Evidence map›Paper›PMID 42397859›Full record

ArticleClinical and translational science2026

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.

Richard F Ittenbach, Courtney R McKeown

Abstract read
In one paragraph

Article in Clinical and translational science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Richard F IttenbachCincinnati Children's Hospital, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA.ORCID 0000-0002-7914-4298
Courtney R McKeownBiological Science, Denison University, Granville, Ohio, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Competency-Based EducationData ManagementData ScienceEducation, Biological and Biomedical Sciences, GraduateEducation, GraduateModels, EducationalTranslational Science, BiomedicalCurriculumHumansTranslational Research, Biomedicalbioinformaticsbiostatisticsclinical trialseducationregulatorytranslational science

Identifiers

PMID42397859
PMCPMC13331204

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.