Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare.

Autor:	Economou-Zavlanos NJ; Duke AI Health, Duke University School of Medicine, Durham, NC 27705, United States., Bessias S; Duke AI Health, Duke University School of Medicine, Durham, NC 27705, United States., Cary MP Jr; Duke AI Health, Duke University School of Medicine, Durham, NC 27705, United States.; Duke University School of Nursing, Durham, NC 27710, United States., Bedoya AD; Duke Health Technology Solutions, Duke University Health System, Durham, NC 27705, United States.; Department of Medicine, Duke University School of Medicine, Durham, NC 27710, United States., Goldstein BA; Duke AI Health, Duke University School of Medicine, Durham, NC 27705, United States.; Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC 27705, United States., Jelovsek JE; Department of Obstetrics and Gynecology, Duke University School of Medicine, Durham, NC 27710, United States., O'Brien CL; Duke Health Technology Solutions, Duke University Health System, Durham, NC 27705, United States.; Department of Medicine, Duke University School of Medicine, Durham, NC 27710, United States., Walden N; Duke AI Health, Duke University School of Medicine, Durham, NC 27705, United States., Elmore M; Duke AI Health, Duke University School of Medicine, Durham, NC 27705, United States., Parrish AB; Office of Regulatory Affairs and Quality, Duke University School of Medicine, Durham, NC 27705, United States., Elengold S; Office of Counsel, Duke University, Durham, NC 27701, United States., Lytle KS; Duke University School of Nursing, Durham, NC 27710, United States.; Duke Health Technology Solutions, Duke University Health System, Durham, NC 27705, United States., Balu S; Duke Institute for Health Innovation, Duke University, Durham, NC 27701, United States., Lipkin ME; Department of Urology, Duke University School of Medicine, Durham, NC 27710, United States., Shariff AI; Department of Medicine, Duke University School of Medicine, Durham, NC 27710, United States.; Duke Endocrine-Oncology Program, Duke University Health System, Durham, NC 27710, United States., Gao M; Duke Institute for Health Innovation, Duke University, Durham, NC 27701, United States., Leverenz D; Department of Medicine, Duke University School of Medicine, Durham, NC 27710, United States., Henao R; Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC 27705, United States.; Department of Bioengineering, King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia., Ming DY; Department of Medicine, Duke University School of Medicine, Durham, NC 27710, United States.; Duke Department of Pediatrics, Duke University Health System, Durham, NC 27705, United States.; Department of Population Health Sciences, Duke University School of Medicine, Durham, NC 27701, United States., Gallagher DM; Department of Medicine, Duke University School of Medicine, Durham, NC 27710, United States., Pencina MJ; Duke AI Health, Duke University School of Medicine, Durham, NC 27705, United States.; Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC 27705, United States., Poon EG; Duke Health Technology Solutions, Duke University Health System, Durham, NC 27705, United States.; Department of Medicine, Duke University School of Medicine, Durham, NC 27710, United States.; Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC 27705, United States.
Jazyk:	angličtina
Zdroj:	Journal of the American Medical Informatics Association : JAMIA [J Am Med Inform Assoc] 2024 Feb 16; Vol. 31 (3), pp. 705-713.
DOI:	10.1093/jamia/ocad221
Abstrakt:	Objective: The complexity and rapid pace of development of algorithmic technologies pose challenges for their regulation and oversight in healthcare settings. We sought to improve our institution's approach to evaluation and governance of algorithmic technologies used in clinical care and operations by creating an Implementation Guide that standardizes evaluation criteria so that local oversight is performed in an objective fashion. Materials and Methods: Building on a framework that applies key ethical and quality principles (clinical value and safety, fairness and equity, usability and adoption, transparency and accountability, and regulatory compliance), we created concrete guidelines for evaluating algorithmic technologies at our institution. Results: An Implementation Guide articulates evaluation criteria used during review of algorithmic technologies and details what evidence supports the implementation of ethical and quality principles for trustworthy health AI. Application of the processes described in the Implementation Guide can lead to algorithms that are safer as well as more effective, fair, and equitable upon implementation, as illustrated through 4 examples of technologies at different phases of the algorithmic lifecycle that underwent evaluation at our academic medical center. Discussion: By providing clear descriptions/definitions of evaluation criteria and embedding them within standardized processes, we streamlined oversight processes and educated communities using and developing algorithmic technologies within our institution. Conclusions: We developed a scalable, adaptable framework for translating principles into evaluation criteria and specific requirements that support trustworthy implementation of algorithmic technologies in patient care and healthcare operations. (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)
Databáze:	MEDLINE
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