Programa de Pós-Graduação em Engenharia Elétrica e de Computação
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Master Thesis Trilhas para auditoria aplicada ao sistema único de saúde no contexto das órteses, próteses e materiais especiais (OPMES): estruturação de uma base de dados integrada a partir do projeto fiscalizasus(Universidade Federal do Rio Grande do Norte, 2025-06-26) Alves, Luca Pareja Credidio Freire; Valentim, Ricardo Alexsandro de Medeiros; https://orcid.org/0000-0002-9216-8593; http://lattes.cnpq.br/3181772060208133; http://lattes.cnpq.br/8782837208577002; Valentim, Janaína Luana Rodrigues da Silva; https://orcid.org/0000-0001-8525-8155; http://lattes.cnpq.br/8236259645905686; Santos, João Paulo Queiroz dos; https://orcid.org/0000-0002-9130-7723; http://lattes.cnpq.br/2413250851590746; Coutinho, Karilany Dantas; https://orcid.org/0000-0002-2051-8611; http://lattes.cnpq.br/8409211766785367; Oliveira, Luiz Affonso Henderson Guedes de; https://orcid.org/0000-0003-2690-1563; http://lattes.cnpq.br/7987212907837941; Rodrigues Júnior, Methanias Colaço; Costa, Theo Duarte da; https://orcid.org/0000-0002-9355-8382; http://lattes.cnpq.br/8305343735444335Background: The Unified Health System (SUS) was a historic milestone established by the 1988 federal constitution. However, over the years the SUS has undergone several transformations, especially concerning the amount of data generated about its internal processes. The National Audit Department of SUS (DenaSUS) was created to manage the SUS's internal control and audit processes. As a result, new demands regarding auditing in the SUS have emerged. One of these activities was organized in partnership between DenaSUS, the Federal University of Rio Grande do Norte (UFRN), the Federal Institute of Rio Grande do Norte (IFRN), the Federal Prosecution Office of Rio Grande do Norte (MPF/RN), the Federal Court of Auditors (TCU) and other competent authorities to build the FiscalizaSUS project, which aims to provide intelligent methods for analyzing large volumes of data in the field of health, with the ultimate goal of delivering audit trails focused on Regulation and Special Orthotics, Prosthetics and Special Materials (OPSM) in the SUS domain, as these are inputs that have already been identified as objects of interest in corruption scandals involving health professionals, as was the case with the “máfia das próteses”.Goal : Thus, the objective of this work is to demonstrate how the application of statistical methods and Big Data can enhance the feasibility for developing OPSM audit trails through the integration of public and private databases. Methods: On the first hand, a systematic mapping of the literature was conducted in order to evaluate which methods are being applied for Big Data-based health audit research. From this point of view, it was possible to analyse and adopt approaches to develop a relational model for OPSM audit trials, and also develop metrics based on statistical analysis of the collected data samples. Results : The Systematic Literature Mapping (SLM) initially included a total of 344 articles, obtained from the search string used. This left 40 articles for evaluation and data collection, after the inclusion and exclusion steps. Heterogeneous solutions were identified to address the issue of health auditing, presenting techniques also related to computational methods and Big Data approaches.From an operational perspective, the tables were organized oriented towards a star schema, containing fact and dimension tables, which enable the integration of different data from various sources, also concerning the goals of each audit trail and assessing the presence of common values between the databases. Nevertheless, the integration between the databases also provided a visualization layer by using Apache Superset’s virtual interface, allowing a comprehensive view of the anomalies through geographical location, links between the data sources, and also through the proposed metrics. Conclusion: The results allow us to conclude that the integration of different data sources related to OPSM can contribute to the identification of irregularities in transactional processes involving this type of medical supply. In addition, the Big Data architecture provided by the FiscalizaSUS project also made it possible to aggregate these different data sets and brought new perspectives to the health audit trails within the scope of the project.