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CMIID: A comprehensive medical information identifier for clinical search harmonization in Data Safe Havens

Title
CMIID: A comprehensive medical information identifier for clinical search harmonization in Data Safe Havens
Type
Article in International Scientific Journal
Year
2021
Authors
Domingues, MAP
(Author)
Other
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Camacho, R
(Author)
Other
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Rodrigues, PP
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
Journal
Vol. 114
ISSN: 1532-0464
Publisher: Elsevier
Indexing
Publicação em ISI Web of Knowledge ISI Web of Knowledge - 0 Citations
Other information
Authenticus ID: P-00X-76K
Abstract (EN): Over the last decades clinical research has been driven by informatics changes nourished by distinct research endeavors. Inherent to this evolution, several issues have been the focus of a variety of studies: multi-location patient data access, interoperability between terminological and classification systems and clinical practice and records harmonization. Having these problems in mind, the Data Safe Haven paradigm emerged to promote a newborn architecture, better reasoning and safe and easy access to distinct Clinical Data Repositories. This study aim is to present a novel solution for clinical search harmonization within a safe environment, making use of a hybrid coding taxonomy that enables researchers to collect information from multiple repositories based on a clinical domain query definition. Results show that is possible to query multiple repositories using a single query definition based on clinical domains and the capabilities of the Unified Medical Language System, although it leads to deterioration of the framework response times. Participants of a Focus Group and a System Usability Scale questionnaire rated the framework with a median value of 72.5, indicating the hybrid coding taxonomy could be enriched with additional metadata to further improve the refinement of the results and enable the possibility of using this system as data quality tagging mechanism.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 12
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