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How can artificial intelligence decrease cognitive and work burden for front line practitioners?
Gandhi, Tejal K; Classen, David; Sinsky, Christine A; Rhew, David C; Vande Garde, Nikki; Roberts, Andrew; Federico, Frank.
Afiliación
  • Gandhi TK; Press Ganey Associates LLC, Boston, MA 02109, United States.
  • Classen D; Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT 84132, United States.
  • Sinsky CA; Professional Satisfaction & Practice Sustainability, American Medical Association, Chicago, IL 60611, United States.
  • Rhew DC; Worldwide Commercial, Microsoft, San Francisco, CA 94103, United States.
  • Vande Garde N; Patient Safety, Oracle Health, Kansas City, MO 64138, United States.
  • Roberts A; Data Science, Oracle Health, Kansas City, MO 64138, United States.
  • Federico F; Institute for Healthcare Improvement, Boston, MA 02109, United States.
JAMIA Open ; 6(3): ooad079, 2023 Oct.
Article en En | MEDLINE | ID: mdl-37655124
Artificial intelligence (AI) has tremendous potential to improve the cognitive and work burden of clinicians across a range of clinical activities, which could lead to reduced burnout and better clinical care. The recent explosion of generative AI nicely illustrates this potential. Developers and organizations deploying AI have a responsibility to ensure AI is designed and implemented with end-user input, has mechanisms to identify and potentially reduce bias, and that the impact on cognitive and work burden is measured, monitored, and improved. This article focuses specifically on the role AI can play in reducing cognitive and work burden, outlines the critical issues associated with the use of AI, and serves as a call to action for vendors and users to work together to develop functionality that addresses these challenges.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: JAMIA Open Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: JAMIA Open Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos