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.

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.

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.

Mapping, Infrastructure, and Data Analysis for the Brazilian Network of Rare Diseases: Protocol for the RARASnet Observational Cohort Study.

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.

Brazil: the emerging epicenter of COVID-19 pandemic.

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. METHODS: In this study, we analyze, based on data analysis and statistics, how other countries evolve and under which conditions they decided to resume normal activity. In addition, due to the heterogeneity of Brazil, we explore Brazilian data of COVID-19 from the State Health Secretaries to evaluate the situation of the pandemic within the states. RESULTS: Results show that while other countries have flattened their curves and present low numbers of active cases, Brazil continues to see an increase in COVID-19 patients. Furthermore, a number of important states are easing restrictions despite a high percentage of confirmed cases. CONCLUSIONS: All analyses show that Brazil is not ready for reopening, and the premature easing of restrictions may increase the number of COVID-19-related deaths and cause the collapse of the public health system.

Data Integration in the Brazilian Public Health System for Tuberculosis: Use of the Semantic Web to Establish Interoperability.

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. OBJECTIVE: To find ways to solve this challenge, this research paper proposes an interoperability solution for the tuberculosis treatment and follow-up scenario in Brazil using Semantic Web technology supported by an ontology. METHODS: The entities of the ontology were allocated under the definitions of Basic Formal Ontology. Brazilian tuberculosis applications were tagged with entities from the resulting ontology. RESULTS: An interoperability layer was developed to retrieve data with the same meaning and in a structured way enabling semantic and functional interoperability. CONCLUSIONS: Health professionals could use the data gathered from several data sources to enhance the effectiveness of their actions and decisions, as shown in a practical use case to integrate tuberculosis data in the State of São Paulo.

A Permissioned Blockchain Network for Security and Sharing of De-identified Tuberculosis Research Data in Brazil.

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. Data must be held secure and traceable, as well as available and understandable, for authorized parties. OBJECTIVES: In this sense, this work aims to propose a blockchain-based approach to build a reusable, decentralized, and de-identified dataset of TB research data, while increasing transparency, accountability, availability, and integrity of raw data collected in EDC systems. METHODS: After identifying challenges and gaps, a solution was proposed to tackle them, considering its relevance for TB studies. Data security issues are being addressed by a blockchain network and a lightweight and practical governance model. Research Electronic Data Capture (REDCap) and KoBoToolbox are used as EDC systems in TB research. Mechanisms to de-identify data and aggregate semantics to data are also available. RESULTS: A permissioned blockchain network was built using Kaleido platform. An integration engine integrates the EDC systems with the blockchain network, performing de-identification and aggregating meaning to data. A governance model addresses operational and legal issues for the proper use of data. Finally, a management system facilitates the handling of necessary metadata, and additional applications are available to explore the blockchain and export data. CONCLUSIONS: Research data are an important asset not only for the research where it was generated, but also to underpin studies replication and support further investigations. The proposed solution allows the delivery of de-identified databases built in real time by storing data in transactions of a permissioned network, including semantic annotations, as data are being collected in TB research. The governance model promotes the correct use of the solution.

Brazil: the emerging epicenter of COVID-19 pandemic

Abstract 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. METHODS: In this study, we analyze, based on data analysis and statistics, how other countries evolve and under which conditions they decided to resume normal activity. In addition, due to the heterogeneity of Brazil, we explore Brazilian data of COVID-19 from the State Health Secretaries to evaluate the situation of the pandemic within the states. RESULTS: Results show that while other countries have flattened their curves and present low numbers of active cases, Brazil continues to see an increase in COVID-19 patients. Furthermore, a number of important states are easing restrictions despite a high percentage of confirmed cases. CONCLUSIONS: All analyses show that Brazil is not ready for reopening, and the premature easing of restrictions may increase the number of COVID-19-related deaths and cause the collapse of the public health system.