Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-27T18:55:45.331Z Has data issue: false hasContentIssue false
  • English
  • Français

183 Translational Health Informatics Support Service Practices, Challenges, and Facilitators

Part of: JCTS_2024_ABSTRACT_COLLECTION

Published online by Cambridge University Press:  03 April 2024

Boris Volkov ,
Chris Pulley ,
Gretchen Sieger  and
Steve Johnson
Boris Volkov
Affiliation:
University of Minnesota Clinical and Translational Science Institute University of Minnesota Institute for Health Informatics University of Minnesota Division of Epidemiology and Community Health
Chris Pulley
Affiliation:
University of Minnesota Clinical and Translational Science Institute
Gretchen Sieger
Affiliation:
University of Minnesota Institute for Health Informatics
Steve Johnson
Affiliation:
University of Minnesota Institute for Health Informatics
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

OBJECTIVES/GOALS: METHODS/STUDY POPULATION: Utilized novel TS evaluation methods and tools: - Translational Science Case Study protocol adapted to examine translational support service practices, barriers and facilitators influencing translational movement. - Translational Science Benefits Model (TSBM) Checklist elements for translational/research impact analysis. Triangulated diverse data sources: - Primary data: semi-structured interviews with translational service stakeholders. - Secondary data: service’s applications, reports, and publications; public stories/news related to their research support; scientific publications; organizational/policy documents; and interviews with research stakeholders featured in published sources. RESULTS/ANTICIPATED RESULTS: Translational challenges include: complexity and constant change of health data; lack of data/informatics literacy amongst researchers; limited appreciation and funding for research data services; silos of functionality and data related to biomedical informatics. Translational facilitators are: the UMN CTSA support; available infrastructure and knowledge base; researchers as the best promoters for services; multidisciplinary collaborations with research/community/healthcare teams; best practice approaches; and learning by doing. The translational/research support service contributes to community and public health, clinical/medical benefits, data literacy, catalyzing data-rich research, and health equity. DISCUSSION/SIGNIFICANCE: The evaluation case study provides evidence and lessons learned related to translational benefits, challenges, and facilitators of a successful translational research support service integrating best informatics practices in clinical research and contributing to health equity improvement.

Type
Evaluation
Information
Journal of Clinical and Translational Science , Volume 8 , Issue s1 , April 2024 , pp. 55
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s), 2024. The Association for Clinical and Translational Science