Data Science Journal (Jun 2019)

Proposed Guideline for Minimum Information Stroke Research and Clinical Data Reporting

  • Judit Kumuthini,
  • Lyndon Zass,
  • Melek Chaouch,
  • Michael Thompson,
  • Paul Olowoyo,
  • Mamana Mbiyavanga,
  • Faniyan Moyinoluwalogo,
  • Gordon Wells,
  • Victornia Nembeware,
  • Nicola J. Mulder,
  • Mayowa Owolabi,
  • H3ABioNet Consortium’s Data and Standard Working Group as members of the H3Africa Consortium

DOI
https://doi.org/10.5334/dsj-2019-026
Journal volume & issue
Vol. 18, no. 1

Abstract

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The management and analyses of large datasets is one of the grand challenges of modern biomedical research. Establishing methods to harmonise and standardise data collection, reporting, sharing and the employed data dictionaries, can support the resolution of these challenges whilst improving research quality, data quality and integrity, allowing sustainable knowledge transfer through re-usability, interoperability, reproducibility. The current project aimed to develop and propose a standardised reporting guideline for stroke research and clinical data reporting. Through systematic consolidation and harmonization of published data collection and reporting standards, several recommendations were drafted for the proposed guideline. These recommendations were reviewed by domain-researchers and clinicians using an online survey, developed in REDCap. The survey was completed by 20 international stroke-specialists, majority of respondents were based in Africa (10), followed by America, Europe and Australia (10). Of these respondents; the majority were working as dual clinician-researchers (57%) with more than 10 years’ experience in the field (78%). Data elements within the reporting standard were classified as participant-, study- and experiment-level information, further subdivided into essential or optional information, and defined using existing ontologies. The proposed reporting guideline can be employed for research utility and adapted for clinical utility as well. It is accompanied with an associated XML schema for REDCap implementation, to increase the user friendliness of data capturing, sharing, reporting and governance. Ultimately, the adoption of common reporting in stroke research has the potential to ensure that researchers gain the maximum benefit from their generated data and data collections.

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