Towards a Reliable Integration Process That Prioritizes Content

• Autor(a) principal: Pacheco, Pedro Filipe Monteiro
• Data de Publicação: 2021
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.22/19948
• topic: Data; ETL; Integration; Integrity; Reliability; Healthcare

The healthcare market increasingly demands Information Technology (IT) systems to reliably integrate information between them. ALERT®, a healthcare IT solution provided by the ALERT company, is a suite of products that integrates the workflow of different healthcare professionals. One of its many functionalities is medication prescription, which obviously requires medication content. This content is provided by external parties and needs to be properly integrated into the ALERT® product. Thus, a solution that appropriately extracts, transforms, and loads such information from multiple sources into its final destination is required. With that in mind, the current project documents all the required development phases for a proper creation of such solution. This includes background research, analysis, design, implementation, and evaluation. The main contribution of this dissertation is an approach for the creation of reliable data integration processes in complex systems, where data integrity is of extreme importance. To do so, a general-purpose Extraction-Transformation-Loading (ETL) framework, entitled ETL Framework (ETLF), has been conceived for that effect. Afterwards, with this software framework, a Medication Integration Platform (MIP) for ALERT® was also created. This platform allows a systematic creation of new medication ETL processes, while ensuring data integrity. In its final appraisal, it was concluded that the developed platform is completely capable of systematically creating new ETL processes that, when avoidable, do not require human interaction. Additionally, it was also concluded that processes built using this platform are sustainable ETL processes that ensure the reliability of data.