Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/37465
Title: Patient data discovery platforms as enablers of biomedical and translational research: a systematic review
Author: Trifan, Alina
Oliveira, José Luís
Keywords: Biomedical data discovery
Discovery platforms
Data interoperability
Secondary use of data
Translational research
Issue Date: May-2019
Publisher: Elsevier
Abstract: Background: The global shift from paper health records to electronic ones has led to an impressive growth of biomedical digital data along the past two decades. Exploring and extracting knowledge from these data has the potential to enhance translational research and lead to positive outcomes for the population’s health and healthcare. Obective: The aim of this study was to conduct a systematic review to identify software platforms that enable discovery, secondary use and interoperability of biomedical data. Additionally, we aim evaluating the identified solutions in terms of clinical interest and main healthcare-related outcomes. Methods: A systematic search of the scientific literature published and indexed in Pubmed between January 2014 and September 2018 was performed. Inclusion criteria were as follows: relevance for the topic of bio- medical data discovery, English language, and free full text. To increase the recall, we developed a semi-auto- matic and incremental methodology to retrieve articles that cite one or more of the previous set. Results: A total number of 500 candidate papers were retrieved through this methodology. Of these, 85 were eligible for abstract assessment. Finally, 37 studies qualified for a full-text review, and 20 provided enough information for the study objectives. Conclusions: This study revealed that biomedical discovery platforms are both a current necessity and a sig- nificantly innovative agent in the area of healthcare. The outcomes that were identified, in terms of scientific publications, clinical studies and research collaborations stand as evidence.
Peer review: yes
URI: http://hdl.handle.net/10773/37465
DOI: 10.1016/j.jbi.2019.103154
Appears in Collections:DETI - Artigos
IEETA - Artigos

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