Reassessing the evidence linking clinical leadership to AI deployment outcomes

Li et al. report that clinician last authorship is associated with greater “impact” in AI deployment trials. This commentary argues that current evidence is insufficient to attribute this to clinical leadership per se. Concerns include outcome definition in a literature where 88% of trials are positive, statistical instability from only 13 non-events, authorship as a noisy proxy for leadership, and structural confounding by trial design and geography.

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Publication Details

Journal
npj Digital Medicine
Published
2026-06-13
DOI
https://doi.org/10.1038/s41746-026-02911-z
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Reassessing the evidence linking clinical leadership to AI deployment outcomes

Henry Bair
npj Digital Medicine
Artificial Intelligence in Healthcare and Education
article

Reassessing the evidence linking clinical leadership to AI deployment outcomes

Henry Bair
article en

Abstract

Li et al. report that clinician last authorship is associated with greater “impact” in AI deployment trials. This commentary argues that current evidence is insufficient to attribute this to clinical leadership per se. Concerns include outcome definition in a literature where 88% of trials are positive, statistical instability from only 13 non-events, authorship as a noisy proxy for leadership, and structural confounding by trial design and geography.

npj Digital MedicineVol. 9(1)
Wills Eye Hospital (US)
Openalex Percentile: Top 8%
Artificial Intelligence in Healthcare and Education
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Reassessing the evidence linking clinical leadership to AI deployment outcomes — Henry Bair · npj Digital Medicine (2026) | TGRS Research Map | TGRS