A platform for integration, data acquisition and data analysis in electronical medical records

Nome do Pesquisador: Fernanda Nascimento Almeida

Agência de fomento: Sem financiamento

Vigência: 06/2016 à 02/2019

Outros Colaboradores:
Tatiane Martins Pacheco

Resumo: Relevant and updated information are crucial to improving decision-making in health care systems. Information access in a timely manner can be the difference between success and failure in a medical process. Electronic medical records (EMR) are used to help manage and store patience record, which include notes of diagnoses, test results, procedures employed during the treatment, among others. This information is considered a fundamental requirement for the development of practices aimed at improving the quality of patient care. Besides aggregating important patient data, this kind of system also enables information sharing between different professionals and the integration of services performed. However, the implementation of such systems is highly complex since they generally combine data from different sources, which have multiple representations and can cause serious problems. As a consequence, the extracted information and results may not be useful to experts, since they might not be able to properly assess the reliability of the generated results. We know that this problem occurs because the information and rules used to generate specific datasets are not preserved. That is, these system generally do not store provenance data. With in mind, we propose the managment system, based on expert knowledge to management and extract more reliable information. This knowledge can be an important ally for the understanding of relevant issues for medicine. We aim to develop a unified platform for the integration of different functionalities, ranging from data acquisition to the methods used to facilitate the extraction of information for data analysis. We aim to create a platform that can be used by health professionals in order to assist medical diagnosis by providing a refined analysis, contributing to the improvement of predictive, preventive and personalized treatments.

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