience of researchers and health professionals. The relevance of this article lies in the innovative approach to supporting tuberculosis research by combining existing technologies and tailoring supporting features.

Myositis Ossificans of the Breast Mimicking Breast Cancer: A Case Report.

Myositis ossificans (MO) is an uncommon tumor characterized by a rapidly growing mass following a history of local trauma. Few cases of MO affecting the breast have been reported, and some were misdiagnosed as primary osteosarcoma of the breast or metaplastic breast carcinoma. The following case report presents a patient with a growing breast lump whose core biopsy result was suspicious for breast cancer. MO was diagnosed after analysis of the mastectomy specimen. This case highlights the importance of MO as a differential diagnosis of a growing soft-tissue mass after trauma to avoid unnecessary overtreatment. Keywords: Myositis Ossificans, Osteosarcoma, Breast Cancer, Mastectomy, Heterotopic Ossification © RSNA, 2023.

Mental Health Indicators for the Brazilian Psychosocial Care Network: A proposal. / Indicadores de saúde mental para a Rede de Atenção Psicossocial brasileira: uma proposta.

OBJECTIVE: to propose Mental Health Indicators aimed at management of the Mental Health Care Network, starting with convergence of their use, in countries with public health organization. METHOD: an exploratory analysis of the indicators adopted and used in these countries, from the detailed analysis of their respective normative documents, considering the World Health Organization guidelines. After selection of the indicators, the Mental Health Matrix was adopted as a suggestion for their development and application in the Brazilian Psychosocial Care Network. The matrix was prepared in two dimensions, respecting the inclusion and exclusion criteria for the indicators studied, as follows: geographical (national/regional, local, individual), and time (entry, process and results). RESULTS: the analysis indicates 41 indicators that presented diverse evidence regarding their use. All were allocated in the Mental Health Matrix, contributing as a metric to analyze the purpose of the Mental Health services, in the levels and phases of each dimension. CONCLUSION: the indicators selected, distributed in the different Mental Health Matrix dimensions, are being made available for their use in management and in the clinical practice, as well as for scientific studies and, in the future, to be used as definers of Mental Health policies.

Unsupervised analysis of COVID-19 pandemic evolution in brazilian states.

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. To achieve this goal we describe an implementation that uses data about Covid-19 spread in Brazilian states (26 states and the federal district), applying a Time Series Clustering technique based on a K-Means variation, using Dynamic Time Warping as a similarity metric. We used data reported by the Ministry of Health in Brazil, referring to deaths per 100k inhabitants, during 452 days from the first reported death in each state. Two analyzes were performed, one considering 3 clusters and the other with 6 clusters. Through these analysis, 3 patterns of responses to the pandemic can be observed, ranging from one of greater to lesser control of the pandemic, although in recent months all clusters showed a highly increase in the number of deaths. The identification of these patterns is important to highlight possible actions and events, as well as other characteristics that determine the correct or incorrect public decision-making in combating the Covid-19 pandemic.

Epidemiology of rare diseases in Brazil: protocol of the Brazilian Rare Diseases Network (RARAS-BRDN).

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. Despite great advances in diagnosis, especially due to new technologies and the recent structuring of clinical assessment of RD in Brazil, epidemiological data are lacking and when available, restricted to specific disorders. This position paper summarises the performance of a nationally representative survey on epidemiology, clinical status, and diagnostic and therapeutic resources employed for individuals with genetic and non-genetic RD in Brazil. The Brazilian Rare Disease Network (BRDN) is under development, comprising 40 institutions, including 18 UH, 17 Rare Diseases Reference Services and five Newborn Screening Reference Services. A retrospective study will be initially conducted, followed by a prospective study. The data collection instrument will use a standard protocol with sociodemographic data and clinical and diagnostic aspects according to international ontology. This great collaborative network is the first initiative of a large epidemiological data collection of RD in Latin America, and the results will increase the knowledge of RD in Brazil and help health managers to improve national public policy on RD in Brazil.

COVID-19 BR: A web portal for COVID-19 information in Brazil.

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.

Development and content validation of a mobile application for monitoring latent tuberculosis treatment.

BACKGROUND: Non-compliance with latent tuberculosis infection (LTBI) treatment is a reality. The objective of this study was to develop and validate an mobile device application for monitoring the treatment of LTBI. METHODS: We defined the requirements, elaborated on the application's conceptual map, generated implementation and prototyping alternatives, and validated content. RESULTS: Feedback on the validity of content were: "usefulness, consistency, clarity, objectivity, vocabulary, and precision" from professionals, and "clarity" from patients. CONCLUSIONS: The application proved to be easy to understand, according to the assessment of both professionals and people undergoing treatment for LTBI.