This paper is in the following e-collection/theme issue:
Generative Language Models Including ChatGPT (1654) Digital Health, Telehealth and e-Innovation in Clinical Settings (755) New Methods and Approaches in Medical Education (687) Artificial Intelligence (5063)Published on in Vol 28 (2026)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/100531, first published
.

Development and Pilot Evaluation of a Standardized and Accessible Rubric (OMNI) for Assessing Generative AI in Health Care Contexts: Four-Stage Mixed Methods Study
Development and Pilot Evaluation of a Standardized and Accessible Rubric (OMNI) for Assessing Generative AI in Health Care Contexts: Four-Stage Mixed Methods Study
Authors of this article:
Erik Cornelisse1
;
Dib Kousa1
;
Bradley D Menz1
;
Brinleigh Murphy-Reuter2
;
Adel Shahnam3
;
Benjamin Chin-Yee4
;
Ryan Calabro5
;
Lee X Li1
;
Imogen Ramsey6
;
Ahmad Y Abuhelwa7
;
Jessica M Logan8
;
Huah Shin Ng1
;
Mythily Aravinthan9
;
James Goonan9
;
Hannah Carthew9
;
Paul Molyneux10
;
Joanne Tang11
;
Nadia Hitchen12, 13
;
Martin Hong14
;
Jimit Gandhi8, 15
;
Stephanie Fontanarosa15
;
Nicholas L Scarfo15
;
Kezia Daniel15
;
Sally B Marotti1, 8, 15
;
Joy Mariadas1
;
Bianca van Diermen10
;
Divya Joyce Susai Manickam9
;
Warit Ruanglertboon16, 17
;
David Postma1
;
Melissa D McCradden18, 19, 20
;
Sandeep Reddy21
;
Stephen Bacchi1, 22
;
Arduino A Mangoni1, 23
;
Ross A McKinnon1
;
Ganessan Kichenadasse1, 24
;
Gary H Lyman25, 26
;
Nicole M Kuderer27
;
Michael J Sorich1
;
Andrew Rowland1
;
Ashley M Hopkins1
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