Filipe Andrade Bernardi
@lis.fmrp.usp.br
University of São Paulo
He holds a degree in Biomedical Informatics from the University of São Paulo (2016), a master's degree in Bioengineering from the University of São Paulo (2019) and a PhD in Bioengineering from the University of São Paulo (2024). He is a researcher affiliated with the Health Intelligence Laboratory, registered and certified in the CNPq group directory (. He has experience and interest in the areas of digital health, data governance and quality, development and validation of computational models and artificial intelligence. His research work includes experience in the areas of Tuberculosis, with participation in several projects linked to the Brazilian Tuberculosis Research Network (REDE-TB). Since 2020, he has also worked in the area of rare diseases, with emphasis on his work at the National Network of Rare Diseases (RARAS), where he is currently the manager of the IT team and a member of the steering committee at the National Institute of
RESEARCH, TEACHING, or OTHER INTERESTS
Health Informatics, Management of Technology and Innovation, Public Health, Environmental and Occupational Health, Reviews and References (medical)
Scopus Publications
Scopus Publications
Ana Clara de Andrade Mioto, Pedro Emilio Andrade Martins, Gabriel Modina, Domingos Alves, Vinicius Costa Lima, Mariane Neiva, and Filipe Andrade Bernardi
Elsevier BV
Mariana Mozini, Raul Rothschild, Ana Clara Mioto, Filipe Bernardi, Vinícius Lima, Giovane Soares, Renan Segamarchi, and Domingos Alves
Elsevier BV
Vinícius Costa Lima, Nathalia Yukie Crepaldi, Filipe Andrade Bernardi, Renan Barbieri Segamarchi, and Domingos Alves
Springer Nature Switzerland
Vinícius Costa Lima, Rui Pedro Charters Lopes Rijo, Filipe Andrade Bernardi, Márcio Eloi Colombo Filho, Francisco Barbosa-Junior, Felipe Carvalho Pellison, Rafael Mello Galliez, Afrânio Lineu Kritski, and Domingos Alves
Springer Science and Business Media LLC
AbstractClinical 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.
Filipe Bernardi, Vinicius Lima, Gabriel Sartoretto, João Baiochi, Victor Cassão, Afrânio Kritski, Rui Rijo, and Domingos Alves
IOS Press
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.
Manoela Reis, Filipe Bernardi, Vinicius Lima, and Domingos Alves
IOS Press
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.
Mariana Mozini, Filipe Bernardi, Ana Clara Mioto, Victor Cassão, Afrânio Kritski, and Domingos Alves
IOS Press
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.
Pedro Emilio Andrade Martins, Márcio Eloi Colombo Filho, Ana Clara de Andrade Mioto, Filipe Andrade Bernardi, Vinícius Costa Lima, Têmis Maria Félix, and Domingos Alves
Springer Nature Switzerland
Filipe Andrade Bernardi, Domingos Alves, Nathalia Crepaldi, Diego Bettiol Yamada, Vinícius Costa Lima, and Rui Rijo
JMIR Publications Inc.
Background Decision-making and strategies to improve service delivery must be supported by reliable health data to generate consistent evidence on health status. The data quality management process must ensure the reliability of collected data. Consequently, various methodologies to improve the quality of services are applied in the health field. At the same time, scientific research is constantly evolving to improve data quality through better reproducibility and empowerment of researchers and offers patient groups tools for secured data sharing and privacy compliance. Objective Through an integrative literature review, the aim of this work was to identify and evaluate digital health technology interventions designed to support the conducting of health research based on data quality. Methods A search was conducted in 6 electronic scientific databases in January 2022: PubMed, SCOPUS, Web of Science, Institute of Electrical and Electronics Engineers Digital Library, Cumulative Index of Nursing and Allied Health Literature, and Latin American and Caribbean Health Sciences Literature. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist and flowchart were used to visualize the search strategy results in the databases. Results After analyzing and extracting the outcomes of interest, 33 papers were included in the review. The studies covered the period of 2017-2021 and were conducted in 22 countries. Key findings revealed variability and a lack of consensus in assessing data quality domains and metrics. Data quality factors included the research environment, application time, and development steps. Strategies for improving data quality involved using business intelligence models, statistical analyses, data mining techniques, and qualitative approaches. Conclusions The main barriers to health data quality are technical, motivational, economical, political, legal, ethical, organizational, human resources, and methodological. The data quality process and techniques, from precollection to gathering, postcollection, and analysis, are critical for the final result of a study or the quality of processes and decision-making in a health care organization. The findings highlight the need for standardized practices and collaborative efforts to enhance data quality in health research. Finally, context guides decisions regarding data quality strategies and techniques. International Registered Report Identifier (IRRID) RR2-10.1101/2022.05.31.22275804
Filipe Andrade Bernardi, Bibiana Mello de Oliveira, Diego Bettiol Yamada, Milena Artifon, Amanda Maria Schmidt, Victória Machado Scheibe, Domingos Alves, and Têmis Maria Félix
JMIR Publications Inc.
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
Filipe Andrade Bernardi, Domingos Alves, Mariane Barros Neiva, Diego Bettiol Yamada, Vinicius Costa Lima, André Vinci, Giovane Thomazini, Rui Rijo, and Têmis Maria Felix
Elsevier BV
Nathalia Yukie Crepaldi, Vinicius Costa Lima, Filipe Andrade Bernardi, and Domingos Alves
Elsevier BV
Giovane Thomazini Soares, Diego Bettiol Yamada, Filipe Andrade Bernardi, Mariane Barros Neiva, Luis Pedro Lombardi Junior, André Luiz Teixeira Vinci, Ana Clara de Andrade Mioto, and Domingos Alves
Elsevier BV
Vinícius Costa Lima, Domingos Alves, Filipe Andrade Bernardi, and Rui Pedro Charters Lopes Rijo
IOS Press
Integration of health information systems are crucial to advance the effective delivery of healthcare for individuals and communities across organizational boundaries. Semantic Web technologies may be used to connect, correlate, and integrate heterogeneous datasets spread over the internet. However, when working with sensitive data, such as health data, security mechanisms are needed. A scoping review of the literature was undertaken to provide a broad view of security mechanisms applied to, or along with, Semantic Web technologies that could allow its use with health data. Searches were conducted in the most relevant databases for the scope of this work. The findings were classified according to the main objective and features presented by each solution. Twenty-six studies were included in the review. They introduced mechanisms that addressed several security attributes, such as authentication, authorization, integrity, availability, confidentiality, privacy, and provenance. These mechanisms support access control frameworks, semantic and functional interoperability infrastructures, and privacy compliance solutions. The findings suggest that the application and use of Semantic Web technologies is still growing, with the healthcare area being particularly interested. The main security mechanisms for Semantic Web technologies, the key security attributes and properties, and the main gaps in the literature were identified, helping to understand the technical needs to mitigate the risks of handling personal health information over the Semantic Web. Also, this research has shown that complex and robust solutions are available to successfully address several security properties and features, depending on the context that the electronic health data is being managed.
Maria Carolina Gironde Ataide, Filipe Andrade Bernardi, Paulo Mazzoncini de Azevedo Marques, and Cláudia Maria de Felício
FapUNIFESP (SciELO)
ABSTRACT Purpose The Orofacial Myofunctional Evaluation with Scores (OMES) protocol has been validated and used in clinical practice and research. The goals of this study were to develop, analyze and improve a version of OMES for the Web and to investigate the relationship between the usability judgments and the prior experience of the evaluators and whether using the interface promotes learning, as shown by the task completion time (TCT). Methods Study steps: 1) inspection of the prototype by the team; 2) evaluation of usability by three experienced speech-language pathologists (SLPs); and 3) evaluation of its usability by 12 SLPs with varying levels of experience in the use of OMES. Participants answered the Heuristic evaluation (HE), the Computer System Usability Questionnaire (CSUQ), and expressed free comments. The TCT was recorded. Results The OMES-Web reached excellent usability levels, and the participants were highly satisfied. The correlations between the participants’ experience and the HE and CSUQ scores were not significant. The TCT decreased significantly throughout the tasks. Conclusion OMES-Web meets the usability criteria, and participants feel satisfied with the system regardless of their level of experience. The fact that it is easy to learn favors its adoption by professionals.
Têmis Maria Félix, Bibiana Mello de Oliveira, Milena Artifon, Isabelle Carvalho, Filipe Andrade Bernardi, Ida V. D. Schwartz, Jonas A. Saute, Victor E. F. Ferraz, Angelina X. Acosta, Ney Boa Sorte,et al.
Orphanet journal of rare diseases Springer Science and Business Media LLC
AbstractThe 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.
Diego Bettiol Yamada, Filipe Andrade Bernardi, Márcio Eloi Colombo Filho, Mariane Barros Neiva, Vinícius Costa Lima, André Luiz Teixeira Vinci, Bibiana Mello de Oliveira, Têmis Maria Félix, and Domingos Alves
Springer International Publishing
Isabelle Carvalho, Mariane Barros Neiva, Newton Shydeo Brandão Miyoshi, Nathalia Yukie Crepaldi, Filipe Andrade Bernardi, Vinícius Costa Lima, Ketlin Fabri dos Santos, Ana Clara de Andrade Mioto, Mariana Tavares Mozini, Rafael Mello Galliez,et al.
Springer International Publishing
Vinicius Costa Lima, Felipe Carvalho Pellison, Filipe Andrade Bernardi, Domingos Alves, and Rui Pedro Charters Lopes Rijo
International Journal of Web Portals IGI Global
One of the critical challenges in health information systems is interoperability. The clinical, strategic, and operational decision depends on quality data and the ability to exchange data inter-systems and inter-health organizations. The Semantic Web plays a cornerstone role as a technology to enable functional and semantic interoperability without substantial changes in existing systems and to improve data sharing capabilities and, consequently, its quality and completeness. However, a common concern is data security. In this context, this research proposes a framework for securing health data, with a real case scenario focused on tuberculosis data exchange over the Semantic Web. The needs of security for the Semantic Web were satisfied, helping to build trust in the data and promoting its use in contexts that were not initially created to openly disseminate data without a significant technological apparatus.
Vinícius Lima, Filipe Bernardi, Rui Rijo, Jó Ueyama, and Domingos Alves
Studies in Health Technology and Informatics IOS Press
Background: Intensified research and innovation and rapid uptake of new tools, interventions, and strategies are crucial to fight Tuberculosis, the world’s deadliest infectious disease. The sharing of health data remains a significant challenge. Data consumers must be able to verify the consistency and integrity of data. Solutions based on distributed ledger technologies may be adequate, where each member in a network holds a unique credential and stores an identical copy of the ledger and contributes to the collective process of validating and certifying digital transactions. Objectives: This work proposes a mechanism and presents a use case in Digital Health to allow the verification of integrity and immutability of TB electronic health records. Methods: IOTA was selected as a supporting tool due to its data immutability, traceability and tamper-proof characteristics. Results: A mechanism to verify the integrity of data through hash functions and the IOTA network is proposed. Then, a set of TB related information systems was integrated with the network. Conclusion: IOTA technology offers performance and flexibility to enable a reliable environment for electronic health records.
Filipe Andrade Bernardi, Diego Bettiol Yamada, Bibiana Mello de Oliveira, Vinicius Costa Lima, Têmis Maria Félix, and Domingos Alves
Elsevier BV
Thomaz Felipe Soares Arnizant, Filipe Andrade Bernardi, Tiago Lara Michelin Sanchez, Nathalia Yukie Crepaldi, Thiago Nascimento do Prado, Marcelle Temporim Novaes, Ethel Leonor Noia Maciel, and Domingos Alves
Elsevier BV
Filipe Andrade Bernardi, Vinicius Costa Lima, Danilo Maglio Sampaio, Marcelo Cordeiro dos Santos, Rui Pedro Charters Lopes Rijo, and Domingos Alves
Elsevier BV
Vinícius Costa Lima, Filipe Andrade Bernardi, Michael Domingues, Afrânio Lineu Kritski, Rui Pedro Chaters Lopes Rijo, and Domingos Alves
Elsevier BV
Victor Cassão, Domingos Alves, Ana Clara de Andrade Mioto, Filipe Andrade Bernardi, and Newton Shydeo Brandão Miyoshi
Elsevier BV