Bernardo Sousa-Pinto, Manuel Marques-Cruz, Ignacio Neumann, Yuan Chi, Artur J Nowak, Marge Reinap, Mariette Awad, Monika Nothacker, Milana Trucl, Jan Brozek, Pablo Alonso-Coello, Wojtek Wiercioch, Amir Qaseem, Elie A Akl, Holger J Schünemann
{"title":"Guidelines International Network: Principles for Use of Artificial Intelligence in the Health Guideline Enterprise.","authors":"Bernardo Sousa-Pinto, Manuel Marques-Cruz, Ignacio Neumann, Yuan Chi, Artur J Nowak, Marge Reinap, Mariette Awad, Monika Nothacker, Milana Trucl, Jan Brozek, Pablo Alonso-Coello, Wojtek Wiercioch, Amir Qaseem, Elie A Akl, Holger J Schünemann","doi":"10.7326/ANNALS-24-02338","DOIUrl":null,"url":null,"abstract":"<p><strong>Description: </strong>Artificial intelligence (AI) has been defined by the High-Level Expert Group on AI of the European Commission as \"systems that display intelligent behaviour by analysing their environment and taking actions-with some degree of autonomy-to achieve specific goals.\" Artificial intelligence has the potential to support guideline planning, development and adaptation, reporting, implementation, impact evaluation, certification, and appraisal of recommendations, which we will refer to as \"guideline enterprise.\" Considering this potential, as well as the lack of guidance for the use of AI in guidelines, the Guidelines International Network (GIN) proposes a set of principles for the development and use of AI tools or processes to support the health guideline enterprise.</p><p><strong>Methods: </strong>A GIN working group on AI developed these principles, informed by the results of a scoping review and practical examples, through iterative discussion.</p><p><strong>Recommendations: </strong>Eight principles were identified to adhere to when using AI in the guideline context: transparency, preplanning, additionality, credibility, ethics, accountability, compliance, and evaluation. These complementary principles are described in a comprehensive way, but they do not provide detailed instructions on how to use specific AI tools. Although these principles are expected to apply across different contexts and stages of the guideline enterprise, details on their implementation have some degree of flexibility. Guideline development groups choosing to use AI will be able to adequately implement the principles if they ensure aspects such as structured reporting on the use of AI tools, involvement of experts in AI, and allocation of funding for the adequate use of AI tools. The GIN principles may support guideline developers in the responsible and transparent use of AI to ensure trustworthy guidelines.</p>","PeriodicalId":7932,"journal":{"name":"Annals of Internal Medicine","volume":" ","pages":""},"PeriodicalIF":19.6000,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Internal Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.7326/ANNALS-24-02338","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0
Abstract
Description: Artificial intelligence (AI) has been defined by the High-Level Expert Group on AI of the European Commission as "systems that display intelligent behaviour by analysing their environment and taking actions-with some degree of autonomy-to achieve specific goals." Artificial intelligence has the potential to support guideline planning, development and adaptation, reporting, implementation, impact evaluation, certification, and appraisal of recommendations, which we will refer to as "guideline enterprise." Considering this potential, as well as the lack of guidance for the use of AI in guidelines, the Guidelines International Network (GIN) proposes a set of principles for the development and use of AI tools or processes to support the health guideline enterprise.
Methods: A GIN working group on AI developed these principles, informed by the results of a scoping review and practical examples, through iterative discussion.
Recommendations: Eight principles were identified to adhere to when using AI in the guideline context: transparency, preplanning, additionality, credibility, ethics, accountability, compliance, and evaluation. These complementary principles are described in a comprehensive way, but they do not provide detailed instructions on how to use specific AI tools. Although these principles are expected to apply across different contexts and stages of the guideline enterprise, details on their implementation have some degree of flexibility. Guideline development groups choosing to use AI will be able to adequately implement the principles if they ensure aspects such as structured reporting on the use of AI tools, involvement of experts in AI, and allocation of funding for the adequate use of AI tools. The GIN principles may support guideline developers in the responsible and transparent use of AI to ensure trustworthy guidelines.
期刊介绍:
Established in 1927 by the American College of Physicians (ACP), Annals of Internal Medicine is the premier internal medicine journal. Annals of Internal Medicine’s mission is to promote excellence in medicine, enable physicians and other health care professionals to be well informed members of the medical community and society, advance standards in the conduct and reporting of medical research, and contribute to improving the health of people worldwide. To achieve this mission, the journal publishes a wide variety of original research, review articles, practice guidelines, and commentary relevant to clinical practice, health care delivery, public health, health care policy, medical education, ethics, and research methodology. In addition, the journal publishes personal narratives that convey the feeling and the art of medicine.