Implementing a data integration infrastructure for healthcare data: A case study

• Autor(a) principal: Mira, Miguel Pratas Ferreira
• Data de Publicação: 2023
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10071/29144
• topic: Dados médicos -- Medical data; Data integration; Data warehouse; COVID-19; Doença cardiovascular -- Cardiovascular disease; Integração de dados

In this master thesis, the challenges and opportunities in health data integration are addressed, focusing on data from patients with a history of cardiovascular disease diagnosed with COVID-19. The main objective of this research was to develop a comprehensive approach for integrating health data from a Portuguese hospital into a common shared repository within the scope of a European Project. For this purpose, the characteristics and specificities of the hospital and target database data were analyzed, ensuring the privacy and security of all the information used. In addition, an ETL architecture was developed to perform the hospital's data extraction, transformation and loading to the target database. The research methodology involved a literature review that identified gaps in current practices, including interoperability between healthcare systems, standardization of formats and terminologies, privacy issues, and technical and organizational challenges. The success of the ETL process and the completeness of the target database were evaluated using appropriate metrics, demonstrating the effectiveness of this process. This work contributes to the research field of health data integration by addressing the challenges and opportunities in health data management and analysis in patients with a history of cardiovascular disease diagnosed with COVID- 19. The developed ETL architecture and ETL process evaluation confirm the feasibility of the proposed approach. The results highlight the importance of data privacy, interoperability, and advanced data analysis techniques in healthcare.