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

J Biomed Inform. 2021 Feb:114:103669. doi: 10.1016/j.jbi.2020.103669. Epub 2020 Dec 24.

Abstract

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.

Keywords: Clinical research; Clinical search harmonization; Data Safe Havens.

MeSH terms

  • Humans
  • Infant, Newborn
  • Metadata*
  • Unified Medical Language System*