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GIN-McMaster Guideline Development Checklist Extension for Integrating Artificial Intelligence in the Health Guideline Enterprise.

Created on 15 Sep 2026

Authors

Manuel Marques-Cruz, Bernardo Sousa-Pinto, Ignacio Neumann, Yuan Chi, Monika Nothacker, Artur Nowak, Marge Reinap, Mariette Awad, Pablo Alonso-Coello, Amir Qaseem, Elie A Akl, Wojtek Wiercioch, Jan Brozek, Holger J Schünemann, GIN AI working group

Published in

Clinical and public health guidelines. Volume 3. Issue 3. Pages e70073. Epub May 30, 2026.

Abstract

Artificial intelligence (AI) may support several processes of the health guideline enterprise. This article describes the development of an extension of the Guidelines International Journal (GIN)-McMaster Guideline Development Checklist (GDC) for integrating AI in the guideline enterprise. This development has been led by the GIN-AI Working Group.
We started by prompting a large language model (LLM) for items related to the use of AI in each of the steps of the original GDC. Subsequently, the members of the working group engaged in a set of iterative discussions, resulting in item refinement and in a consensus first version of the extension. We retrospectively applied this first version to a case use of guidelines incorporating AI in their development (Allergic Rhinitis and its Impact on Asthma [ARIA] 2024-2025 guidelines), leading to further refinement and to the approval of the final extension tool.
Prompting LLMs resulted in the generation of 149 items. Of those, 117 were removed and 19 were modified by members of the working group. On the other hand, 17 new items were added during the iterative discussion process. The retrospective application of the extension led to changes in the wording of four items. The final version of the checklist extension has been approved with 49 items modifying or adding to the original GDC.
We have developed an extension of the GIN-McMaster GDC that encompasses a set of conduct standards that are intended to facilitate the comprehensive and transparent integration of AI in the health guideline enterprise.
Not applicable. This study is not a clinical trial.

PMID:
42740749
Bibliographic data and abstract were imported from PubMed on 15 Sep 2026.

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