Development of Core Competencies in Clinical Data Science Graduate Education: A Follow-On Tutorial to From Clinical Data Management to Clinical Data Science: Time for a New Educational Model.

Authors

Richard F Ittenbach, Courtney R McKeown

Published in

Clinical and translational science. Volume 19. Issue 7. Pages e70653.

Abstract

This paper presents a structured framework for designing a competency-based curriculum in clinical data science graduate education and serves as a follow-on to the 2023 tutorial From Clinical Data Management to Clinical Data Science: Time for a New Educational Model. The new hybridized knowledge base reflects the interdisciplinary demands of the field by integrating the parent disciplines of biostatistics, biomedical informatics, clinical medicine, and regulatory science. Core competencies for the graduate program were identified through expert review, alignment with professional societies' competencies for professional practice, and iterative faculty and practitioner validation. The resulting program comprises 10 courses mapped to professional standards and distilled into five overarching competencies to help translational scientists integrate the industry-based, mission-driven instructional strategies of prior eras with the more contemporary, scientifically oriented discipline of the future. This framework may be generalized to other content areas and disciplines within the translational science arena.

PMID:
42397859
Bibliographic data and abstract were imported from PubMed on 04 Jul 2026.

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