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Plataforma dinâmica para armazenamento e gestão de dados de saúde
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Advisor(s)
Abstract(s)
Embora a gestão e preparação de dados constitua uma grande proporção do esforço total
envolvido na análise baseada nos registos de saúde eletrónicos, Electronic health record,
(EHR), as diretrizes atuais para a adquisição e processamento externo de EHR (fora dos
próprios sistemas de informação dos Hospitais e Centros de Saúde) são ainda insuficientes até
à data de hoje, e é uma realidade que os médicos e profissionais da saúde são confrontados
com o problema (desafio) de poder de extrair, processar e analisar quantidades suficientes de
EHR para a realização de investigação clínica conclusiva (com representatividade estatística).
Nesse sentido, neste projeto de dissertação de mestrado se propõe desenvolver uma
“Plataforma Dinâmica para Armazenamento e Gestão de Dados de Saúde” com foco nos
pacientes. Esta plataforma tem como objetivo três temas centrais: (1) simplificar o processo de
captura e anonimização dos dados dos pacientes; (2) gestão centralizada dos dados, evitando
a formação de silos e lacunas de dados; e o mais importante (3) automatizar o processo de
criação de datasets de benchmarking para agilizar, facilitar e melhorar o processamento e a
análise de grandes volumes de dados (EHR) nos processos de investigação clínica. Se
pretende ainda que esta plataforma seja agnóstica ao tipo de dados, i.e., garantindo que toda a
informação está centralizada no registo do paciente e que vincule / enlace todos os tipos de
dados (exames) possíveis desde simples dados de texto e valores numéricos até outras
estruturas de dados mais complexas.
Although data management and preparation constitutes a large proportion of the total effort involved in electronic health record (EHR) based analysis, current guidelines for external EHR acquisition and processing (outside of Hospitals and Health Centers' own information systems Health) are still insufficient nowadays, and it is a reality that doctors and health professionals are faced with the problem (challenge) of being able to extract, process and analyze sufficient amounts of EHR to carry out conclusive clinical research ( with statistical representativeness). In this sense, this master's dissertation project proposes to develop a “Dynamic Platform for Storage and Management of Health Data” with a focus on patients. This platform aims at three central themes: (1) simplify the process of capturing and anonymizing patient data; (2) centralized data management, avoiding the formation of silos and data gaps; and most importantly (3) automate the process of creating benchmarking datasets to streamline, facilitate and improve processing and analysis of large volumes of data (EHR) in clinical research processes. If you also want this platform to be agnostic to the type of data, i.e., ensuring that all information is centralized in the patient's record and that it links / links all types of data (exams) possible, from simple text data and numerical values to other more complex data structures.
Although data management and preparation constitutes a large proportion of the total effort involved in electronic health record (EHR) based analysis, current guidelines for external EHR acquisition and processing (outside of Hospitals and Health Centers' own information systems Health) are still insufficient nowadays, and it is a reality that doctors and health professionals are faced with the problem (challenge) of being able to extract, process and analyze sufficient amounts of EHR to carry out conclusive clinical research ( with statistical representativeness). In this sense, this master's dissertation project proposes to develop a “Dynamic Platform for Storage and Management of Health Data” with a focus on patients. This platform aims at three central themes: (1) simplify the process of capturing and anonymizing patient data; (2) centralized data management, avoiding the formation of silos and data gaps; and most importantly (3) automate the process of creating benchmarking datasets to streamline, facilitate and improve processing and analysis of large volumes of data (EHR) in clinical research processes. If you also want this platform to be agnostic to the type of data, i.e., ensuring that all information is centralized in the patient's record and that it links / links all types of data (exams) possible, from simple text data and numerical values to other more complex data structures.
Description
Keywords
Dados de saúde Bases de dados Gerenciamento dinâmico de dados Plataforma dinâmica EHR Health data Databases Dynamic data management Dynamic platform